Energy-Efficient Edge Computing Service Provisioning for Vehicular Networks: A Consensus ADMM Approach

In vehicular networks, in-vehicle user equipment (UE) with limited battery capacity can achieve opportunistic energy saving by offloading energy-hungry workloads to vehicular edge computing nodes via vehicle-to-infrastructure links. However, how to determine the optimal portion of workload to be off...

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Vydáno v:	IEEE transactions on vehicular technology Ročník 68; číslo 5; s. 5087 - 5099
Hlavní autoři:	Zhou, Zhenyu, Feng, Junhao, Chang, Zheng, Shen, Xuemin
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.05.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Ad hoc networks Algorithms Batteries Computer simulation consensus ADMM Convex functions Data transmission Edge computing Energy Energy conservation Energy consumption energy efficiency Energy transmission Handover Optimization Provisioning Topology Vehicle-to-infrastructure vehicular edge computing vehicular networks Workload workload offloading Workloads
ISSN:	0018-9545, 1939-9359
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Abstract	In vehicular networks, in-vehicle user equipment (UE) with limited battery capacity can achieve opportunistic energy saving by offloading energy-hungry workloads to vehicular edge computing nodes via vehicle-to-infrastructure links. However, how to determine the optimal portion of workload to be offloaded based on the dynamic states of energy consumption and latency in local computing, data transmission, workload execution and handover, is still an open issue. In this paper, we study the energy-efficient workload offloading problem and propose a low-complexity distributed solution based on consensus alternating direction method of multipliers. By incorporating a set of local variables for each UE, the original problem, in which the optimization variables of UEs are coupled together, is transformed into an equivalent general consensus problem with separable objectives and constraints. The consensus problem can be further decomposed into a bunch of subproblems, which are distributed across UEs and solved in parallel simultaneously. Finally, the proposed solution is validated based on a realistic road topology of Beijing, China. Simulation results have demonstrated that significant energy saving gain can be achieved by the proposed algorithm.
AbstractList	In vehicular networks, in-vehicle user equipment (UE) with limited battery capacity can achieve opportunistic energy saving by offloading energy-hungry workloads to vehicular edge computing nodes via vehicle-to-infrastructure links. However, how to determine the optimal portion of workload to be offloaded based on the dynamic states of energy consumption and latency in local computing, data transmission, workload execution and handover, is still an open issue. In this paper, we study the energy-efficient workload offloading problem and propose a low-complexity distributed solution based on consensus alternating direction method of multipliers. By incorporating a set of local variables for each UE, the original problem, in which the optimization variables of UEs are coupled together, is transformed into an equivalent general consensus problem with separable objectives and constraints. The consensus problem can be further decomposed into a bunch of subproblems, which are distributed across UEs and solved in parallel simultaneously. Finally, the proposed solution is validated based on a realistic road topology of Beijing, China. Simulation results have demonstrated that significant energy saving gain can be achieved by the proposed algorithm.
Author	Zhou, Zhenyu Chang, Zheng Feng, Junhao Shen, Xuemin
Author_xml	– sequence: 1 givenname: Zhenyu orcidid: 0000-0002-3344-4463 surname: Zhou fullname: Zhou, Zhenyu email: zhenyu_zhou@ncepu.edu.cn organization: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, China – sequence: 2 givenname: Junhao orcidid: 0000-0002-3655-2275 surname: Feng fullname: Feng, Junhao email: junhao_feng@ncepu.edu.cn organization: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, China – sequence: 3 givenname: Zheng orcidid: 0000-0003-3766-820X surname: Chang fullname: Chang, Zheng email: zheng.chang@jyu.fi organization: Faculty of Information Technology, University of Jyväskylä, Jyväskylä, Finland – sequence: 4 givenname: Xuemin orcidid: 0000-0002-4140-287X surname: Shen fullname: Shen, Xuemin email: xshen@bbcr.uwaterloo.ca organization: Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada
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SubjectTerms	Ad hoc networks Algorithms Batteries Computer simulation consensus ADMM Convex functions Data transmission Edge computing Energy Energy conservation Energy consumption energy efficiency Energy transmission Handover Optimization Provisioning Topology Vehicle-to-infrastructure vehicular edge computing vehicular networks Workload workload offloading Workloads
Title	Energy-Efficient Edge Computing Service Provisioning for Vehicular Networks: A Consensus ADMM Approach
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