基于代码的车辆雾网络计算卸载

Fangzhe Chen, Zhibin Gao, Zhang Liu, Lianfeng Huang, Yuliang Tang
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引用次数: 0

摘要

随着车载信息娱乐应用数量呈指数级增长,将从计算密集型应用中划分出来的若干子任务卸载到不同的雾节点上被认为是满足卸载需求的一种很有前途的范式。然而,在任何雾节点上子任务的失败传输都会增加车辆雾网络(VeFNs)的执行延迟和能耗。在本文中,我们利用代码技术产生额外的子任务,并以计算资源的冗余交换可靠性,从而提高了车对车(V2V)通信的鲁棒性,减少了计算卸载的开销。此外,我们采用了基于模拟退火(CBSA)的基于码的计算卸载算法,找到最优的编码方案和资源分配策略。数值结果验证了算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Code-based Computation Offloading in Vehicular Fog Networks
With the number of in-vehicle infotainment applications exponentially increasing, offloading several subtasks divided from computation-intensive application to different fog nodes is convinced as a promising paradigm to satisfy the offloading requirements. However, failure transmission of subtask in any fog node will increase execution latency and energy consumption in Vehicular Fog Networks (VeFNs). In this paper, we leverage the code technology to produce extra subtasks and exchange the redundancy of computing resources for reliability, which improve the robustness of vehicle to vehicle (V2V) communication and decrease the overhead of computation offloading. Furthermore, we adopt a code-based computation offloading algorithm based on simulated annealing (CBSA) that finds the optimal coding scheme and resources allocation strategy. The numerical results are illustrated to demonstrate effectiveness of proposed algorithm.
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