Vehicular edge computing (VEC) has become a promising solution in electric vehicle (EV) utilization. However, the uneven geographical distribution of service requests may lead to load imbalances among edge servers in different clusters. Thus, the integration of task offloading (TO) and resource allocation (RA) is pivotal for achieving optimal performance in edge computing systems. In this study, we explore an efficient collaborative scheme for task offloading and resource allocation across multiple edge network areas. Initially, we model the Multi-Edge System Delay (MESD) by considering the average end-to-end delay in the system. Subsequently, we introduce the concept of request redistribution using a load-balancing approach to simplify the joint TO & RA problem into a manageable RA problem. Our algorithm mathematically formulates the MESD model and employs a heuristic method to address the formulated problem. Finally, we have compared our proposed work with several baselines and the results confirm the effectiveness of the proposed mechanism.
Collaborative Vehicular Edge Computing Design for Delay-Sensitive Applications
2024-06-24
428490 byte
Conference paper
Electronic Resource
English