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  • 1.
    Ahani, Ghafour
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    BS-assisted Task Offloading for D2D Networks with Presence of User Mobility2019In: 2019 IEEE 89TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2019-SPRING), IEEE , 2019Conference paper (Refereed)
    Abstract [en]

    Task offloading is a key component in mobile edge computing. Offloading a task to a remote server takes communication and networking resources. An alternative is device-to-device (D2D) offloading, where a task of a device is offloaded to some device having computational resource available. The latter requires that the devices are within the range of each other, first for task collection, and later for result gathering. Hence, in mobility scenarios, the performance of D2D offloading will suffer if the contact rates between the devices are low. We enhance the setup to base station (BS) assisted D2D offloading, namely, a BS can act as a relay for task distribution or result collection. However, this would imply additional consumption of wireless resources. The associated cost and the improvement in completion time of task offloading compose a fundamental trade-off. For the resulting optimization problem, we mathematically prove the complexity, and propose an algorithm using Lagrangian duality. The simulation results demonstrate not only that the algorithm has close-to-optimal performance, but also provide structural insights of the optimal trade-off.

  • 2.
    Ahani, Ghafour
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    On optimal proactive and retention-aware caching with user mobility2018In: 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), IEEE, 2018Conference paper (Refereed)
    Abstract [en]

    Caching popular contents at edge devices is an effective solution to alleviate the burden of the backhaul networks. Earlier investigations commonly neglected the storage cost in caching. More recently, retention-aware caching, where both the downloading cost and storage cost are accounted for, is attracting attention. Motivated by this, we address proactive and retention-aware caching problem with the presence of user mobility, optimizing the sum of the two types of costs. More precisely, a cost-optimal caching problem for vehicle-to-vehicle networks is formulated with joint consideration of the impact of the number of vehicles, cache size, storage cost, and content request probability. This is a combinatorial optimization problem. However, we derive a stream of analytical results and they together lead to an algorithm that guarantees global optimum with polynomial-time complexity. Numerical results show significant improvements in comparison to popular caching and random caching.

  • 3.
    Deng, Tao
    et al.
    Southwest Jiaotong Univ, Inst Mobile Commun, Chengdu, Sichuan, Peoples R China..
    Ahani, Ghafour
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. Komar Univ Sci & Technol, Dept Comp Engn, Sulaymaniyah, Iraq..
    Fan, Pingzhi
    Southwest Jiaotong Univ, Inst Mobile Commun, Chengdu, Sichuan, Peoples R China..
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Cost-Optimal Caching for D2D Networks with Presence of User Mobility2017In: GLOBECOM 2017 - 2017 IEEE Global Communications Conference, IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    Caching popular files at user equipments (UEs) provides an effective way to alleviate the burden of the back-haul networks. Generally, popularity based caching is not a system-wide optimal strategy, especially for mobility scenarios. Motivated by this observation, an optimal caching problem with respect to user mobility is investigated. To be specific, a cost-optimal caching problem (COCP) for device-to-device (D2D) networks is formulated, in which the impact of user mobility, cache size, and total number of encoded file segments are considered. Compared with the related studies, our investigation guarantees that the collected segments are non-overlapping, takes into account the cost of downloading from the network, and provides a rigorous complexity analysis. For problem solving, we first prove that the optimal caching placement of one user, giving other users' caching placements, can be derived in polynomial time. Then, based on this proof, a fast yet effective caching placement algorithm for all users is developed. Simulation results verify the effectiveness of this algorithm by comparing it to conventional caching algorithms.

  • 4. Deng, Tao
    et al.
    Ahani, Ghafour
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Fan, Pingzhi
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Cost-optimal caching for D2D networks with user mobility: Modeling, analysis, and computational approaches2018In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 5, p. 3082-3094Article in journal (Refereed)
  • 5.
    Deng, Tao
    et al.
    Southwest Jiaotong Univ, Sch Informat Sci & Technol, Chengdu 610031, Sichuan, Peoples R China.
    Fan, Pingzhi
    Southwest Jiaotong Univ, Sch Informat Sci & Technol, Chengdu 610031, Sichuan, Peoples R China.
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Optimizing Retention-Aware Caching in Vehicular Networks2019In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 67, no 9, p. 6139-6152Article in journal (Refereed)
    Abstract [en]

    Caching is an effective way to address the challenges due to explosive data traffic growth and massive device connectivity in fifth-generation (5G) networks. Currently, few works on caching pay attention to the impact of the time duration for which content is stored, called retention time, on caching optimization. The research on retention time is motivated by two practical issues, i.e., flash memory damage and storage rental cost in cloud networks, together giving rise to the storage cost. How to optimize caching contents taking the storage cost into consideration is a challenging problem, especially for the scenarios with cache-enabled mobile nodes. In this paper, a retention-aware caching problem (RACP) in vehicular networks is formulated, considering the impact of the storage cost. The problem's complexity analysis is provided. For symmetric cases, an optimal dynamic programming (DP) algorithm with polynomial time complexity is derived. For general cases, a low complexity and effective retention aware multi-helper caching algorithm (RAMA) is proposed. Numerical results are used to verify the effectiveness of the algorithms.

  • 6. Deng, Tao
    et al.
    You, Lei
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Fan, Pingzhi
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Device caching for network offloading: Delay minimization with presence of user mobility2018In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 7, no 4, p. 558-561Article in journal (Refereed)
  • 7.
    Ecker, Grit
    et al.
    INFORM GmbH, Risk & Fraud Division, Aachen, Germany.
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. Department of Science and Technology, Linköping University, Norrköping, Sweden.
    Koster, Arie M. C. A.
    Lehrstuhl II für Mathematik, RWTH Aachen University, Aachen, Germany.
    Schmeink, Anke
    Institute for Theoretical Information Technology, RWTH Aachen University, Aachen, Germany.
    Accurate optimization models for interference constrained bandwith allocation in cellular networks2019In: Computers & Operations Research, ISSN 0305-0548, E-ISSN 1873-765X, Vol. 101, p. 1-12Article in journal (Refereed)
    Abstract [en]

    In cellular networks, the signal-to-interference-plus-noise ratio (SINR) is a key metric for link availability and quality. For network planning purposes, a straightforward modeling unfortunately yields numerically difficult optimization models. Further, given a required data rate of a link, its bandwidth consumption depends nonlinearly on the SINR.

    In this paper, we develop two novel approaches to jointly model SINR-based link availability and bandwidth requirements accurately. The first approach is a set-wise formulation from a user’s point of view, while the second one exploits discrete channel quality indicators. We compare these formulations with three known approximate approaches numerically, revealing the clear outperformance of our approaches in terms of exactness. Moreover, since the exact models comprise an exponential number of either variables or constraints, we discuss their pros and cons in a further computational study and develop a more efficient algorithm dealing implicitly with the involved constraints.

  • 8. Lei, Lei
    et al.
    Vu, Thang X.
    You, Lei
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Fowler, Scott
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Efficient minimum-energy scheduling with machine-learning based predictions for multiuser MISO systems2018In: Proc. International Conference on Communications: ICC 2018, IEEE Communications Society, 2018Conference paper (Refereed)
  • 9. Lei, Lei
    et al.
    You, Lei
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Dai, Gaoyang
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Vu, Thang Xuan
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Chatzinotas, Symeon
    A deep learning approach for optimizing content delivering in cache-enabled HetNet2017In: Proc. 14th International Symposium on Wireless Communication Systems, IEEE, 2017, p. 449-453Conference paper (Refereed)
  • 10.
    Lei, Lei
    et al.
    Luxembourg Univ, Interdisciplinary Ctr Secur Reliabil & Trust, Luxembourg, Luxembourg.
    You, Lei
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Yang, Yang
    Luxembourg Univ, Interdisciplinary Ctr Secur Reliabil & Trust, Luxembourg, Luxembourg.
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Chatzinotas, Symeon
    Luxembourg Univ, Interdisciplinary Ctr Secur Reliabil & Trust, Luxembourg, Luxembourg.
    Ottersten, Bjorn
    Luxembourg Univ, Interdisciplinary Ctr Secur Reliabil & Trust, Luxembourg, Luxembourg.
    Power and Load Optimization in Interference-Coupled Non-Orthogonal Multiple Access Networks2018In: 2018 IEEE Global Communications Conference (GLOBECOM), IEEE , 2018Conference paper (Refereed)
    Abstract [en]

    Towards energy savings in large-scale non-orthogonal multiple access (NOMA) networks, we investigate power and load optimization for multi-cell and multi-carrier NOMA systems in this paper. To capture the coupling relation of mutual interference among cells, firstly, we extend a load-coupling model from orthogonal multiple access (OMA) to NOMA networks. Next, with this analytical tool, we formulate the considered optimization problem in NOMA-based load-coupled systems, where optimizing load, power, and determining decoding order are the key aspects in the optimization. Theoretically, we prove that the minimum network energy consumption can be achieved by using all the time-frequency resources in each cell to deliver users' demand. To achieve the optimal load and enable efficient power optimization, we develop a power-adjustment algorithm. Numerical results demonstrate promising energy-saving gains of NOMA over OMA in large-scale cellular networks, in particular for the high-demand and resource-limited scenarios.

  • 11. Lei, Lei
    et al.
    You, Lei
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Yang, Yang
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Chatzinotas, Symeon
    Ottersten, Björn
    Power and load optimization in interference-coupled non-orthogonal multiple access networks2018In: Proc. 37th Global Communications Conference, IEEE Communications Society, 2018Conference paper (Refereed)
  • 12.
    Wiatr, Pawel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Chen, Jiajia
    KTH Royal Inst Technol, Opt Networks Lab, Stockholm, Sweden..
    Monti, Paolo
    KTH Royal Inst Technol, Opt Networks Lab, Stockholm, Sweden..
    Wosinska, Lena
    KTH Royal Inst Technol, Opt Networks Lab, Stockholm, Sweden..
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Device Reliability Performance Awareness: Impact of RWA on EDFA Failure Reparation Cost in Optical Networks2017In: Proceedings of 2017 9Th International Workshop On Resilient Networks Design And Modeling (Rndm) / [ed] Rak, J Bilo, D Marzo, J Calle, E Pareta, JS, IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    High reliability performance of network is essential to minimize the possible network service interruption time, particularly in optical backbone networks where a large amount of data can be affected by a single failure. The existing studies on improvement of network reliability performance assume that failures of network devices are not related to the traffic load, which on the other hand, is not always true. For example, the lifetime of erbium doped fiber amplifier (EDFA) depends on the number of amplified lightpaths passing through. Encouraged by this observation, in this paper, we investigate the impact of used routing and wavelength assignment (RWA) algorithm on the number of failures in the network, and as a consequence on the network operational cost related to the failure reparation. We propose and evaluate a novel RWA approach, referred to as reliability performance aware RWA (RA-RWA), taking into account particular EDFA reliability performance characteristics with the goal of reducing the number of EDFA failures. The assessment results show that the operational cost related to EDFA failure reparation is impacted by the chosen RWA. The proposed RA-RWA provides 6% reduction, while other analyzed RWA algorithm, i.e., least loaded path (LLP), causes significant rise (up to 27%) of EDFA related failure reparation cost compared to the classical shortest path (SP) approach. In addition, RA-RWA offers further benefits in terms of reduced blocking probability compared to the SP. Concluding, we show that considering device reliability performance characteristics in RWA is important for the optical network operators as it can impact the network operational cost related to EDFA failure reparation.

  • 13.
    Wiatr, Pawel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Chen, Jiajia
    Optical Networks Lab, KTH Royal Institute of Technology, Stockholm, Sweden.
    Monti, Paolo
    Optical Networks Lab, KTH Royal Institute of Technology, Stockholm, Sweden.
    Wosinska, Lena
    Optical Networks Lab, KTH Royal Institute of Technology, Stockholm, Sweden.
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Routing and wavelength assignment vs EDFA reliability performance in optical backbone networks: An operational cost perspective2019In: Optical Switching and Networkning Journal, ISSN 1573-4277, E-ISSN 1872-9770, Vol. 31, p. 211-217Article in journal (Refereed)
    Abstract [en]

    A failure in optical backbone network can cause tremendous consequences as a substantial number of connections often each carrying a large amount of data can be interrupted. Therefore, high reliability performance is essential for the network operators. Many existing works that aim at improving network reliability performance implicitly assume that the lifetime of devices is constant and independent of the traffic load. However, the reliability performance of a device is related to its occupancy. For example, the failure rate of erbium doped fiber amplifier (EDFA) can be expressed as a function of the number of amplified wavelengths. On the other hand, the choice of routing and wavelength assignment (RWA) algorithm impacts the link load and, as a consequence, can influence the number of EDFA failures in the network.

    In this paper we examine how RWA can impact the failure reparation related network operational costs. Several types of RWA approaches are considered, namely load-balancing, energy-awareness, and reliability-awareness. Among all the considered RWA algorithms, the reliability-aware RWA (RA-RWA) approach leverages on EDFA reliability profile to reduce the number of EDFA failures in the network and the related operational costs.

    The simulation results show that the RWA algorithm impacts in a significant way the operational costs caused by EDFA failures. The cost associated with reparation of an EDFA decreases by 7.8% (in case of RA-RWA) and increases by up to 40% (in case of a load-balancing approach) compared to the classical Shortest Path (SP) approach. Moreover, the cost caused by connection rerouting due to link unavailability triggered by EDFA failure exhibits a 20% decrease (RA-RWA) and up to 94% increase (energy-aware algorithm). We also analyze some key network performance metrics that may be affected by RWA, including blocking probability, link occupancy distribution, and path length.

  • 14.
    Wiatr, Pawel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Reliability performance aware routing2018In: Proc. 10th International Workshop on Resilient Networks Design and Modeling, IEEE, 2018Conference paper (Refereed)
  • 15.
    Wiatr, Pawel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Wosinska, Lena
    KTH Royal Inst Technol, Opt Networks Lab, Stockholm, Sweden.
    Chen, Jiajia
    KTH Royal Inst Technol, Opt Networks Lab, Stockholm, Sweden.
    Optical Interconnect Architectures for Datacenters2018In: 2018 IEEE Photonics Conference (IPC) / [ed] Winzer, P Tsang, HK Capmany, J Yao, J Fontaine, N Dutta, N, IEEE, 2018Conference paper (Refereed)
    Abstract [en]

    This paper highlights the challenges faced by the current datacenter networks, where using photonic technology offers a numbers of obvious advantages. Some existing optical intra-datacenter network architectures will be presented along with new ideas allowing for reduction of energy consumption and required spectrum resources.

  • 16.
    You, Lei
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Lei, Lei
    Luxembourg Univ, Interdisciplinary Ctr Secur Reliabil & Trust, Luxembourg, Luxembourg..
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Sun, Sumei
    Inst Infocomm Res, A STAR, Singapore, Singapore..
    Chatzinotas, Symeon
    Luxembourg Univ, Interdisciplinary Ctr Secur Reliabil & Trust, Luxembourg, Luxembourg..
    Ottersten, Bjoern
    Luxembourg Univ, Interdisciplinary Ctr Secur Reliabil & Trust, Luxembourg, Luxembourg..
    A Framework for Optimizing Multi-cell NOMA: Delivering Demand with Less Resource2017In: GLOBECOM 2017 - 2017 IEEE Global Communications Conference, IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    Non-orthogonal multiple access (NOMA) allows multiple users to simultaneously access the same time-frequency resource by using superposition coding and successive interference cancellation (SIC). Thus far, most papers on NOMA have focused on performance gain for one or sometimes two base stations. In this paper, we study multi-cell NOMA and provide a general framework for user clustering and power allocation, taking into account inter-cell interference, for optimizing resource allocation of NOMA in multi-cell networks of arbitrary topology. We provide a series of theoretical analysis, to algorithmically enable optimization approaches. The resulting algorithmic notion is very general. Namely, we prove that for any performance metric that monotonically increases in the cells' resource consumption, we have convergence guarantee for global optimum. We apply the framework with its algorithmic concept to a multi-cell scenario to demonstrate the gain of NOMA in achieving significantly higher efficiency.

  • 17.
    You, Lei
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    A Note on Decoding Order in Optimizing Multi-cell NOMAManuscript (preprint) (Other academic)
  • 18.
    You, Lei
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Joint CoMP-Cell Selection and Resource Allocation in Fronthaul-Constrained C-RAN2017In: Proc. 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, IEEE, 2017Conference paper (Refereed)
  • 19.
    You, Lei
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    User-centric Performance Optimization with Remote Radio Head Cooperation in C-RAN2017Manuscript (preprint) (Other academic)
  • 20.
    You, Lei
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Yuan, Di
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Lei, Lei
    Sun, Sumei
    Chatzinotas, Symeon
    Ottersten, Björn
    Resource optimization with load coupling in multi-cell NOMA2018In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 7, p. 4735-4749Article in journal (Refereed)
1 - 20 of 20
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