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An edge computing environment features multiple edge servers and multipleservice clients. In this environment, mobile service providers can offloadclient-side computation tasks from service clients' devices onto edge serversto reduce service latency and power consumption experienced by the clients. Acritical issue that has yet to be properly addressed is how to allocate edgecomputing resources to achieve two optimization objectives: 1) minimize theservice cost measured by the service latency and the power consumptionexperienced by service clients; and 2) maximize the service capacity measuredby the number of service clients that can offload their computation tasks inthe long term. This paper formulates this long-term problem as a stochasticoptimization problem and solves it with an online algorithm based on Lyapunovoptimization. This NP-hard problem is decomposed into three sub-problems, whichare then solved with a suite of techniques. The experimental results show thatour approach significantly outperforms two baseline approaches.

Service Capacity Enhanced Task Offloading and Resource Allocation in Multi-Server Edge Computing Environment