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Im, Youngbin
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MoDEMS: Optimizing Edge Computing Migrations for User Mobility

DC Field Value Language Kim, Taejin ko Sathyanarayana, Sandesh Dhawaskar ko Chen, Siqi ko Im, Youngbin ko Zhang, Xiaoxi aoxi ko Ha, Sangtae ko Joe-Wong, Carlee ko 2023-01-06T02:21:43Z - 2023-01-06 ko 2023-03 ko
dc.identifier.citation IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, v.41, no.3, pp.675 - 689 ko
dc.identifier.issn 0733-8716 ko
dc.identifier.uri -
dc.description.abstract Edge computing capabilities in 5G wireless networks promise to benefit mobile users: computing tasks can be offloaded from user devices to nearby edge servers, reducing users’ experienced latencies. Few works have addressed how this offloading should handle long-term user mobility: as devices move, they will need to offload to different edge servers, which may require migrating data or state information from one edge server to another. In this paper, we introduce MoDEMS, a system model and architecture that provides a rigorous theoretical framework and studies the challenges of such migrations to minimize the service provider cost and user latency. We show that this cost minimization problem can be expressed as an integer linear programming problem, which is hard to solve due to resource constraints at the servers and unknown user mobility patterns. We show that finding the optimal migration plan is in general NP-hard, and we propose alternative heuristic solution algorithms that perform well in both theory and practice. We finally validate our results with real user mobility traces, ns-3 simulations, and an LTE testbed experiment. Migrations reduce the latency experienced by users of edge applications by 33% compared to previously proposed migration approaches. ko
dc.language 영어 ko
dc.publisher Institute of Electrical and Electronics Engineers ko
dc.title MoDEMS: Optimizing Edge Computing Migrations for User Mobility ko
dc.type ARTICLE ko
dc.identifier.scopusid 2-s2.0-85115363983 ko
dc.identifier.wosid 000934107300008 ko
dc.type.rims ART ko
dc.identifier.doi 10.1109/IWQOS52092.2021.9521352 ko
dc.identifier.url ko
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