Joint Optimal Allocation of Wireless Resource and MEC Computation Capability in Vehicular Network

Min Zhu, Yanzhao Hou, Xiaofeng Tao, Tengfei Sui, Lei Gao
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引用次数: 7

Abstract

Numerous applications of vehicles are computation- intensive and delay-sensitive. In order to deal with the problem caused by limited wireless and computation capability in the Mo- bile Edge Computing (MEC) enabled vehicular network, a Joint Optimization of Wireless and Computation Allocation (JOWCA) algorithm is proposed to minimize global delay of MEC-enabled vehicular network. The JOWCA algorithm consists of vehicle- to-vehicle (V2X) matching and MEC computation capability allocation. In the V2X matching, a Graph-based Interference Cancellation (Graph-IC) scheme is proposed to allocate Resource Blocks (RBs) for vehicle-to- infrastructure (V2I) links and vehicle- to-vehicle (V2V) links to mitigate co-channel interference. The Graph-IC contains an adaptive interference threshold modified Heuristic Clustering (HC) algorithm and Hungarian algorithm. In the MEC computation capability allocation, the optimal solution of V2I link offloading ratio and MEC computation capability scheduling are obtained by applying Karush-Kuhn- Tucker (KKT) condition. Simulation shows that the proposed scheme can effectively reduce the global delay of the MEC- enabled vehicular network.
车载网络无线资源联合优化分配与MEC计算能力
车辆的许多应用都是计算密集型和延迟敏感的。针对移动边缘计算(mobile Edge Computing, MEC)车辆网络中无线和计算能力有限的问题,提出了一种无线和计算分配联合优化(Joint Optimization of wireless and computation Allocation, JOWCA)算法,以最小化移动边缘计算(MEC)车辆网络的全局延迟。JOWCA算法包括车对车(V2X)匹配和MEC计算能力分配。在V2X匹配中,提出了一种基于图的干扰消除(Graph-IC)方案,为车对基础设施(V2I)链路和车对车(V2V)链路分配资源块(RBs),以减轻同信道干扰。图集成电路包含自适应干扰阈值改进的启发式聚类算法和匈牙利算法。在MEC计算能力分配中,应用Karush-Kuhn- Tucker (KKT)条件,得到了V2I链路卸载比和MEC计算能力调度的最优解。仿真结果表明,该方案能够有效地降低基于MEC的车辆网络的全局时延。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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