COOPER-SCHED: A Cooperative Scheduling Framework for Mobile Edge Computing with Expected Deadline Guarantee

While mobile edge computing (MEC) holds promise to enhance users' mobile experiences, building a scheduling framework to make full use of MEC capabilities is challenging. When involving quality of service (QoS) in MEC, the problem becomes even harder. In this work, we focus on QoS guaranteed sc...

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Veröffentlicht in:IEEE transactions on parallel and distributed systems 2024, p.1-1
Hauptverfasser: Liu, Chubo, Li, Kenli, Liang, Jie, Li, Keqin
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Sprache:eng
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Zusammenfassung:While mobile edge computing (MEC) holds promise to enhance users' mobile experiences, building a scheduling framework to make full use of MEC capabilities is challenging. When involving quality of service (QoS) in MEC, the problem becomes even harder. In this work, we focus on QoS guaranteed scheduling in MEC with a cloudlet, which is a small cloud center deployed at the wireless access point (AP) to serve nearby mobile devices. There are multiple mobile devices (MDs) and each one is associated with a job to be offloaded to the AP and executed in the cloudlet. Each job is associated with a block of input data, an execution workload, and a QoS requirement, i.e., a time deadline that the job is expected to be completed before it. Our goal is to find an efficient schedule, which involves radio access network (RAN) allocation and job mapping on multiple heterogeneous servers, such that the number of jobs whose deadlines are satisfied is maximized. The problem is proved to be NP-hard. To solve the problem, we propose an extended marriage algorithm (EMA) by adapting the stable marriage game, for job mapping in the cloudlet. Based on this algorithm, we further implement a cooperative game based scheduling method COOPER-SCHED, which also involves RAN allocation. We perform extensive random experiments and compare it with three common heuristics in scheduling literature. The results show that COOPER-SCHED can find better schedules and shows more stability, i.e., suffering less impacts from RAN allocation, than others in MEC.
ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2019.2921761