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arXiv · 1903.04709

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

Wei Du·Tao Lei·Qiang He·Wei Liu·Qiwang Lei·Hailiang Zhao·Wei Wang
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Abstract

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

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Wei Du, Tao Lei, Qiang He, Wei Liu, Qiwang Lei, Hailiang Zhao, Wei Wang. 2019-03-12. Service Capacity Enhanced Task Offloading and Resource Allocation in Multi-Server Edge Computing Environment. https://arxiv.org/abs/1903.04709

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