| 1. |
- Ahmed, Jawwad, et al.
(författare)
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Survivability strategies for PCE-based WDM networks offering high reliability performance
- 2013
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Ingår i: National Fiber Optic Engineers Conference, NFOEC 2013. - Washington, D.C. : Optical Society of America.
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Konferensbidrag (refereegranskat)abstract
- Two approaches based on backup reprovisioning and path restoration are proposed for dynamic failure recovery in survivable, PCE-based, WDM networks. Results show that proposed schemes can achieve high connection availability in double link failure scenarios.
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| 2. |
- Alabbasi, Abdulrahman, et al.
(författare)
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Interplay of Processing and Radio Parameters : A Service-Oriented Performance Study
- 2020
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Ingår i: IEEE Systems Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 1932-8184 .- 1937-9234. ; 14:1, s. 398-409
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we propose general service-oriented end-to-end energy and delay models. They facilitate the evaluation of new schemes, by enabling flexible allocation of processing functions at multilayer radio access network. These models describe the underlaying processing of communication function (PCF)'s complexity and the induced bandwidth. We also introduce the concept of processing interference and link it to the average PCF option of the competing users at the cloud. The proposed framework shows the possibility to compensate the delay or energy degradation, e.g., due to radio environment, by reallocating processing parameters, e.g., allocation of PCF or number of virtual central processing units (VCPUs). Several conclusions are inferred from the system's evaluation. For instance, at lowmodulation index (MI), the behavior of overall energy consumption is dominated by PCF energy, not the transmission energy, whereas, at high MI, the behavior of overall energy consumption is dominated by transmission energy. Centralization of PCF reduces the impact of processing interference (of competing users) on the targeted service's delay from 11 to 2 ms, and service's energy consumption from 18 to 2 J. We further evaluate the impact of PCF on the decision of offloading the service, to be computed at the cloud.
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| 3. |
- Alabbasi, Abdulrahman, et al.
(författare)
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On Energy Efficiency of Prioritized IoT Systems
- 2017
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Ingår i: Globecom 2017 - 2017 IEEE Global Communications Conference. - : IEEE. - 9781509050192
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Konferensbidrag (refereegranskat)abstract
- The inevitable deployment of 5G and the Internet of Things (IoT) sheds the light on the importance of the energy efficiency (EE) performance of Device-to- Device (DD) communication systems. In this work, we address a potential IoT application, where different prioritized DD system, i.e., Low-Priority (LP) and High-Priority (HP) systems, co-exist and share the spectrum. We maximize the EE of each system by proposing two schemes. The first scheme optimizes the individual transmission power and the spatial density of each system. The second scheme optimizes the transmission power ratio of both systems and the spatial density of each one. We also construct and analytically solve a multi- objective optimization problem that combines and jointly maximizes both HP and LP EE performance. Unique structures of the addressed problems are verified. Via numerical results we show that the system which dominates the overall EE (combined EEs of both HP and LP) is the system corresponding to the lowest power for low/high power ratio (between HP and LP systems). However, if the power ratio is close to one, the dominating EE corresponds to the system with higher weight.
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| 4. |
- Alabbasi, Abdulrahman, et al.
(författare)
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Optimal Processing Allocation to Minimize Energy and Bandwidth Consumption in Hybrid CRAN
- 2018
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Ingår i: IEEE Transactions on Green Communications and Networking. - : Institute of Electrical and Electronics Engineers (IEEE). - 2473-2400. ; 2:2, s. 545-555
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Tidskriftsartikel (refereegranskat)abstract
- Cloud radio access network (CRAN) architecture is proposed to save energy, facilitate coordination between radio units, and achieve scalable solutions to improve radio network's performance. However, stringent delay and bandwidth constraints are incurred by fronthaul in CRAN [the network segment connecting RUs and digital units (DUs)]. Therefore, we propose a hybrid cloud radio access network architecture, where a DU's functionalities can be virtualized and split at several conceivable points. Each split option results in two-level deployment of the processing functions (central site level and remote site level) connected by a transport network, called midhaul. We study the interplay of energy efficiency and midhaul bandwidth consumption under optimal processing allocation. We jointly minimize the power and midhaul bandwidth consumption in H-CRAN, while satisfying network constraints, i.e., processing and midhaul bandwidth capacity. We enable power saving functionalities by shutting down different network components. The proposed model is formulated as a constraint programming problem. The proposed solution shows that 42 percentile of midhaul bandwidth savings can be achieved compared to the fully centralized CRAN; and 35 percentile of power consumption saving can be achieved compared to the case where all the network functions are distributed at the edge.
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| 5. |
- Azari, Amin, 1988-, et al.
(författare)
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Energy and Resource Efficiency by User Traffic Prediction and Classification in Cellular Networks
- 2022
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Ingår i: IEEE Transactions on Green Communications and Networking. - : Institute of Electrical and Electronics Engineers (IEEE). - 2473-2400. ; 6:2, s. 1082-1095
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Tidskriftsartikel (refereegranskat)abstract
- There is a lack of research on the analysis of peruser traffic in cellular networks, for deriving and following traffic-aware network management. In fact, the legacy design approach, in which resource provisioning and operation control are performed based on the cell-aggregated traffic scenarios, are not so energy- and cost-efficient and need to be substituted with user-centric predictive analysis of mobile network traffic and proactive network resource management. Here, we shed light on this problem by designing traffic prediction tools that utilize standard machine learning (ML) tools, including long shortterm memory (LSTM) and autoregressive integrated moving average (ARIMA) on top of per-user data. We present an expansive empirical evaluation of the designed solutions over a real network traffic dataset. Within this analysis, the impact of different parameters, such as the time granularity, the length of future predictions, and feature selection are investigated. As a potential application of these solutions, we present an ML-powered Discontinuous reception (DRX) scheme for energy saving. Towards this end, we leverage the derived ML models for dynamic DRX parameter adaptation to user traffic. The performance evaluation results demonstrate the superiority of LSTM over ARIMA in general, especially when the length of the training time series is high enough, and it is augmented by a wisely-selected set of features. Furthermore, the results show that adaptation of DRX parameters by online prediction of future traffic provides much more energy-saving at low latency cost in comparison with the legacy cell-wide DRX parameter adaptation.
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| 6. |
- Azari, Amin, et al.
(författare)
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Energy-Efficient and Reliable IoT Access Without Radio Resource Reservation
- 2021
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Ingår i: IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING. - : Institute of Electrical and Electronics Engineers (IEEE). - 2473-2400. ; 5:2, s. 908-920
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Tidskriftsartikel (refereegranskat)abstract
- One of the major challenges for Internet-of-Things applications is that the existing cellular technologies do not support the uplink IoT traffic in an energy-efficient manner. There are two principal ways for serving the uplink IoT traffic: grant-based (i.e., scheduled) and grant-free (i.e., random access). Grant-based access provides fine-grained control of reliability and latency at the cost of energy consumption required for signaling. Grant-free access removes the signaling overhead at the cost of looser control of performance in terms of reliability and latency. However, a precise analysis of reliability, latency and energy performance of grant-free access (GFA) is largely missing. This article focuses on a GFA-type protocol, in which a device transmits several packet replicas, asynchronously with respect to the other devices. Using stochastic geometry, we derive closed-form expressions for reliability, delay, and energy consumption, which can be used to identify the tradeoffs among these performance parameters. In order to improve the performance of the protocol, we develop a receiver that leverages the random timing and frequency offsets among the devices in order to facilitate resolution of collisions. This is complemented by a per-device adaptive scheme that controls the number of transmitted replicas. The evaluation confirms the validity of the analysis and the potential of the proposed solution, identifying operating regions in which GFA outperforms the grant-based access.
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| 7. |
- Azari, Amin, 1988-, et al.
(författare)
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Grant-Free Radio Access for Cellular IoT
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Radio resource management (RRM) is a major factor affecting the delay, reliability, and energy consumption of Internet of Things (IoT) communications. This article is focused on grant-free access, a class of techniques suited to support massive IoT connectivity. Within the proposed scheme, the IoT devices transmit multiple replicas of the same packet. In addition to that, the receiver makes use of the random timing and frequency offsets in order to carry out Successive Interference Cancellation (SIC). The system performance is investigated by using a model based on stochastic geometry, leading to closed-form expressions for the key performance indicators, such as reliability and battery lifetime. The framework allows optimization of the number of replicas per device. This results in overall improvement of the energy consumption, delay and reliability, at the expense of more complex processing at the Base Station. The evaluation results indicate that the proposed data transmission and reception schemes can significantly prolong battery lifetime of IoT devices by removing the need for connection establishment and reducing the number of retransmissions. The obtained results also indicate existence of traffic-load regions, where grant-free radio access outperforms the grant-based one, which is used in LTE and NB-IoT systems. These results pave the way for enabling intelligent grant-based/free operation mode switching in 5G networks.
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| 8. |
- Azari, Amin, 1988-, et al.
(författare)
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Machine Learning assisted Handover and Resource Management for Cellular Connected Drones
- 2020
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Ingår i: Proceedings of the IEEE Vehicular Technology Conference. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- Cellular connectivity for drones comes with a wide set of challenges as well as opportunities. Communication of cellular-connected drones is influenced by 3-dimensional mobility and line-of-sight channel characteristics which results in higher number of handovers with increasing altitude. Our cell planning simulations in coexistence of aerial and terrestrial users indicate that the severe interference from drones to base stations is a major challenge for uplink communications of terrestrial users. Here, we first present the major challenges in co-existence of terrestrial and drone communications by considering real geographical network data for Stockholm. Then, we derive analytical models for the key performance indicators (KPIs), including communications delay and interference over cellular networks, and formulate the handover and radio resource management (H-RRM) optimization problem. Afterwards, we transform this problem into a machine learning problem, and propose a deep reinforcement learning solution to solve HRRM problem. Finally, using simulation results, we present how the speed and altitude of drones, and the tolerable level of interference, shape the optimal H-RRM policy in the network. Especially, the heat-maps of handover decisions for different altitudes/speeds of drones have been presented, which promote a revision of the legacy handover schemes and boundaries of cells in the sky.
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| 9. |
- Azari, Amin, 1988-, et al.
(författare)
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On the Latency-Energy Performance of NB-IoT Systems in Providing Wide-Area IoT Connectivity
- 2019
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Ingår i: IEEE Transactions on Green Communications and Networking. - 2473-2400.
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Tidskriftsartikel (refereegranskat)abstract
- Narrowband Internet-of-Things (NB-IoT) offers a significant link budget improvement in comparison with the legacy networks by introducing different coverage classes, allowing repeated transmissions, and tuning the repetition order based on the path-loss in communications. However, those repetitions necessarily increase energy consumption and latency in the whole NB-IoT system. The extent to which the whole system is affected depends on the scheduling of the uplink and downlink channels. We address this question, not treated previously, by developing a tractable model of NB-IoT connectivity, comprising message exchanges in random-access, control, and data channels. The model is then used to analyze the impact of channel scheduling and interaction of coverage classes on the performance of IoT devices through the derivation of the expected latency and battery lifetime. These results are subsequently employed in determining the optimized operation points, i.e., (i) scheduling of data and control channels for a given set of users and respective coverage classes, or (ii) determining the optimal set of coverage classes and served users per coverage class for a given scheduling strategy. Simulations results show the validity of the analysis and confirm that channel scheduling and coexistence of coverage classes significantly affect latency and battery lifetime performance of NB-IoT devices.
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| 10. |
- Azari, Amin, et al.
(författare)
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Optimized Resource Provisioning and Operation Control for Low-power Wide-area IoT Networks
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Grant-free radio access is a promising solution for reducing energy consumption and access delay in low power wide-area (LPWA) Internet of Things (IoT) networks. This work is devoted to reliability modeling, battery-lifetime analysis, resource provisioning, and operation control for grantfreeIoT networks. Our modeling captures correlation in devices’locations, benefits from 3D (time/frequency/code) interference analysis, and enables coexistence analysis of multi-type IoT technologies. We derive the interplay amongst density of the access points, communication bandwidth, traffic volume, and quality of service (QoS) of communications. Deriving the interplay enables scalability analysis, i.e. it figures out the required increase in device's energy consumption (or access network’s resources) for compensating the increase in traffic volume or QoS demand. Our major contribution consists in deriving traffic loads and respective exchange rates in which, energy and cost resources of devices and the access network, respectively, could be traded to achieve a given level of QoS. We further indicate operation regions in which scaling a parameter turns from being a friend into a foe. Finally, we present energy- and cost-optimized operation control and resource provisioning strategies, respectively. The simulation results confirm tightness of the analytical expressions, and indicate the usefulness of them in planning and operation control of IoT networks.
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