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Game Theoretic Approaches to Massive Data Processing in Wireless Networks

Author(s): Zheng, Zijie; Song, Lingyang; Han, Zhu; Li, Geoffrey Ye; Poor, H Vincent

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dc.contributor.authorZheng, Zijie-
dc.contributor.authorSong, Lingyang-
dc.contributor.authorHan, Zhu-
dc.contributor.authorLi, Geoffrey Ye-
dc.contributor.authorPoor, H Vincent-
dc.date.accessioned2024-02-18T03:13:38Z-
dc.date.available2024-02-18T03:13:38Z-
dc.date.issued2018-02-28en_US
dc.identifier.citationZheng, Zijie, Song, Lingyang, Han, Zhu, Li, Geoffrey Ye, Poor, H Vincent. (2018). Game Theoretic Approaches to Massive Data Processing in Wireless Networks. IEEE Wireless Communications, 25 (1), 98 - 104. doi:10.1109/mwc.2018.1700175en_US
dc.identifier.issn1536-1284-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1vh5cj2s-
dc.description.abstractWireless communication networks are becoming highly virtualized with two-layer hierarchies, in which controllers at the upper layer with tasks to achieve can ask a large number of agents at the lower layer to help realize computation, storage, and transmission functions. Through offloading data processing to the agents, the controllers can accomplish otherwise prohibitive big data processing. Incentive mechanisms are needed for the agents to perform the controllers' tasks in order to satisfy the corresponding objectives of controllers and agents. In this article, a hierarchical game framework with fast convergence and scalability is proposed to meet the demand for real-time processing for such situations. Possible future research directions in this emerging area are also discussed.en_US
dc.format.extent98 - 104en_US
dc.language.isoen_USen_US
dc.relation.ispartofIEEE Wireless Communicationsen_US
dc.rightsAuthor's manuscripten_US
dc.titleGame Theoretic Approaches to Massive Data Processing in Wireless Networksen_US
dc.typeJournal Articleen_US
dc.identifier.doidoi:10.1109/mwc.2018.1700175-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

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