Affinity-Based Resource and Task Allocation in Edge Computing Systems

Edge computing has become a promising technology to mitigate the latency of various cloud services. Task scheduling in edge computing is challenging due to the heterogeneous devices and multiple tasks. This paper proposes an affinity-based scheduling algorithm to solve the multi-task scheduling problem with heterogeneous computing resources under edge computing. The algorithm uses a centralized scheduling strategy that takes into account the overall matching between intelligent computing tasks and heterogeneous resources from two aspects: resource affinity and system load balancing. It can adjust the weights among these aspects to meet different application requirements. The results show that the proposed algorithm can reduce the average response time by at least 10% and has a significant advantage regarding the system running time compared to the other comparative methods.