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dc.contributor.author Kim, Yeongjin -
dc.contributor.author Choi, Pyeongjun -
dc.contributor.author Lim, Jeong-A -
dc.contributor.author Kwak, Jeongho -
dc.date.accessioned 2023-10-23T18:10:19Z -
dc.date.available 2023-10-23T18:10:19Z -
dc.date.created 2023-06-01 -
dc.date.issued 2023-10 -
dc.identifier.issn 0018-9545 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/46542 -
dc.description.abstract Flexible resource management can be facilitated by recent drastic advances in software-defined networking (SDN) and network function virtualization (NFV) technologies. Most of recent studies on resource management have mainly focused on the independent optimization of network function and computing function on top of a single-layer SDN architecture. In this paper, we focus on networking and processing resource orchestration to enhance the performance of network/computing functions in a hierarchical cloud-edge-radio 5G network architecture. Specifically, we propose a dynamic resource management algorithm, namely RACER, to process network/computing functions by opportunistically exploiting a tradeoff between the characteristics of the cloud and edge with respect to the amount of available resources and transmission delay. Herein, we decompose an original long-term problem including complex decisions in all network layers (that is, cloud, edge, and radio) into spatio-temporal subproblems without loss of optimality by leveraging Lyapunov optimization. Then, we derive the RACER algorithm to find the decisions in each layer and each time slot. This online-fashioned algorithm is pragmatic because it not only exploits information obtained from instantaneous time slots, but also operates in a distributed manner with small message exchanges between the different layers. Moreover, we demonstrate the excellent performance improvement of the proposed dynamic and holistic RACER algorithm compared to static and independent policies in the 5G network environment. © IEEE. -
dc.language English -
dc.publisher Institute of Electrical and Electronics Engineers Inc. -
dc.title Network-Compute Co-Optimization for Service Chaining in Cloud-Edge-Radio 5G Networks -
dc.type Article -
dc.identifier.doi 10.1109/TVT.2023.3271693 -
dc.identifier.scopusid 2-s2.0-85159810047 -
dc.identifier.bibliographicCitation IEEE Transactions on Vehicular Technology, v.72, no.10, pp.13374 - 13391 -
dc.description.isOpenAccess FALSE -
dc.subject.keywordAuthor Resource orchestration -
dc.subject.keywordAuthor SDN/NFV -
dc.subject.keywordAuthor service chaining -
dc.subject.keywordAuthor 5G -
dc.subject.keywordAuthor cloud -
dc.subject.keywordAuthor edge -
dc.subject.keywordAuthor radio access networks -
dc.subject.keywordPlus PLACEMENT -
dc.subject.keywordPlus POWER -
dc.subject.keywordPlus ALLOCATION -
dc.citation.endPage 13391 -
dc.citation.number 10 -
dc.citation.startPage 13374 -
dc.citation.title IEEE Transactions on Vehicular Technology -
dc.citation.volume 72 -
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Department of Electrical Engineering and Computer Science Intelligent Computing & Networking Laboratory 1. Journal Articles

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