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1.
  • Adam, Constantin, et al. (författare)
  • A Middleware Design for Large-scale Clusters offering Multiple Services
  • 2006
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 3:1, s. 1-12
  • Tidskriftsartikel (refereegranskat)abstract
    • We present a decentralized design that dynamically allocates resources to multiple services inside a global server cluster. The design supports QoS objectives (maximum response time and maximum loss rate) for each service. A system administrator can modify policies that assign relative importance to services and, in this way, control the resource allocation process. Distinctive features of our design are the use of an epidemic protocol to disseminate state and control information, as well as the decentralized evaluation of utility functions to control resource partitioning among services. Simulation results show that the system operates both effectively and efficiently; it meets the QoS objectives and dynamically adapts to load changes and to failures. In case of overload, the service quality degrades gracefully, controlled by the cluster policies.
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2.
  • Adam, Constantin, et al. (författare)
  • Service middleware for self-managing large-scale systems
  • 2007
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 4:3, s. 50-64
  • Tidskriftsartikel (refereegranskat)abstract
    • Resource management poses particular challenges in large-scale systems, such as server clusters that simultaneously process requests from a large number of clients. A resource management scheme for such systems must scale both in the in the number of cluster nodes and the number of applications the cluster supports. Current solutions do not exhibit both of these properties at the same time. Many are centralized, which limits their scalability in terms of the number of nodes, or they are decentralized but rely on replicated directories, which also reduces their ability to scale. In this paper, we propose novel solutions to request routing and application placementtwo key mechanisms in a scalable resource management scheme. Our solution to request routing is based on selective update propagation, which ensures that the control load on a cluster node is independent of the system size. Application placement is approached in a decentralized manner, by using a distributed algorithm that maximizes resource utilization and allows for service differentiation under overload. The paper demonstrates how the above solutions can be integrated into an overall design for a peer-to-peer management middleware that exhibits properties of self-organization. Through complexity analysis and simulation, we show to which extent the system design is scalable. We have built a prototype using accepted technologies and have evaluated it using a standard benchmark. The testbed measurements show that the implementation, within the parameter range tested, operates efficiently, quickly adapts to a changing environment and allows for effective service differentiation by a system administrator.
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3.
  • Alizadeh Noghani, Kyoomars, et al. (författare)
  • Multi-Objective genetic algorithm for fast service function chain reconfiguration
  • 2023
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4537. ; 20:3, s. 3501-3522
  • Tidskriftsartikel (refereegranskat)abstract
    • The optimal placement of virtual network functions (VNFs) improves the overall performance of servicefunction chains (SFCs) and decreases the operational costs formobile network operators. To cope with changes in demands,VNF instances may be added or removed dynamically, resourceallocations may be adjusted, and servers may be consolidated.To maintain an optimal placement of SFCs when conditionschange, SFC reconfiguration is required, including the migration of VNFs and the rerouting of service-flows. However, suchreconfigurations may lead to stress on the VNF infrastructure,which may cause service degradation. On the other hand, notchanging the placement may lead to suboptimal operation,and servers and links may become congested or underutilized,leading to high operational costs. In this paper, we investigatethe trade-off between the reconfiguration of SFCs and theoptimality of their new placement and service-flow routing. Wedevelop a multi-objective genetic algorithm that explores thePareto front by balancing the optimality of the new placementand the cost to achieve it. Our numerical evaluations show thata small number of reconfigurations can significantly reduce theoperational cost of the VNF infrastructure. In contrast, toomuch reconfiguration may not pay off due to high costs. Webelieve that our work provides an important tool that helpsnetwork providers to plan a good reconfiguration strategy fortheir service chains.
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4.
  • Azari, Amin, 1988-, et al. (författare)
  • Reliable and Energy-Efficient IoT Systems : Design Considerations in Coexistence Deployments
  • 2023
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4537. ; 20:3, s. 2412-2427
  • Tidskriftsartikel (refereegranskat)abstract
    • Currently, there is a plethora of low-power wide-area IoT networking solutions available, each targeting a specific niche of use-cases and deployment scenarios. Existing studies on reliability evaluations of IoT solutions rely on the assumption that a single technology is deployed in the service area, or different IoT technologies operate over dedicated spectrum bands. Here, we investigate the reliability performance of IoT communications in coexisting scenarios, where multiple competing radio-access technologies share spectrum resources. Our focus is on solutions exploiting grant-free communications, which are gaining traction due to their potential to lower the energy consumption, and have been adopted in recent IoT technologies like SigFox and LoRa. We first derive an analytical model of the interference, comprising both inter- and intra-technology interference sources. We then leverage the Poisson Cluster Process for modeling distribution of devices in the service area, and derive expressions for the communication reliability, energy consumption, and battery lifetime of IoT devices. Exploiting these expressions, we study the energy-reliability trade-offs and investigate strategies to maintain or improve communication reliability, while minimizing energy consumption in coexisting scenarios by proper adjustment of communications parameters at the device side and provisioning resources at the network side. We verify the analytical results via numerical evaluations, confirming their accuracy and performing optimization in some example networking setups.
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5.
  • Behravesh, Rasaoul, et al. (författare)
  • Machine Learning at the Mobile Edge : The Case of Dynamic Adaptive Streaming over HTTP (DASH)
  • 2022
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers Inc.. - 1932-4537. ; 19:4, s. 4779-4793
  • Tidskriftsartikel (refereegranskat)abstract
    • Dynamic Adaptive Streaming over HTTP (DASH) is a standard for delivering video in segments and adapting each segment’s bitrate (quality), to adjust to changing and limited network bandwidth. We study segment prefetching, informed by machine learning predictions of bitrates of client segment requests, implemented at the network edge. We formulate this client segment request prediction problem as a supervised learning problem of predicting the bitrate of a client’s next segment request, in order to prefetch it at the mobile edge, with the objective of jointly improving the video streaming experience for the users and network bandwidth utilization for the service provider. The results of extensive evaluations showed a segment request prediction accuracy of close to 90% and reduced video segment access delay with a cache hit ratio of 58%, and reduced transport network load by lowering the backhaul link utilization by 60.91%.
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6.
  • Behravesh, Rasoul, et al. (författare)
  • Time-Sensitive Mobile User Association and SFC Placement in MEC-Enabled 5G Networks
  • 2021
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 18:3, s. 3006-3020
  • Tidskriftsartikel (refereegranskat)abstract
    • The ongoing roll-out of 5G networks paves the way for many fascinating applications such as virtual reality (VR), augmented reality (AR), and autonomous driving. Moreover, 5G enables billions of devices to transfer an unprecedented amount of data at the same time. This transformation calls for novel technologies like multi-access edge computing (MEC) to satisfy the stringent latency and bitrate requirements of the mentioned applications. The main challenge pertaining to MEC is that the edge MEC nodes are usually characterized by scarce computational resources compared to the core or cloud, arising the challenge of efficiently utilizing the edge resources while ensuring that the service requirements are satisfied. When considered with the users’ mobility, this poses another challenge, which lies in minimization of the service interruption for the users whose service requests are represented as service function chains (SFCs) composed of virtualized network functions (VNFs) instantiated on the MEC nodes or on the cloud. In this paper, we study the problem of joint user association, SFC placement, and resource allocation, employing mixed-integer linear programming (MILP) techniques. The objective function of this MILP-based problem formulation are to minimize (i) the service provisioning cost, (ii) the transport network utilization, and (iii) the service interruption. Moreover, a heuristic algorithm is proposed to tackle the scalability issue of the MILP-based algorithms. Finally, comprehensive experiments are performed to draw a comparison between these approaches.
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7.
  • Boldt, Martin, et al. (författare)
  • Alarm prediction in cellular base stations using data-driven methods
  • 2021
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers Inc.. - 1932-4537. ; 18:2, s. 1925-1933
  • Tidskriftsartikel (refereegranskat)abstract
    • The importance of cellular networks continuously increases as we assume ubiquitous connectivity in our daily lives. As a result, the underlying core telecom systems have very high reliability and availability requirements, that are sometimes hard to meet. This study presents a proactive approach that could aid satisfying these high requirements on reliability and availability by predicting future base station alarms. A data set containing 231 internal performance measures from cellular (4G) base stations is correlated with a data set containing base station alarms. Next, two experiments are used to investigate (i) the alarm prediction performance of six machine learning models, and (ii) how different predict-ahead times (ranging from 10 min to 48 hours) affect the predictive performance. A 10-fold cross validation evaluation approach and statistical analysis suggested that the Random Forest models showed best performance. Further, the results indicate the feasibility of predicting severe alarms one hour in advance with a precision of 0.812 (±0.022, 95 % CI), recall of 0.619 (±0.027) and F1-score of 0.702 (±0.022). A model interpretation package, ELI5, was used to identify the most influential features in order to gain model insight. Overall, the results are promising and indicate the potential of an early-warning system that enables a proactive means for achieving high reliability and availability requirements. IEEE
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8.
  • Cao, Yuan, et al. (författare)
  • Multi-Tenant Provisioning for Quantum Key Distribution Networks With Heuristics and Reinforcement Learning : A Comparative Study
  • 2020
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4537. ; 17:2, s. 946-957
  • Tidskriftsartikel (refereegranskat)abstract
    • Quantum key distribution (QKD) networks are potential to be widely deployed in the immediate future to provide long-term security for data communications. Given the high price and complexity, multi-tenancy has become a cost-effective pattern for QKD network operations. In this work, we concentrate on addressing the online multi-tenant provisioning (On-MTP) problem for QKD networks, where multiple tenant requests (TRs) arrive dynamically. On-MTP involves scheduling multiple TRs and assigning non-reusable secret keys derived from a QKD network to multiple TRs, where each TR can be regarded as a high-security-demand organization with the dedicated secret-key demand. The quantum key pools (QKPs) are constructed over QKD network infrastructure to improve management efficiency for secret keys. We model the secret-key resources for QKPs and the secret-key demands of TRs using distinct images. To realize efficient On-MTP, we perform a comparative study of heuristics and reinforcement learning (RL) based On-MTP solutions, where three heuristics (i.e., random, fit, and best-fit based On-MTP algorithms) are presented and a RL framework is introduced to realize automatic training of an On-MTP algorithm. The comparative results indicate that with sufficient training iterations the RL-based On-MTP algorithm significantly outperforms the presented heuristics in terms of tenant-request blocking probability and secret-key resource utilization.
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9.
  • Dan, Jurca, et al. (författare)
  • H-GAP : Estimating Histograms of Local Variables with Accuracy Objectives for Distributed Real-Time Monitoring
  • 2010
  • Ingår i: IEEE Transactions on Network and Service Management. - : IEEE Communications Society. - 1932-4537. ; 7:2, s. 83-95
  • Tidskriftsartikel (refereegranskat)abstract
    • We present H-GAP, a protocol for continuous monitoring,which provides a management station with the valuedistribution of local variables across the network. The protocolestimates the histogram of local state variables for a givenaccuracy and with minimal overhead. H-GAP is decentralizedand asynchronous to achieve robustness and scalability, and itexecutes on an overlay interconnecting management processesin network devices. On this overlay, the protocol maintains aspanning tree and updates the histogram through incrementalaggregation. The protocol is tunable in the sense that it allowscontrolling, at runtime, the trade-off between protocol overheadand an accuracy objective. This functionality is realized throughdynamic configuration of local filters that control the flow ofupdates towards the management station. The paper includes ananalysis of the problem of histogram aggregation over aggregationtrees, a formulation of the global optimization problem, anda distributed solution containing heuristic, tree-based algorithms.Using SUM as an example, we show how general aggregationfunctions over local variables can be efficiently computed withH-GAP. We evaluate our protocol through simulation using realtraces. The results demonstrate the controllability of H-GAP ina selection of scenarios and its efficiency in large-scale networks.
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10.
  • Deka, Pratyush Kr., et al. (författare)
  • Semi-supervised range-based anomaly detection for cloud systems
  • 2023
  • Ingår i: IEEE Transactions on Network and Service Management. - : IEEE. - 1932-4537. ; 20:2, s. 1290-1304
  • Tidskriftsartikel (refereegranskat)abstract
    • The inherent characteristics of cloud systems often lead to anomalies, which pose challenges for high availability, reliability, and high performance. Detecting anomalies in cloud key performance indicators (KPI) is a critical step towards building a secure and trustworthy system with early mitigation features. This work is motivated by (i) the efficacy of recent reconstruction-based anomaly detection (AD), (ii) the misrepresentation of the accuracy of time series anomaly detection because point-based Precision and Recall are used to evaluate the efficacy for range-based anomalies, and (iii) detects performance and security anomalies when distributions shift and overlaps. In this paper, we propose a novel semi-supervised dynamic density-based detection rule that uses the reconstruction error vectors in order to detect anomalies. We use long short-term memory networks based on encoder-decoder (LSTM-ED) architecture to reconstruct the normal KPI time series. We experiment with both testbed and a diverse set of real-world datasets. The experimental results show that the dynamic density approach exhibits better performance compared to other detection rules using both standard and range-based evaluation metrics. We also compare the performance of our approach with state-of-the-art methods, outperforms in detecting both performance and security anomalies.
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11.
  • Fetahi, Wuhib, et al. (författare)
  • Robust Monitoring of Network-wide Aggregates through Gossiping
  • 2009
  • Ingår i: IEEE Transactions on Network and Service Management. - : IEEE Communications Society. - 1932-4537. ; 6:2, s. 95-109
  • Tidskriftsartikel (refereegranskat)abstract
    • We investigate the use of gossip protocols for continuousmonitoring of network-wide aggregates under crash failures.Aggregates are computed from local management variablesusing functions such as SUM, MAX, or AVERAGE. For this typeof aggregation, crash failures offer a particular challenge dueto the problem of mass loss, namely, how to correctly accountfor contributions from nodes that have failed. In this paper wegive a partial solution. We present G-GAP, a gossip protocolfor continuous monitoring of aggregates, which is robust againstfailures that are discontiguous in the sense that neighboringnodes do not fail within a short period of each other. We giveformal proofs of correctness and convergence, and we evaluatethe protocol through simulation using real traces. The simulationresults suggest that the design goals for this protocol have beenmet. For instance, the tradeoff between estimation accuracyand protocol overhead can be controlled, and a high estimationaccuracy (below some 5% error in our measurements) is achievedby the protocol, even for large networks and frequent nodefailures. Further, we perform a comparative assessment of GGAPagainst a tree-based aggregation protocol using simulation.Surprisingly, we find that the tree-based aggregation protocolconsistently outperforms the gossip protocol for comparativeoverhead, both in terms of accuracy and robustness.
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12.
  • Fischer, Andreas, et al. (författare)
  • Generating Virtual Network Embedding Problems with Guaranteed Solutions
  • 2016
  • Ingår i: IEEE Transactions on Network and Service Management. - : IEEE. - 1932-4537. ; 13:3, s. 504-517
  • Tidskriftsartikel (refereegranskat)abstract
    • The efficiency of network virtualization depends on the appropriate assignment of resources. The underlying problem, called Virtual Network Embedding, has been much discussed in the literature, and many algorithms have been proposed, attempting to optimize the resource assignment in various respects. Evaluation of those algorithms requires a large number of randomly generated embedding scenarios. This paper presents a novel scenario generation approach and demonstrates how to produce scenarios with a guaranteed exact solution, thereby facilitating better evaluation of embedding algorithms.
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13.
  • Franke, Ulrik, et al. (författare)
  • Experimental Evidence on Decision-Making in Availability Service Level Agreements
  • 2016
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 13:1, s. 58-70
  • Tidskriftsartikel (refereegranskat)abstract
    • As more enterprises buy information technology services, studying their underpinning contracts becomes more important. With cloud computing and outsourcing, these service level agreements (SLAs) are now often the only link between the business and the supporting IT services. This paper presents an experimental economics investigation of decision-making with regard to availability SLAs, among enterprise IT professionals. The method and the ecologically valid subjects make the study unique to date among IT service SLA studies. The experiment consisted of pairwise choices under uncertainty, and subjects (N = 46) were incentivized by payments based on one of their choices, randomly selected. The research question investigated in this paper is: Do enterprise IT professionals maximize expected value when procuring availability SLAs, as would be optimal from the business point of view? The main result is that enterprise IT professionals fail to maximize expected value. Whereas some subjects do maximize expected value, others are risk-seeking, risk-averse, or exhibit non-monotonic preferences. The nonmonotonic behavior in particular is an interesting observation, which has no obvious explanation in the literature. For a subset of the subjects (N = 29), a few further hypotheses related to associations between general attitude to risk or professional experience on the one hand, and behavior in SLAs on the other hand, were investigated. No support for these associations was found. The results should be interpreted with caution, due to the limited number of subjects. However, given the prominence of SLAs in modern IT service management, the results are interesting and call for further research, as they indicate that current professional decision-making regarding SLAs can be improved. In particular, if general attitude to risk and professional experience do not impact decision-making with regard to SLAs, more extensive use of decision-support systems might be called for in order to facilitate proper risk management.
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14.
  • Franke, Ulrik (författare)
  • Optimal IT service availability : Shorter outages, or fewer?
  • 2012
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 9:1, s. 22-33
  • Tidskriftsartikel (refereegranskat)abstract
    • High enterprise IT service availability is a key success factor throughout many industries. While understanding of the economic importance of availability management is becoming more widespread, the implications for management of Service Level Agreements (SLAs) and thinking about availability risk management are just beginning to unfold. This paper offers a framework within which to think about availability management, highlighting the importance of variance of outage costs. The importance of variance is demonstrated using simulations on existing data sets of revenue data. An important implication is that when outage costs are proportional to outage duration, more but shorter outages should be preferred to fewer but longer, in order to minimize variance. Furthermore, two archetypal cases where the cost of an outage depends non-linearly on its duration are considered. An optimal outage length is derived, and some guidance is also given for its application when the variance of hourly downtime costs is considered. The paper is concluded with a discussion about the feasibility of the method, its practitioner relevance and its implications for SLA management.
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15.
  • Fu, Jing, 1978-, et al. (författare)
  • Loop-Free Updates of Forwarding Tables
  • 2008
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 5:1, s. 22-35
  • Tidskriftsartikel (refereegranskat)abstract
    • When the forwarding paths in an IP network change due to a link failure or a link weight modification, the forwarding tables in the routers may need to be updated. Each of these updates may cause transient loops if they are not performed in an appropriate order. In this paper, we propose an order to update the forwarding tables that avoids transient loops for non-urgent changes. The order is obtained by studying the changes in the forwarding tables, therefore it can be used in networks running any routing protocols, and for any type of forwarding path changes. After presenting the order, we prove that it is correct, and present an efficient algorithm to compute the order. Thereafter, we present several algorithms for performing forwarding table updates in accordance with the order. We also discuss how the update algorithms can be applied to both networks with centralized control and decentralized routing protocols. Finally, we study the update algorithms’ performance on several network topologies and with varying parameter settings and for several types of forwarding path changes.
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16.
  • Gao, Deyun, et al. (författare)
  • PMNDN : Proxy Based Mobility Support Approach in Mobile NDN Environment
  • 2017
  • Ingår i: IEEE Transactions on Network and Service Management. - : IEEE. - 1932-4537. ; 14:1, s. 191-203
  • Tidskriftsartikel (refereegranskat)abstract
    • In this paper, we study the source mobility problem that exists in the current named data networking (NDN) architecture and propose a proxy-based mobility support approach named PMNDN to overcome the problem. PMNDN proposes using a proxy to efficiently manage source mobility. Besides, functionalities of the NDN access routers are extended to track the mobility status of a source and signal Proxy about a handoff event. With this design, a mobile source does not need to participate in handoff signaling which reduces the consumption of limited wireless bandwidth. PMNDN also features an ID that is structurally similar to the content name so that routing scalability of NDN architecture is maintained and addressing efficiency of Interest packets is improved. We illustrate the performance advantages of our proposed solution by comparing the handoff performance of the mobility support approaches with that in NDN architecture and current Internet architecture via analytical and simulation investigation. We show that PMNDN offers lower handoff cost, shorter handoff latency, and less packet losses during the handoff process
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17.
  • Gonzalez Prieto, Alberto, 1977-, et al. (författare)
  • A-GAP : An Adaptive Protocol for Continuous Network Monitoring with Accuracy Objectives
  • 2007
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 4:1, s. 2-12
  • Tidskriftsartikel (refereegranskat)abstract
    • We present A-GAP, a novel protocol for continuous monitoring of network state variables, which aims at achieving a given monitoring accuracy with minimal overhead. Network state variables are computed from device counters using aggregation functions, such as SUM, AVERAGE and MAX. The accuracy objective is expressed as the average estimation error. A-GAP is decentralized and asynchronous to achieve robustness and scalability. It executes on an overlay that interconnects management processes on the devices. On this overlay, the protocol maintains a spanning tree and updates the network state variables through incremental aggregation. Based on a stochastic model, it dynamically configures local filters that control whether an update is sent towards the root of the tree. We evaluate A-GAP through simulation using real traces and two different types of topologies of up to 650 nodes. The results show that we can effectively control the trade-off between accuracy and protocol overhead, and that the overhead can be reduced by almost two orders of magnitude when allowing for small errors. The protocol quickly adapts to a node failure and exhibits short spikes in the estimation error. Lastly, it can provide an accurate estimate of the error distribution in real-time.
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18.
  • Hammar, Kim, et al. (författare)
  • Intrusion Prevention Through Optimal Stopping
  • 2022
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4537. ; 19:3, s. 2333-2348
  • Tidskriftsartikel (refereegranskat)abstract
    • We study automated intrusion prevention using reinforcement learning. Following a novel approach, we formulate the problem of intrusion prevention as an (optimal) multiple stopping problem. This formulation gives us insight into the structure of optimal policies, which we show to have threshold properties. For most practical cases, it is not feasible to obtain an optimal defender policy using dynamic programming. We therefore develop a reinforcement learning approach to approximate an optimal threshold policy. We introduce T- SPSA, an efficient reinforcement learning algorithm that learns threshold policies through stochastic approximation. We show that T- SPSA outperforms state-of-the-art algorithms for our use case. Our overall method for learning and validating policies includes two systems: a simulation system where defender policies are incrementally learned and an emulation system where statistics are produced that drive simulation runs and where learned policies are evaluated. We show that this approach can produce effective defender policies for a practical IT infrastructure.
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19.
  • Hammar, Kim, et al. (författare)
  • Learning Near-Optimal Intrusion Responses Against Dynamic Attackers
  • 2024
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4537. ; 21:1, s. 1158-1177
  • Tidskriftsartikel (refereegranskat)abstract
    • We study automated intrusion response and formulate the interaction between an attacker and a defender as an optimal stopping game where attack and defense strategies evolve through reinforcement learning and self-play. The game-theoretic modeling enables us to find defender strategies that are effective against a dynamic attacker, i.e., an attacker that adapts its strategy in response to the defender strategy. Further, the optimal stopping formulation allows us to prove that best response strategies have threshold properties. To obtain near-optimal defender strategies, we develop Threshold Fictitious Self-Play (T-FP), a fictitious self-play algorithm that learns Nash equilibria through stochastic approximation. We show that T-FP outperforms a state-of-the-art algorithm for our use case. The experimental part of this investigation includes two systems: a simulation system where defender strategies are incrementally learned and an emulation system where statistics are collected that drive simulation runs and where learned strategies are evaluated. We argue that this approach can produce effective defender strategies for a practical IT infrastructure.
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20.
  • Ibidunmoye, Olumuyiwa, et al. (författare)
  • Adaptive Anomaly Detection in Performance Metric Streams
  • 2018
  • Ingår i: IEEE Transactions on Network and Service Management. - : IEEE. - 1932-4537. ; 15:1, s. 217-231
  • Tidskriftsartikel (refereegranskat)abstract
    • Continuous detection of performance anomalies such as service degradations has become critical in cloud and Internet services due to impact on quality of service and end-user experience. However, the volume and fast changing behaviour of metric streams have rendered it a challenging task. Many diagnosis frameworks often rely on thresholding with stationarity or normality assumption, or on complex models requiring extensive offline training. Such techniques are known to be prone to spurious false-alarms in online settings as metric streams undergo rapid contextual changes from known baselines. Hence, we propose two unsupervised incremental techniques following a two-step strategy. First, we estimate an underlying temporal property of the stream via adaptive learning and, then we apply statistically robust control charts to recognize deviations. We evaluated our techniques by replaying over 40 time-series streams from the Yahoo! Webscope S5 datasets as well as 4 other traces of real web service QoS and ISP traffic measurements. Our methods achieve high detection accuracy and few false-alarms, and better performance in general compared to an open-source package for time-series anomaly detection.
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21.
  • Javier, Baliosian, et al. (författare)
  • Distributed Auto-configuration of Neighboring Cell Graphs in Radio Access Networks
  • 2010
  • Ingår i: IEEE Transactions on Network and Service Management. - : IEEE Communications Society. - 1932-4537. ; 7:3, s. 145-157
  • Tidskriftsartikel (refereegranskat)abstract
    • In order to execute a handover processes in a GSMor UMTS Radio Access Network, each cell has a list of neighborsto which such handovers may be made. Today, these lists arestatically configured during network planning, which does notallow for dynamic adaptation of the network to changes andunexpected events such as a cell failure. This paper advocatesan autonomic, decentralized approach to dynamically configureneighboring cell lists. The main contribution of this work isa novel protocol, called DOC, which detects and continuouslytracks the coverage overlaps among cells. The protocol executeson a spanning tree where the nodes are radio base stations andthe links represent communication channels. Over this tree, nodesperiodically exchange information about terminals that are intheir respective coverage area. Bloom filters are used for efficientrepresentations of terminal sets and efficient set operations. Theprotocol aggregates Bloom filters to reduce the communicationoverhead and also for routing messages along the tree. Usingsimulation, we study the system in steady state, when a basestation is added or a base station fails, and also during theinitialization phase where the system self-configures.
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22.
  • Kjaer, Martin Ansbjerg, et al. (författare)
  • Resource allocation and disturbance rejection in web servers using SLAs and virtualized servers
  • 2009
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 6:4
  • Tidskriftsartikel (refereegranskat)abstract
    • Abstract—Resource management in IT–enterprises gain more and more attention due to high operation costs. For instance, web sites are subject to very changing traffic–loads over the year, over the day, or even over the minute. Online adaption to the changing environment is one way to reduce losses in the operation. Control systems based on feedback provide methods for such adaption, but is in nature slow, since changes in the environment has to propagate through the system before being compensated. Therefore, feed–forward systems can be introduced that has shown to improve the transient performance. However, earlier proposed feed–forward systems have been based on offline estimation. In this article we show that off–line estimations can be problematic in online applications. Therefore, we propose a method where parameters are estimated online, and thus also adapts to the changing environment. We compare our solution to two other control strategies proposed in the literature, which are based on off-line estimation of certain parameters. We evaluate the controllers with both discrete-event simulations and experiments in our testbed. The investigations show the strength of our proposed control system.
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23.
  • Kristiansson, Johan, et al. (författare)
  • An application-layer approach to seamless mobile multimedia communication
  • 2006
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 3:1, s. 33-42
  • Tidskriftsartikel (refereegranskat)abstract
    • Providing seamless IP mobility support is one of the most challenging problems towards a world of mobile and ubiquitous multimedia communication. This paper proposes an application-layer framework based on the Session Initiation Protocol and the Resilient Mobile Socket to provide mobility support for distributed multimedia applications. As a part of the framework the paper describes a new handover strategy called Competition-based Soft-Handover Management that uses simulcast to improve quality of service and to seamlessly hand over multimedia traffic to the network interface that currently offers better network characteristics. In short, during a handover packets are simulcasted through all available network interfaces, and when the packets are received by the remote end-point, they are merged back into one stream. As each network connection competes with other connections in contributing to the merged stream at the remote end-point, the handover process can be viewed as a competition where the connection that contributes most is selected after the handover. As a proof of concept, the framework has been integrated into Marratech, which is a commercially available audio/video group communication application. By using network emulators, the paper demonstrates how the framework can be used to improve QoS, compare end-to-end performance, and perform lossless handovers while reducing redundant packets.
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24.
  • Lin, Bing, et al. (författare)
  • A Pretreatment Workflow Scheduling Approach for Big Data Applications in Multi-cloud Environments
  • 2016
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 13:3, s. 581-594
  • Tidskriftsartikel (refereegranskat)abstract
    • The rapid development of the latest distributed computing paradigm, i.e., cloud computing, generates a highly fragmented cloud market composed of numerous cloud providers and offers tremendous parallel computing ability to handle Big Data problems. One of the biggest challenges in Multi-clouds is efficient workflow scheduling. Although the workflow scheduling problem has been studied extensively, there are still very few primal works tailored for Multi-cloud environments. Moreover, the existing research works either fail to satisfy the Quality of Service (QoS) requirements, or do not consider some fundamental features of cloud computing such as heterogeneity and elasticity of computing resources. In this paper, a scheduling algorithm which is called Multi-Clouds Partial Critical Paths with Pretreatment (MCPCPP) for Big Data workflows in Multi-clouds is presented. This algorithm incorporates the concept of Partial Critical Paths, and aims to minimize the execution cost of workflow while satisfying the defined deadline constraint. Our approach takes into considerations the essential characteristics of Multi-clouds such as the charge per time interval, various instance types from different cloud providers as well as homogeneous intra-bandwidth vs. heterogeneous inter-bandwidth. Various types of workflows are used for evaluation purpose and our experimental results show that the MCPCPP is promising.
  •  
25.
  • Meer, Irshad Ahmad, et al. (författare)
  • Mobility Management for Cellular-Connected UAVs: Model Based Versus Learning Based Approaches for Service Availability
  • 2024
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4537. ; , s. 1-1
  • Tidskriftsartikel (refereegranskat)abstract
    • Mobility management for terrestrial users is mostlyconcerned with avoiding radio link failure for the edge users wherethe cell boundaries are defined. The problem becomes interestingfor an aerial user experiencing fragmented coverage in the sky andline-of-sight conditions with multiple ground base stations (BSs).For aerial users, mobility management is not only concerned withavoiding link failures but also avoiding unnecessary handoverswhile maintaining extended service availability, especially inup-link communication. The line of sight conditions from anUnmanned Aerial Vehicle (UAV) to multiple neighboring BSs makeit more prone to frequent handovers, leading to control packetoverheads and delays in the communication service. Depending onthe use cases, UAVs require a certain level of service availability,which makes their mobility management a critical task. Thecurrent mobility robustness optimization (MRO) procedure thatadaptively manages handover parameters to avoid unnecessaryhandovers is optimized only for terrestrial users. It needs tobe updated to capture the unique mobility challenges of aerialusers. In this work, we propose two approaches to accomplishthis: 1) A model based service availability-aware MRO wherehandover control parameters, such as handover margin and timeto trigger are tuned to maintain high service availability witha minimum number of handovers, and, 2) A deep Q-networkbased model free approach for decreasing unnecessary handoverswhile maintaining high service availability. Simulation resultsdemonstrate that both the proposed algorithms converge promptlyand increase the service availability by more than 40% while thenumber of handovers is reduced by more than 50% as comparedto traditional approaches.
  •  
26.
  • Meng, Weizhi, et al. (författare)
  • Towards Bayesian-based Trust Management for Insider Attacks in Healthcare Software-Defined Networks
  • 2018
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4537. ; 15:2, s. 761-773
  • Tidskriftsartikel (refereegranskat)abstract
    • The medical industry is increasingly digitalized and Internet-connected (e.g., Internet of Medical Things), and when deployed in an Internet of Medical Things environment, software-defined networks (SDN) allow the decoupling of network control from the data plane. There is no debate among security experts that the security of Internet-enabled medical devices is crucial, and an ongoing threat vector is insider attacks. In this paper, we focus on the identification of insider attacks in healthcare SDNs. Specifically, we survey stakeholders from 12 healthcare organizations (i.e., two hospitals and two clinics in Hong Kong, two hospitals and two clinics in Singapore, and two hospitals and two clinics in China). Based on the survey findings, we develop a trust-based approach based on Bayesian inference to figure out malicious devices in a healthcare environment. Experimental results in either a simulated and a real-world network environment demonstrate the feasibility and effectiveness of our proposed approach regarding the detection of malicious healthcare devices, i.e., our approach could decrease the trust values of malicious devices faster than similar approaches.
  •  
27.
  • Mishra, Kaushik, et al. (författare)
  • Collaborative cloud resource management and task consolidation using JAYA variants
  • 2024
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4537.
  • Tidskriftsartikel (refereegranskat)abstract
    • In Cloud-based computing, job scheduling and load balancing are vital to ensure on-demand dynamic resource provisioning. However, reducing the scheduling parameters may affect datacenter performance due to the fluctuating on-demand requests. To deal with the aforementioned challenges, this research proposes a job scheduling algorithm, which is an improved version of a swarm intelligence algorithm. Two approaches, namely linear weight JAYA (LWJAYA) and chaotic JAYA (CJAYA), are implemented to improve the convergence speed for optimal results. Besides, a load-balancing technique is incorporated in line with job scheduling. Dynamically independent and non-pre-emptive jobs were considered for the simulations, which were simulated on two disparate test cases with homogeneous and heterogeneous VMs. The efficiency of the proposed technique was validated against a synthetic and real-world dataset from NASA, and evaluated against several top-of-the-line intelligent optimization techniques, based on the Holms test and Friedman test. Findings of the experiment show that the suggested approach performs better than the alternative approaches.
  •  
28.
  • Munir, M. S., et al. (författare)
  • Risk-Aware Energy Scheduling for Edge Computing with Microgrid : A Multi-Agent Deep Reinforcement Learning Approach
  • 2021
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 18:3, s. 3476-3497
  • Tidskriftsartikel (refereegranskat)abstract
    • In recent years, multi-access edge computing (MEC) is a key enabler for handling the massive expansion of Internet of Things (IoT) applications and services. However, energy consumption of a MEC network depends on volatile tasks that induces risk for energy demand estimations. As an energy supplier, a microgrid can facilitate seamless energy supply. However, the risk associated with energy supply is also increased due to unpredictable energy generation from renewable and non-renewable sources. Especially, the risk of energy shortfall is involved with uncertainties in both energy consumption and generation. In this paper, we study a risk-aware energy scheduling problem for a microgrid-powered MEC network. First, we formulate an optimization problem considering the conditional value-at-risk (CVaR) measurement for both energy consumption and generation, where the objective is to minimize the expected residual of scheduled energy for the MEC networks and we show this problem is an NP-hard problem. Second, we analyze our formulated problem using a multi-agent stochastic game that ensures the joint policy Nash equilibrium, and show the convergence of the proposed model. Third, we derive the solution by applying a multi-agent deep reinforcement learning (MADRL)-based asynchronous advantage actor-critic (A3C) algorithm with shared neural networks. This method mitigates the curse of dimensionality of the state space and chooses the best policy among the agents for the proposed problem. Finally, the experimental results establish a significant performance gain by considering CVaR for high accuracy energy scheduling of the proposed model than both the single and random agent models. 
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29.
  • Natalino Da Silva, Carlos, 1987, et al. (författare)
  • Root Cause Analysis for Autonomous Optical Network Security Management
  • 2022
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 19:3, s. 2702-2713
  • Tidskriftsartikel (refereegranskat)abstract
    • The ongoing evolution of optical networks towards autonomous systems supporting high-performance services beyond 5G requires advanced functionalities for automated security management. To cope with evolving threat landscape, security diagnostic approaches should be able to detect and identify the nature not only of existing attack techniques, but also those hitherto unknown or insufficiently represented. Machine Learning (ML)-based algorithms perform well when identifying known attack types, but cannot guarantee precise identification of unknown attacks. This makes Root Cause Analysis (RCA) crucial for enabling timely attack response when human intervention is unavoidable. We address these challenges by establishing an ML-based framework for security assessment and analyzing RCA alternatives for physical-layer attacks. We first scrutinize different Network Management System (NMS) architectures and the corresponding security assessment capabilities. We then investigate the applicability of supervised and unsupervised learning (SL and UL) approaches for RCA and propose a novel UL-based RCA algorithm called Distance-Based Root Cause Analysis (DB-RCA). The framework’s applicability and performance for autonomous optical network security management is validated on an experimental physical-layer security dataset, assessing the benefits and drawbacks of the SL-and UL-based RCA. Besides confirming that SL-based approaches can provide precise RCA output for known attack types upon training, we show that the proposed UL-based RCA approach offers meaningful insight into the anomalies caused by novel attack types, thus supporting the human security officers in advancing the physical-layer security diagnostics.
  •  
30.
  • Nougnanke, Benoit, et al. (författare)
  • ML-Based Performance Modeling in SDN-Enabled Data Center Networks
  • 2023
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4537. ; 20:1, s. 815-829
  • Tidskriftsartikel (refereegranskat)abstract
    • Traffic optimization and smart buffering are fundamental to achieve both great application performance and resource efficiency in data centers with heterogeneous workloads, including incast and elephant traffics. However, general performance models providing insights on how various factors affect traffic performance metrics needed by these management functions are missing. For the special case of incast, the existing models are analytical ones, either tightly coupled with a particular protocol version or specific to certain empirical data. Motivated by this observation, this paper proposes an SDN-enabled machine-learning-based performance modeling approach in data center networks that leverages random forest predictions. Evaluations based on datasets constructed through intensive NS-3 simulations show that we can achieve accurate predictions of incast and elephant performance metrics based on various features. With this performance modeling capability, smart buffering schemes or traffic optimization algorithms could anticipate and efficiently optimize system parameters adjustment to achieve optimal performance continuously in data centers.
  •  
31.
  • Safavi, Mohammadhassan, et al. (författare)
  • Online Learning and Placement Algorithms for Efficient Delivery of User Generated Contents in Telco-CDNs
  • 2019
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 17:1, s. 637-651
  • Tidskriftsartikel (refereegranskat)abstract
    • User generated content (UGC) makes up a significant portion of Internet traffic. As opposed to other content, UGC has so far been left outside over-the-top providing network operators content distribution networks (telco-CDN) due to the difficulty in determining optimised placement of such content. The side effect of this is that UGC content is not placed close to end users and therefore occupy unnecessary network resources. The difficulty in determining optimal placement of UGC stems from the different geographical and dynamic behaviour of the content generators, and a further complication is that with UGC, it is necessary to place content in real-time which this has an impact on performance optimality. Even though CDNs have been widely studied in the literature, little attention has been given to the challenging case of UGC placement. In this paper, we propose an on-line placement algorithm and compare its performance with the off-line counterpart based on integer programming, both under the assumption that the popularity of content is known to the algorithms. In order to determine the popularity, we present an on-line learning model to predict spatial patterns in content requests. Furthermore, we couple the model with an algorithm for learning the early popularity of content, i.e. shortly after the content becomes known. We show that together, these approaches enable service providers to effectively place UGC and minimise the cost of serving UGC in their networks.
  •  
32.
  • Salehi, Fateme, et al. (författare)
  • Reliability and Delay Analysis of 3-Dimensional Networks With Multi-Connectivity : Satellite, HAPs, and Cellular Communications
  • 2024
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4537. ; 21:1, s. 437-450
  • Tidskriftsartikel (refereegranskat)abstract
    • Aerial vehicles (AVs) such as electric vertical take-off and landing (eVTOL) aircraft make aerial passenger transportation a reality in urban environments. However, their communication connectivity is still under research to realize their safe and full-scale operation. This paper envisages a multi-connectivity (MC) enabled aerial network to provide ubiquitous and reliable service to AVs. Vertical heterogeneous networks with direct air-to-ground (DA2G) and air-to-air (A2A) communication, high altitude platforms (HAPs), and low Earth orbit (LEO) satellites are considered. We evaluate the end-to-end (E2E) multi-hop reliability and network availability of the downlink of AVs for remote piloting scenarios, and control/telemetry traffic. Command and control (C2) connectivity service requires ultra-reliable and low-latency communication (URLLC), therefore we analyse E2E reliability and latency under the finite blocklength (FBL) regime. We explore how different MC options satisfy the demanding E2E connectivity requirements taking into account antenna radiation patterns and unreliable backhaul links. Since providing seamless connectivity to AVs is very challenging due to the line-of-sight (LoS) interference and reduced gains of downtilt ground base station (BS) antennas, we use coordinated multi-point (CoMP) among ground BSs to alleviate the inter-cell interference. Furthermore, we solve an optimization problem to select the best MC path under the quality of service (QoS) constraints. We maximize spectral efficiency (SE) to specify the optimum MC path with the minimum number of required links. Based on the simulation results, we find out that even with very efficient interference mitigation, MC is the key enabler for safe remote piloting operations.
  •  
33.
  • Samani, Forough Shahab, et al. (författare)
  • Conditional Density Estimation of Service Metrics for Networked Services
  • 2021
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4537. ; 18:2, s. 2350-2364
  • Tidskriftsartikel (refereegranskat)abstract
    • We predict the conditional distributions of service metrics, such as response time or frame rate, from infrastructure measurements in a networked environment. From such distributions, key statistics of the service metrics, including mean, variance, or quantiles can be computed, which are essential for predicting SLA conformance and enabling service assurance. We present and assess two methods for prediction: (1) mixture models with Gaussian or Lognormal kernels, whose parameters are estimated using mixture density networks, a class of neural networks, and (2) histogram models, which require the target space to be discretized. We apply these methods to a VoD service and a KV store service running on our lab testbed. A comparative evaluation shows the relative effectiveness of the methods when applied to operational data. We find that both methods allow for accurate prediction. While mixture models provide a general and elegant solution, they incur a very high overhead related to hyper-parameter search and neural network training. Histogram models, on the other hand, allow for efficient training, but require adjustment to the specific use case.
  •  
34.
  • Santos, Alex S., et al. (författare)
  • Multi-Criteria Decision Approach for Lightpath Restoration After Resource Crunch
  • 2024
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; In Press
  • Tidskriftsartikel (refereegranskat)abstract
    • Network operators must deal with Classes of Service (CoS), which have several quality requirements, such as latency, bandwidth/capacity, priority, etc. Besides, it is observed an increase in the volume of traffic that is offered to the transport network. This traffic can be affected by network natural disasters or human-made attacks. In this case, network operators must decide which services to restore, considering their different requirements. In this work, we present a Lightpath Selection Algorithm (LSA) that aims to select lightpaths to be restored after a resource crunch. This algorithm has a multicriteria decision approach considering CoS, Bandwidth, number of Hops, and Holding time. Moreover, service degradation is also considered for those lightpaths that can not be restored with full bandwidth. Results show that our proposed algorithm can improve network restorability and availability without penalizing low-level CoSs.
  •  
35.
  • Sengupta, Jayasree, et al. (författare)
  • On Cross-Layer Interactions of QUIC, Encrypted DNS and HTTP/3 : Design, Evaluation and Dataset
  • 2024
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers Inc.. - 1932-4537. ; , s. 1-1
  • Tidskriftsartikel (refereegranskat)abstract
    • Every Web session involves a DNS resolution. While, in the last decade, we witnessed a promising trend towards an encrypted Web in general, DNS encryption has only recently gained traction with the standardisation of DNS over TLS (DoT) and DNS over HTTPS (DoH). Meanwhile, the rapid rise of QUIC deployment has now opened up an exciting opportunity to utilise the same protocol to not only encrypt Web communications, but also DNS. In this paper, we evaluate this benefit of using QUIC to coalesce name resolution via DNS over QUIC (DoQ), and Web content delivery via HTTP/3 (H3) with 0-RTT. We compare this scenario using several possible combinations where H3 is used in conjunction with DoH and DoQ, as well as the unencrypted DNS over UDP (DoUDP). We observe, that when using H3 1-RTT, page load times with DoH can get inflated by >30% over fixed-line and by >50% over mobile when compared to unencrypted DNS with DoUDP. However, this cost of encryption can be drastically reduced when encrypted connections are coalesced (DoQ + H3 0-RTT), thereby reducing the page load times by 1/3 over fixed-line and 1/2 over mobile, overall making connection coalescing with QUIC the best option for encrypted communication on the Internet. 
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36.
  • Srivastava, Shekhar, et al. (författare)
  • Determining link weight system under various objectives for OSPF networks using a Lagrangian relaxation-based approach
  • 2005
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 2:1, s. 9-18
  • Tidskriftsartikel (refereegranskat)abstract
    • An important traffic engineering problem for OSPF networks is the determination of optimal link weights. Certainly, this depends on the traffic engineering objective. Regardless, often a variety of performance measures may be of interest to a network provider due to their impact on the network. In this paper, we consider different objectives and discuss how they impact the determination of the link weights and different performance measures. In particular, we propose a composite objective function; furthermore, we present a Lagrangian relaxation-based dual approach to determine the link weight system. We then consider different performance measures and discuss the effectiveness of different objectives through computational studies of a variety of network topologies. We find that our proposed composite objective function with Lagrangian relaxation-based dual approach is very effective in meeting different performance measures and is computationally very fast.
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37.
  •  
38.
  • Subramanya, T., et al. (författare)
  • Centralized and Federated Learning for Predictive VNF Autoscaling in Multi-domain 5G Networks and Beyond
  • 2021
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers Inc.. - 1932-4537. ; 18:1, s. 63-78
  • Tidskriftsartikel (refereegranskat)abstract
    • Network Function Virtualization (NFV) and Multi-access Edge Computing (MEC) are two technologies expected to play a vital role in 5G and beyond networks. However, adequate mechanisms are required to meet the dynamically changing network service demands to utilize the network resources optimally and also to satisfy the demanding QoS requirements. Particularly in multi-domain scenarios, the additional challenge of isolation and data privacy among domains needs to be tackled. To this end, centralized and distributed Artificial Intelligence (AI)-driven resource orchestration techniques (e.g., virtual network function (VNF) autoscaling) are foreseen as the main enabler. In this work, we propose deep learning models, both centralized and federated approaches, that can perform horizontal and vertical autoscaling in multi-domain networks. The problem of autoscaling is modelled as a time series forecasting problem that predicts the future number of VNF instances based on the expected traffic demand. We evaluate the performance of various deep learning models trained over a commercial network operator dataset and investigate the pros and cons of federated learning over centralized learning approaches. Furthermore, we introduce the AI-driven Kubernetes orchestration prototype that we implemented by leveraging our MEC platform and assess the performance of the proposed deep learning models in a practical setup. 
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39.
  • Sundqvist, Tobias, et al. (författare)
  • Robust procedural learning for anomaly detection and observability in 5G RAN
  • 2024
  • Ingår i: IEEE Transactions on Network and Service Management. - : IEEE. - 1932-4537. ; 21:2, s. 1432-1445
  • Tidskriftsartikel (refereegranskat)abstract
    • Most existing large distributed systems have poor observability and cannot use the full potential of machine learning-based behavior analysis. The system logs, which contain the primary source of information, are unstructured and lack the context needed to track procedures and learn the system’s behavior. This work presents a new trace guideline that enables a component-and procedure-based split of the system logs for the future 5G Radio Access Network (RAN). As the system can be broken into smaller pieces, models can more accurately learn the system’s behavior and use the context to improve anomaly detection and observability. The evaluation result is astonishing; where previously state-of-the-art methods struggle to learn the behavior, a fast, dictionary-based algorithm can detect all anomalies and keep false positives close to zero. Troubleshooters can also more quickly identify anomalies and gain useful insights into the component interaction in RAN.
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40.
  • Tkachuk, Roman-Valentyn, et al. (författare)
  • A Survey on Blockchain-based Telecommunication Services Marketplaces
  • 2022
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers Inc.. - 1932-4537. ; 19:1, s. 228-255
  • Tidskriftsartikel (refereegranskat)abstract
    • Digital marketplaces were created recently to accelerate the delivery of applications and services to customers. Their appealing feature is to activate and dynamize the demand, supply, and development of digital goods, applications, or services. By being an intermediary between producer and consumer, the primary business model for a marketplace is to charge the producer with a commission on the amount paid by the consumer. However, most of the time, the commission is dictated by the marketplace facilitator itself and creates an imbalance in value distribution, where producer and consumer sides suffer monetarily. In order to eliminate the need for a centralized entity between the producer and consumer, a blockchain-based decentralized digital marketplace concept was introduced. It provides marketplace actors with the tools to perform business transactions in a trusted manner and without the need for an intermediary. In this work, we provide a survey on Telecommunication Services Marketplaces (TSMs) which employ blockchain technology as the main trust enabling entity in order to avoid any intermediaries. We provide an overview of scientific and industrial proposals on the blockchain-based online digital marketplaces at large, and TSMs in particular. We consider in this study the notion of telecommunication services as any service enabling the capability for information transfer and, increasingly, information processing provided to a group of users by a telecommunications system. We discuss the main standardization activities around the concepts of TSMs and provide particular use-cases for the TSM business transactions such as SLA settlement. Also, we provide insights into the main foundational services provided by the TSM, as well as a survey of the scientific and industrial proposals for such services. Finally, a prospect for future developments is given. Author
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41.
  • Vajd, Faezeh Samimi, et al. (författare)
  • Dynamic Joint Functional Split and Resource Allocation Optimization in Elastic Optical Fronthaul
  • 2022
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 19:4, s. 4505-4515
  • Tidskriftsartikel (refereegranskat)abstract
    • Dynamic reconfigurability in optical and mobile networks can facilitate heterogeneous service provisioning while utilizing minimal resources. This allows cost-efficient service delivery resulting in high revenues for network operators. Deployment of elastic mobile and optical networks is a key driver for enabling reconfigurability in modern networks. Elastic optical networks can be exploited as the fronthaul portion of new generation of mobile networks. Such elastic optical fronthaul networks facilitate joint reconfiguration of flexible radio and optical elements and provide considerable performance improvements. In this paper, we focus on the joint dynamic selection of functional splits and configuration of optical transponders and illustrate that designing a converged network with optical and radio elements improves network power efficiency. A time-averaged stochastic optimization problem is formulated and its solution is derived using a modified version of the Lyapunov drift technique. Simulation results demonstrate that the proposed scheme can reduce the average power consumption by up to 70% compared to a cloud radio access network with a traditional optical fronthaul. Further, the results show that the modified Lyapunov technique can afford stringent fronthaul delays below 250 μs. We also discuss how future technology upgrades such as increasing the number of radio antenna ports and decreasing the granularity of fiber spectrum grid may influence the results.
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42.
  • Vestin, Jonathan, 1989-, et al. (författare)
  • Towards in-network event detection and filtering for publish/subscribe communication using programmable data planes
  • 2021
  • Ingår i: IEEE Transactions on Network and Service Management. - : IEEE. - 1932-4537. ; 18:1, s. 415-428
  • Tidskriftsartikel (refereegranskat)abstract
    • Industrial Internet of Things (I-IoT) applications require a large number of sensor data to be processed under tight delay and jitter constraints. In such applications, flexible event detection and fast reaction to critical events is an important building block. Traditional approaches use either proprietary networks and dedicated hardware or transmit sensor data towards processing elements in the Cloud or at the Network Edge, using distributed stream processing frameworks. For scalability, a large number of servers are needed and processing on commodity CPUs typically involves high and unpredictable latency. In this paper, we explore how programmable data planes can be used to detect events flexibly and trigger customized and programmable actions directly from the switch program or the programmable network interface card (SmartNIC). We present FastReact-PS, an event-based publish/subscribe I-IoT processing framework in P4 language, which can be flexibly customized from the control plane. Together with stateful processing, FastReact-PS supports windowed time series analysis as well as complex event detection and processing based on boolean logic directly in the data plane of newly emerging programmable networking devices. The logic can be adjusted dynamically from the control plane without the need for recompilation. We implement FastReact-PS in P4 and evaluate it on both a SmartNIC and a DPDK-based software switch running in user space. Our evaluation shows that the latency is reduced by one order of magnitude compared to end-host based approaches at significantly lower jitter while being scalable to processing up to 11 million events per second.
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43.
  • Vu, Xuan-Son, 1988-, et al. (författare)
  • MetaVSID : a robust meta-reinforced learning approach for VSI-DDoS detection on the edge
  • 2023
  • Ingår i: IEEE Transactions on Network and Service Management. - : IEEE. - 1932-4537. ; 20:2, s. 1625-1643
  • Tidskriftsartikel (refereegranskat)abstract
    • The explosive growth of end devices that generate massive amounts of data requires close-proximity computing resources for processing at the network’s edge. Having geographic distributions and limited resources of edge nodes or servers opens several doors for attackers to exploit them primarily to the detriment of deployed services; one of the recent attacks is Very Short Intermittent Distributed Denial of Services (VSI-DDoS). Deep learning-based models have been developed to detect and mitigate such attacks but cause the degrading quality of models due to covariate shifts when deployed in real-world environments. Therefore, we propose a new approach, called MetaVSID, to detect VSI-DDoS attacks in edge clouds using meta-reinforcement learning followed by ensemble learning to increase the robustness of the model in detecting VSI-DDoS attacks early. The proposed model can capture dynamic patterns of VSI-DDoS attacks, from which it identifies manipulated services and increase service availability when covariate shifts at deployment time. We carry out extensive experiments to validate the MetaVSID using both testbed and benchmark datasets. Via the meta-reinforced downsampling process, the proposed method improves sample efficiency, leading to cost-effective policies. Moreover, the optimized policies are generalized to adapt to dynamic changes in the training distribution. Our experimental results demonstrate that MetaVSID stably achieves better performance in multiple evaluation settings with the difference from baseline models from 1.5% to 7.5% in terms of AUC for both VSI-DDoS and DDoS detection, especially under covariate shift settings.
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44.
  • Wang, Xiaoxuan, et al. (författare)
  • Online Feature Selection for Efficient Learning in Networked Systems
  • 2022
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4537. ; 19:3, s. 2885-2898
  • Tidskriftsartikel (refereegranskat)abstract
    • Current AI/ML methods for data-driven engineering use models that are mostly trained offline. Such models can be expensive to build in terms of communication and computing costs, and they rely on data that is collected over extended periods of time. Further, they become out-of-date when changes in the system occur. To address these challenges, we investigate online learning techniques that automatically reduce the number of available data sources for model training. We present an online algorithm called Online Stable Feature Set Algorithm (OSFS), which selects a small feature set from a large number of available data sources after receiving a small number of measurements. The algorithm is initialized with a feature ranking algorithm, a feature set stability metric, and a search policy. We perform an extensive experimental evaluation of this algorithm using traces from an in-house testbed and from two external datasets. We find that OSFS achieves a massive reduction in the size of the feature set by 1-3 orders of magnitude on all investigated datasets. Most importantly, we find that the accuracy of a predictor trained on a OSFS-produced feature set is somewhat better than when the predictor is trained on a feature set obtained through offline feature selection. OSFS is thus shown to be effective as an online feature selection algorithm and robust regarding the sample interval used for feature selection. We also find that, when concept drift in the data underlying the model occurs, its effect can be mitigated by recomputing the feature set and retraining the prediction model.
  •  
45.
  • Wang, Yufeng, et al. (författare)
  • VPEF : A simple and effective incentive mechanism in community-based autonomous networks
  • 2015
  • Ingår i: IEEE Transactions on Network and Service Management. - 1932-4537. ; 12:1, s. 75-86
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper focuses on incentivizing cooperative behavior in community-based autonomous networking environments (like mobile social networks, etc.), in which through dynamically forming virtual and/or physical communities, users voluntarily participate in and contribute resources (or provide services) to the community while consuming. Specifically, we proposed a simple but effective EGT (Evolutionary Game Theory)-based mechanism, VPEF (Voluntary Principle and round-based Entry Fee), to drive the networking environment into cooperative. VPEF builds incentive mechanism as two simple system rules: The first is VP meaning that all behaviors are voluntarily conducted by users: Users voluntarily participate (after paying round-based entry fee), voluntarily contribute resource, and voluntarily punish other defectors (incurring extra cost to those so-called punishers); The second is EF meaning that an arbitrarily small round-based entry fee is set for each user who wants to participate in the community. We presented a generic analytical framework of evolutionary dynamics to model VPEF scheme, and theoretically proved that VPEF scheme's efficiency loss defined as the ratio of system time, in which no users will provide resource, is 4/(8 + M). M is the number of users in community-based collaborative system. Finally, the simulated results using content availability as an example verified our theoretical analysis
  •  
46.
  • Wuhib, Fetahi, et al. (författare)
  • A Gossip Protocol for Dynamic ResourceManagement in Large Cloud Environments
  • 2012
  • Ingår i: IEEE Transactions on Network and Service Management. - : IEEE Communications Society. - 1932-4537. ; 9:2, s. 213-225
  • Tidskriftsartikel (refereegranskat)abstract
    • We address the problem of dynamic resource management for a large-scale cloud environment. Our contribution includes outlining a distributed middleware architecture and presenting one of its key elements: a gossip protocol that (1) ensures fair resource allocation among sites/applications, (2) dynamically adapts the allocation to load changes and (3) scales both in the number of physical machines and sites/applications. We formalize the resource allocation problem as that of dynamically maximizing the cloud utility under CPU and memory constraints. We first present a protocol that computes an optimalsolution without considering memory constraints and prove correctness and convergence properties. Then, we extend that protocol to provide an efficient heuristic solution for the complete problem, which includes minimizing the cost for adapting an allocation. The protocol continuously executes on dynamic, local input and does not require global synchronization, as other proposed gossip protocols do. We evaluate the heuristic protocol through simulation and find its performance to be well-aligned with our design goals.
  •  
47.
  • Wuhib, Fetahi, et al. (författare)
  • A Gossiping Protocol for Detecting Global Threshold Crossings
  • 2010
  • Ingår i: IEEE Transactions on Network and Service Management. - : IEEE. - 1932-4537. ; 7:1, s. 42-57
  • Tidskriftsartikel (refereegranskat)abstract
    • We investigate the use of gossip protocols for the detection of network-wide threshold crossings. Our design goals are low protocol overhead, small detection delay, low probability of false positives and negatives, scalability, robustness to node failures and controllability of the trade-off between overhead and detection delay. Based on push-synopses, a gossip protocol introduced by Kempe et al., we present a protocol that indicates whether a global aggregate of static local values is above or below a given threshold. For this protocol, we prove correctness and show that it converges to a state with no overhead when the aggregate is sufficiently far from the threshold. Then, we introduce an extension we call TG-GAP, a protocol that (1) executes in a dynamic network environment where local values change and (2) implements hysteresis behavior with upper and lower thresholds. Key elements of its design are the construction of snapshots of the global aggregate for threshold detection and a mechanism for synchronizing local states, both of which are realized through the underlying gossip protocol. Simulation studies suggest that TG-GAP is efficient in that the protocol overhead is minimal when the aggregate is sufficiently far from the threshold, that its overhead and the detection delay are largely independent on the system size, and that the tradeoff between overhead and detection quality can be effectively controlled. Lastly, we perform a comparative evaluation of TG-GAP against a tree-based protocol. We conclude that, for detecting global threshold crossings in the type of scenarios investigated, the tree-based protocol incurs a significantly lower overhead and a smaller detection delay than a gossip protocol such as TG-GAP.
  •  
48.
  • Yaghoubi, Forough, 1988-, et al. (författare)
  • Consistency-Aware Weather Disruption-Tolerant Routing in SDN-Based Wireless Mesh Networks
  • 2018
  • Ingår i: IEEE Transactions on Network and Service Management. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1932-4537. ; 15:2, s. 582-595
  • Tidskriftsartikel (refereegranskat)abstract
    • Wireless network solutions, a dominant enabling technology for the backhaul segment, are susceptible to weather disturbances that can substantially degrade network throughput and/or delay, compromising the stringent 5G requirements. These effects can be alleviated by centralized rerouting realized by software defined networking architecture. However, careless frequent reconfigurations can lead to inconsistencies in the network states due to asynchrony between different switches, which can create congestion and limit the rerouting gain. The aim of this paper is to minimize the total data loss during rain disturbance by proposing an algorithm that decides on the timing, the sequence, and the paths for rerouting of network flows considering the imposed congestion during reconfiguration. At each time sample, the central controller decides whether to adopt the optimal routes at a switching cost, defined as the imposed congestion, or to keep using existing, sub-optimal routes at a throughput loss. To find optimal solutions with minimal data loss in a static scenario, we formulate a dynamic programming problem that utilizes perfect knowledge of rain attenuation for the whole rain period. For dynamic scenarios with unknown future rain attenuation, we propose an online consistency-aware rerouting algorithm, called consistency-aware rerouting with prediction (CARP), which uses the temporal correlation of rain fading to estimate future rain attenuation. Simulation results on synthetic and real networks validate the efficiency of our CARP algorithm, substantially reducing data loss and increasing network throughput with a fewer number of rerouting actions compared to a greedy and a regular rerouting benchmarking approaches.
  •  
49.
  • Yaghoubi, Forough, 1988-, et al. (författare)
  • Consistency-aware Weather Disruption-tolerant Routing in SDNbased Wireless Mesh Networks
  • 2017
  • Ingår i: IEEE Transactions on Network and Service Management. - : IEEE Communications Society. - 1932-4537.
  • Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
    • Although, wireless solutions continue to be a dominant enabling technology in the future backhaul  segment, they are susceptible to weather disturbances that may substantially degrade network throughput, or delay, compromising the 5G requirements.  These  effects  can  be  alleviated  by centralized rerouting realized by software defined networking (SDN) architecture. However, careless frequent reconfigurations may lead to inconsistencies in network states due to asynchrony between different switches, which may create  congestion and limit the gain of frequent rerouting.  In  this  paper, we focus on the rerouting process during rain disturbance considering the minimum total congestion imposed  during  the  update  of  routing  tables as a switching cost. At each time sample, the central controller has the possibility to adopt the optimal routes at a switching cost or to keep using previous routes at the expense of a throughput loss due to route sub- optimality. To find optimal solutions with minimal data loss in a static scenario, we formulate a dynamic programming problem that utilizes perfect knowledge of the rain attenuation for the whole rain period (off-line policy with full knowledge). For dynamic scenarios where the future rain attenuation data cannot be known, we propose an online consistency-aware rerouting algorithm, called optimal control action with prediction (OCAP), which uses the temporal correlation of rain fading to estimate the future rain attenuation. Simulation results on synthetic and real networks validate the efficiency of our OCAP algorithm, substantially reducing congestion and increasing network throughput with a fewer number of rerouting actions compared to benchmarks approaches.
  •  
50.
  • Zhao, Peiyue, et al. (författare)
  • A Benders Decomposition Approach for Resilient Placement of Virtual Process Control Functions in Mobile Edge Clouds
  • 2018
  • Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-4537. ; 15:4, s. 1460-1472
  • Tidskriftsartikel (refereegranskat)abstract
    • Replacing hardware controllers with software-based virtual process control functions (VPFs) is a promising approach for improving the operational efficiency and flexibility of industrial control systems. VPFs can be executed in edge clouds in 5G mobile networks or in the wireless backhaul, which can further improve efficiency. Nonetheless, for the acceptance of virtualization in industrial control systems, a fundamental challenge is to ensure that the placement of VPFs be resilient to component failures and cyber-attacks, besides being efficient. In this paper we address this challenge by considering that VPF placement costs are incurred by reserving mobile edge computing (MEC) resources, executing VPF instances, and by data communication. We formulate the VPF placement problem as an integer programming problem, considering resilience as a constraint. We propose a solution based on generalized Benders decomposition and based on linear relaxation of the resulting sub-problems, which effectively reduces the number of integer variables to the number of MEC nodes. We evaluate the proposed solution with respect to operational cost, efficiency, and scalability in a simulated metropolitan area. Our results show that the proposed solution reduces the total cost significantly compared to a greedy baseline algorithm and a local search heuristic, and can scale to moderate problem instances.
  •  
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