Joint Optimization of Service Caching Placement and Computation Offloading in Mobile Edge Computing System
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In mobile edge computing (MEC) systems, edge service caching refers to pre-storing the necessary programs for executing certain computation tasks at MEC servers. At resource-constrained edge servers, service caching placement is in general a complicated problem that highly correlates to the offloading decisions of computation tasks. In this paper, we consider an edge server assisting a mobile user (MU) in executing a sequence of computation tasks. In particular, the MU can run its customized programs at the edge server, while the server can selectively cache the previously generated programs for future service reuse. To minimize the computation delay and energy consumption of the MU, we formulate a mixed integer non-linear programming (MINLP) that jointly optimizes the service caching placement, computation offloading, and system resource allocation. We first derive the closed-form expressions of the optimal resource allocation, and subsequently transform the MINLP into an equivalent pure 0-1 integer linear programming (ILP). To further reduce the complexity in solving a large-size ILP, we exploit the graphical structures in optimal solutions, and devise a reduced-complexity alternating optimization technique to iteratively update the caching placement and offloading decision. Simulations show that the proposed techniques achieve substantial resource savings compared to other representative benchmark methods.
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