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1.
  • Bayram, Firas, et al. (creator_code:aut_t)
  • From concept drift to model degradation : An overview on performance-aware drift detectors
  • 2022
  • record:In_t: Knowledge-Based Systems. - : Elsevier BV. - 0950-7051 .- 1872-7409. ; 245
  • swepub:Mat_researchreview_t (swepub:level_refereed_t)abstract
    • The dynamicity of real-world systems poses a significant challenge to deployed predictive machine learning (ML) models. Changes in the system on which the ML model has been trained may lead to performance degradation during the system’s life cycle. Recent advances that study non-stationary environments have mainly focused on identifying and addressing such changes caused by a phenomenon called concept drift. Different terms have been used in the literature to refer to the same type of concept drift and the same term for various types. This lack of unified terminology is set out to create confusion on distinguishing between different concept drift variants. In this paper, we start by grouping concept drift types by their mathematical definitions and survey the different terms used in the literature to build a consolidated taxonomy of the field. We also review and classify performance-based concept drift detection methods proposed in the last decade. These methods utilize the predictive model’s performance degradation to signal substantial changes in the systems. The classification is outlined in a hierarchical diagram to provide an orderly navigation between the methods. We present a comprehensive analysis of the main attributes and strategies for tracking and evaluating the model’s performance in the predictive system. The paper concludes by discussing open research challenges and possible research directions.
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2.
  • Gokan Khan, Michel, 1989-, et al. (creator_code:aut_t)
  • PerfSim : A Performance Simulator for Cloud Native Microservice Chains
  • 2023
  • record:In_t: IEEE Transactions on Cloud Computing. - : IEEE. - 2168-7161. ; :2, s. 1395-1413
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Cloud native computing paradigm allows microservice-based applications to take advantage of cloud infrastructure in a scalable, reusable, and interoperable way. However, in a cloud native system, the vast number of configuration parameters and highly granular resource allocation policies can significantly impact the performance and deployment cost of such applications. For understanding and analyzing these implications in an easy, quick, and cost-effective way, we present PerfSim, a discrete-event simulator for approximating and predicting the performance of cloud native service chains in user-defined scenarios. To this end, we proposed a systematic approach for modeling the performance of microservices endpoint functions by collecting and analyzing their performance and network traces. With a combination of the extracted models and user-defined scenarios, PerfSim can simulate the performance behavior of service chains over a given period and provides an approximation for system KPIs, such as requests' average response time. Using the processing power of a single laptop, we evaluated both simulation accuracy and speed of PerfSim in 104 prevalent scenarios and compared the simulation results with the identical deployment in a real Kubernetes cluster. We achieved ~81-99% simulation accuracy in approximating the average response time of incoming requests and ~16-1200 times speed-up factor for the simulation.
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3.
  • Ma, Yunpeng, et al. (creator_code:aut_t)
  • Automated and Systematic Digital Twins Testing for Industrial Processes
  • 2023
  • record:In_t: Proceedings - 2023 IEEE 16th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2023. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350333350 ; , s. 149-158
  • swepub:Mat_conferencepaper_t (swepub:level_refereed_t)abstract
    • Digital twins (DT) of industrial processes have become increasingly important. They aim to digitally represent the physical world to help evaluate, optimize, and predict physical processes and behaviors. Therefore, DT is a vital tool to improve production automation through digitalization and becomes more sophisticated due to rapidly evolving simulation and modeling capabilities, integration of IoT sensors with DT, and high-capacity cloud/edge computing infrastructure. However, the fidelity and reliability of DT software are essential to represent the physical world. This paper shows an automated and systematic test architecture for DT that correlates DT states with real-time sensor data from a production line in the forging industry. Our evaluation shows that the architecture can significantly accelerate the automatic DT testing process and improve its reliability. A systematic online DT testing method can significantly detect the performance shift and continuously improve the DT's fidelity. The snapshot creation methodology and testing agent architecture can be an inspiration and can be generally applicable to other industrial processes that use DT to generalize their automated testing. 
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4.
  • Abdollahi, Kamran, et al. (creator_code:aut_t)
  • Improving Performance of On Demand Multicast Routing by deleting lost join query packet
  • 2010
  • record:In_t: Proceedings of The Sixth Advanced International Conference on Telecommunications - AICT 2010. - : IEEE conference proceedings. - 9780769540214 ; , s. 316-322
  • swepub:Mat_conferencepaper_t (swepub:level_refereed_t)abstract
    • A Mobile ad hoc network is a collection of wireless nodes that dynamically organize themselves to form a network without the need for any fixed infrastructure or centralized administration. The network topology dynamically changes frequently in an unpredictable manner since nodes are free to move. Support for multicasting is essential in such environment as it is considered to be an efficient way to deliver information from source nodes to many client nodes. A problem with multicast routing algorithms is their efficiency as their forwarding structure determines the overall network resource consumption makes them significantly less efficient than unicast routing algorithms. In this research, we improve the performance of the popular ODMRP multicast routing protocol by restricting the domain of join query packets, which have been lost. This is achieved by augmenting the join query packets with minimum extra information (one field), which denotes the number of the visited node from previous forwarding group. Simulation results show, that our mechanisms significantly reduce the control traffic and thus the overall latency and power consumption in the network.
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5.
  • Aboueata, N., et al. (creator_code:aut_t)
  • Supervised machine learning techniques for efficient network intrusion detection
  • 2019
  • record:In_t: Proceedings - International Conference on Computer Communications and Networks, ICCCN. - : IEEE. - 9781728118567
  • swepub:Mat_conferencepaper_t (swepub:level_refereed_t)abstract
    • Cloud computing is gaining significant traction and virtualized data centers are becoming popular as a cost-effective infrastructure in telecommunication industry. Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) are being widely deployed and utilized by end users, including many private as well as public organizations. Despite its wide-spread acceptance, security is still the biggest threat in cloud computing environments. Users of cloud services are under constant fear of data loss, security breaches, information theft and availability issues. Recently, learning-based methods for security applications are gaining popularity in the literature with the advents in machine learning (ML) techniques. In this work, we explore applicability of two well-known machine learning approaches, which are, Artificial Neural Networks (ANN) and Support Vector Machines (SVM), to detect intrusions or anomalous behavior in the cloud environment. We have developed ML models using ANN and SVM techniques and have compared their performances. We have used UNSW-NB-15 dataset to train and test the models. In addition, we have performed feature engineering and parameter tuning to find out optimal set of features with maximum accuracy to reduce the training time and complexity of the ML models. We observe that with proper features set, SVM and ANN techniques have been able to achieve anomaly detection accuracy of 91% and 92% respectively, which is higher compared against that of the one achieved in the literature, with reduced number of features needed to train the models.
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6.
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7.
  • Agapi, Mesodiakaki, et al. (creator_code:aut_t)
  • Joint User Association and Backhaul Routing for Green 5G Mesh Millimeter Wave Backhaul Networks
  • 2017
  • record:In_t: Proceedings Of The 20Th Acm International Conference On Modelling, Analysis And Simulation Of Wireless And Mobile Systems. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450351645 ; , s. 179-186
  • swepub:Mat_conferencepaper_t (swepub:level_refereed_t)abstract
    • With the advance of fifth generation (5G) networks, network density needs to grow significantly in order to meet the required capacity demands. A massive deployment of small cells may lead to a high cost for providing. ber connectivity to each node. Consequently, many small cells are expected to be connected through wireless links to the umbrella eNodeB, leading to a mesh backhaul topology. This backhaul solution will most probably be composed of high capacity point-to-point links, typically operating in the millimeter wave (mmWave) frequency band due to its massive bandwidth availability. In this paper, we propose a mathematical model that jointly solves the user association and backhaul routing problem in the aforementioned context, aiming at the energy efficiency maximization of the network. Our study considers the energy consumption of both the access and backhaul links, while taking into account the capacity constraints of all the nodes as well as the fulfillment of the service-level agreements (SLAs). Due to the high complexity of the optimal solution, we also propose an energy efficient heuristic algorithm (Joint), which solves the discussed joint problem, while inducing low complexity in the system. We numerically evaluate the algorithm performance by comparing it not only with the optimal solution but also with reference approaches under different traffic load scenarios and backhaul parameters. Our results demonstrate that Joint outperforms the state-of-the-art, while being able to find good solutions, close to optimal, in short time.
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8.
  • Al-Dulaimy, Auday, et al. (creator_code:aut_t)
  • MultiScaler : A Multi-Loop Auto-Scaling Approach for Cloud-Based Applications
  • 2020
  • record:In_t: IEEE Transactions on Cloud Computing. - : Institute of Electrical and Electronics Engineers (IEEE). - 2168-7161.
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Cloud computing offers a wide range of services through a pool of heterogeneous Physical Machines (PMs) hosted on cloud data centers, where each PM can host several Virtual Machines (VMs). Resource sharing among VMs comes with major benefits, but it can create technical challenges that have a detrimental effect on the performance. To ensure a specific service level requested by the cloud-based applications, there is a need for an approach to assign adequate resources to each VM. To this end, we present our novel Multi-Loop Control approach, called MultiScaler , to allocate resources to VMs based on the Service Level Agreement (SLA) requirements and the run-time conditions. MultiScaler is mainly composed of three different levels working closely with each other to achieve an optimal resource allocation. We propose a set of tailor-made controllers to monitor VMs and take actions accordingly to regulate contention among collocated VMs, to reallocate resources if required, and to migrate VMs from one PM to another. The evaluation in a VMware cluster have shown that the MultiScaler approach can meet applications performance goals and guarantee the SLA by assigning the exact resources that the applications require. Compared with sophisticated baselines, MultiScaler produces significantly better reaction to changes in workloads even under the presence of noisy neighbors.
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9.
  • Alfredsson, Rebecka, et al. (creator_code:aut_t)
  • Accelerating a Transport Layer based 5G Multi-Access Proxy on SmartNIC
  • 2022
  • record:In_t: Würzburg Workshop on Next-Generation Communication Networks (WueWoWas'22). - : Würzburgs universitet. ; , s. 4-
  • swepub:Mat_conferencepaper_t (swepub:level_scientificother_t)abstract
    • Utilizing multiple access technologies such as 5G,4G, and Wi-Fi within a coherent framework is currentlystandardized by 3GPP within 5G ATSSS. Indeed, distributingpackets over multiple networks can lead to increased robustness,resiliency and capacity. A key part of such a framework isthe multi-access proxy, which transparently distributes packetsover multiple paths. As the proxy needs to serve thousands ofcustomers, scalability and performance are crucial for operatordeployments. In this paper, we leverage recent advancementsin data plane programming, implement a multi-access proxybased on the MP-DCCP tunneling approach in P4 and hardwareaccelerate it by deploying the pipeline on a smartNIC. Thisis challenging due to the complex scheduling and congestioncontrol operations involved. We present our pipeline and datastructures design for congestion control and packet schedulingstate management. Initial measurements in our testbed showthat packet latency is in the range of 25 μs demonstrating thefeasibility of our approach.
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10.
  • Ali Yahiya, Tara, et al. (creator_code:aut_t)
  • Seamless Interworking of WLAN and WMAN Wireless Networks
  • 2006
  • swepub:Mat_conferencepaper_t (swepub:level_refereed_t)abstract
    • Future network environments will be heterogeneous and mobile terminals will have the opportunity to dynamically select among many different access technologies. Therefore, it is important to provide service continuity in case of vertical handovers when terminals change the access technology. Two important wireless access technologies are WLAN (Wireless Local Access Networks) and WMAN (Wireless Metropolitan Access Networks) networks. In this paper, we address several challenges related to a seamless integration of those technologies. We highlight important aspects for designing a WLAN/WMAN interworking architecture and we address important Quality of Service (QoS) issues for such interworked systems like degree of QoS support provided by the technologies, QoS mapping and signalling for vertical handover. By formulating several interworking scenarios, where WLAN users with ongoing voice, video and data sessions hand over to WMAN, we study QoS and performance issues and analyse feasibility of seamless session continuity through simulations
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