Six-factors Score-based Match-making Based on Priority and Preemption for Resource Allocation in Edge Computing

The Bao Bui, Aly Sakr, Juan Castrillon, Rolf Schuster · 2021

The growth of Internet of Things (IoT) devices and their unpredictable needs make resource allocation of edge computing systems challenging. A good edge computing system or platform should not only solve the resources allocation challenge to balance loads among edge servers with the best quality of service for all clients but also deal with emergencies where high-priority clients need access to the edge. This paper presents an improvement of an existing algorithm Score-Based Match-Making (SBMM) to solve the aforementioned challenge. A six-factors score-based Match-Making algorithm is proposed to tackle priority-related challenges in resource allocation with a preemption factor to deal with emergency problems. An evaluation of our own orchestration platform (Edge Diagnostics Platform) under different scenarios and algorithms, namely random, naive, SBMM is presented. The experimental studies highlight the improvement in clients' priority distribution in edge servers and solve the problem of emergency clients with preemption. The simulation results verify that the proposed algorithm is significantly better than the original algorithm in the context of prioritized deployments.

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