2020
DOI: 10.1109/access.2020.2979479
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Queuing Model Based Edge Placement for Work Offloading in Mobile Cloud Networks

Abstract: Recently, many useful services have been provided through wireless mobile devices. One of the critical issues is that mobile devices are generally built with limited computing capability, and thus may not be able to handle the complexity of many advanced services. This problem can be mitigated by offloading certain jobs from the mobile devices to the edge or cloud servers. However, the locations of the edge servers and the allocation of the offloading jobs to the edge servers can significantly affect the traff… Show more

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Cited by 18 publications
(10 citation statements)
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“…The number of content cached at cloudlet increases with the number of offloaded tasks increasing [46]. Content cache performance significantly impacts delay and bandwidth [47]. For example, the popular cached content in cloudlet can reduce the delay and the bandwidth usage of subsequent access to the same content.…”
Section: ) Cache Contentmentioning
confidence: 99%
“…The number of content cached at cloudlet increases with the number of offloaded tasks increasing [46]. Content cache performance significantly impacts delay and bandwidth [47]. For example, the popular cached content in cloudlet can reduce the delay and the bandwidth usage of subsequent access to the same content.…”
Section: ) Cache Contentmentioning
confidence: 99%
“…Most of the works consider the edge server placement as a placement problem by selecting K locations from N candidates with different objections. In this case, generally the edge servers are co-located with access points [8][9][10][11][12][13][14][15][16] or other network functions [17,18]. These works are marked as yes in the column of Co-located.…”
Section: B Physical Resources Placementmentioning
confidence: 99%
“…In addition, server placement and resource allocation are simultaneously considered in some works. In [15], the edge server placement and work allocation strategy is investigated with the goal of minimizing traffic load in the mobile edge networks for green communications. For joint edge server placement and application configuration, a localsearch based algorithm to minimize the service cost and opening cost of edge servers is proposed in [34].…”
Section: B Physical Resources Placementmentioning
confidence: 99%
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