Task offloading in Internet of Vehicles (IoV) involves numerous steps and optimization variables such as: where to offload tasks, how to allocate computation resources, how to adjust offloading ratio and transmit power for offloading, and such optimization variables and hybrid combination features are highly coupled with each other. Thus, this is a fully challenge issue to optimize these variables for task offloading to sustainably reduce energy consumption with load balancing while ensuring that a task is completed before its deadline. In this paper, we first provide a Mixed Integer Nonlinear Programming Problem (MINLP) formulation for such task offloading under energy and deadline constraints in IoV. Furthermore, in order to efficiently solve the formulated MINLP, we decompose it into two subproblems, and design a low-complexity Joint Optimization for Energy Consumption and Task Processing Delay (JOET) algorithm to optimize selection decisions, resource allocation, offloading ratio and transmit power adjustment. We carry out extensive simulation experiments to validate JOET. Simulation results demonstrate that JOET outperforms many representative existing approaches in quickly converge and effectively reduce energy consumption and delay. Specifically, average energy consumption and task processing delay have been reduced by 15.93% and 15.78%, respectively, and load balancing efficiency has increased by 10.20%.

中文翻译：

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JOET：面向车联网的可持续车辆辅助边缘计算

车联网(IoV)中的任务卸载涉及众多步骤和优化变量，例如：在哪里卸载任务、如何分配计算资源、如何调整卸载比和传输功率以进行卸载，并且此类优化变量和混合组合特征具有高度相互耦合。因此，优化用于任务卸载的这些变量以通过负载平衡持续降低能耗，同时确保任务在截止日期前完成是一个完全具有挑战性的问题。在本文中，我们首先提供了一个混合整数非线性规划问题 (MINLP) 公式，用于在 IoV 中的能量和期限约束下进行此类任务卸载。此外，为了有效地解决公式化的 MINLP，我们将其分解为两个子问题，并设计低复杂度的能耗和任务处理延迟联合优化（JOET）算法，以优化选择决策、资源分配、卸载率和发射功率调整。我们进行了广泛的模拟实验来验证 JOET。仿真结果表明，JOET 在快速收敛和有效降低能耗和延迟方面优于许多具有代表性的现有方法。具体来说，平均能耗和任务处理延迟分别降低了15.93%和15.78%，负载均衡效率提高了10.20%。仿真结果表明，JOET 在快速收敛和有效降低能耗和延迟方面优于许多具有代表性的现有方法。具体来说，平均能耗和任务处理延迟分别降低了15.93%和15.78%，负载均衡效率提高了10.20%。仿真结果表明，JOET 在快速收敛和有效降低能耗和延迟方面优于许多具有代表性的现有方法。具体来说，平均能耗和任务处理延迟分别降低了15.93%和15.78%，负载均衡效率提高了10.20%。