Delay-Minimization and Load-Balancing Task Offloading in Mobile Edge Computing
Lianlian Yang, Xing Zhang, Junjie Li, Bo Lei · 2024
As an emerging computing paradigm, Mobile edge computing (MEC) can provide more efficient and flexible computing services for the Industrial Internet of Things (IIoT). However, due to the dispersed deployment locations of computing nodes, the varying service requirements of tasks, and the complexity of wireless transmission environments, efficient task offloading in IIoT remains an important issue. In this paper, we investigate the problem of task offloading and resource allocation in a multi-computing node collaboration scenario. A joint resource allocation, offloading nodes, and paths selection optimization (JRNP) algorithm is proposed to minimize the total task completion latency, the maximum node load, and the maximum network link load. The original problem is decomposed into sub-problems by the proposed algorithm, which are optimized alternatively. Furthermore, a heuristic algorithm is developed to address the task offloading decision sub-problem by integrating the cache constraints of the nodes, the network load, and the performance of multi-hop links. Simulation results illustrate that the proposed algorithms can effectively balance the network load and significantly reduce the total task completion delay.