Edge Service Caching

Edge computing, with service caching as a key application, is essential for reducing service response time and alleviating core network traffic burden. However, due to limited edge resource capacities compared to cloud data centers, optimizing edge caching service performance presents significant challenges. This chapter examines two cases of edge service caching: static and updated. In static edge caching, a multi-edge scenario with heterogeneous resource capacities and resource type mismatches is considered. Cooperative service caching and workload scheduling are jointly optimized to minimize service response time and outsourced traffic. For updated edge caching, a single edge node with multiple mobile users is studied, focusing on jointly optimizing cached information freshness and service performance. Frequent information updates from sensors consume substantial edge bandwidth, potentially degrading mobile user service performance. Information updates and computation offloading are jointly optimized to maintain fresh information while minimizing mobile computation offloading delay and energy consumption. Both cases involve mixed-integer nonlinear optimization problems with non-polynomial complexity. This chapter analyzes problem properties and designs reduced-complexity algorithms. Simulation results demonstrate the effectiveness of the proposed algorithms.