Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/96185
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electronic and Information Engineering | en_US |
dc.creator | Mao, Y | en_US |
dc.creator | You, C | en_US |
dc.creator | Zhang, J | en_US |
dc.creator | Huang, K | en_US |
dc.creator | Letaief, KB | en_US |
dc.date.accessioned | 2022-11-11T07:56:54Z | - |
dc.date.available | 2022-11-11T07:56:54Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/96185 | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.rights | © 2017 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. | en_US |
dc.rights | This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. | en_US |
dc.rights | The following article Y. Mao, C. You, J. Zhang, K. Huang and K. B. Letaief, "A Survey on Mobile Edge Computing: The Communication Perspective," in IEEE Communications Surveys & Tutorials, vol. 19, no. 4, pp. 2322-2358, Fourthquarter 2017 is available at https://doi.org/10.1109/COMST.2017.2745201. | en_US |
dc.subject | Computation offloading | en_US |
dc.subject | Fog computing | en_US |
dc.subject | Green computing | en_US |
dc.subject | Mobile cloud computing | en_US |
dc.subject | Mobile edge computing | en_US |
dc.subject | Resource management | en_US |
dc.title | A survey on mobile edge computing : the communication perspective | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 2322 | en_US |
dc.identifier.epage | 2358 | en_US |
dc.identifier.volume | 19 | en_US |
dc.identifier.issue | 4 | en_US |
dc.identifier.doi | 10.1109/COMST.2017.2745201 | en_US |
dcterms.abstract | Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized mobile cloud computing toward mobile edge computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also discuss a set of issues, challenges, and future research directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | IEEE communications surveys and tutorials, 2017, v. 19, no. 4, p. 2322-2358 | en_US |
dcterms.isPartOf | IEEE communications surveys and tutorials | en_US |
dcterms.issued | 2017 | - |
dc.identifier.scopus | 2-s2.0-85028734877 | - |
dc.identifier.eissn | 1553-877X | en_US |
dc.description.validate | 202211 bckw | en_US |
dc.description.oa | Author’s Original | en_US |
dc.identifier.FolderNumber | RGC-B3-1033 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | Green (AO) | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Survey_Mobile_Edge.pdf | Preprint version | 4.06 MB | Adobe PDF | View/Open |
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