2017/03/30 by Xu Chen, Lingjun Pu, Chen, Xu +7
Computer Science · Engineering · #FOS: Computer and information sciences #IoT and Edge/Fog Computing #Mobile Crowdsensing and Crowdsourcing #Molecular Communication and Nanonetworks #Networking and Internet Architecture (cs.NI)
paper · pdf · doi:10.48550/arxiv.1703.10340
openalex publication_date 2017/03/30 · openalex created_date 2019/06/27 · openalex updated_date 2026/07/28
In this article we propose a novel Device-to-Device (D2D) Crowd framework for 5G mobile edge computing, where a massive crowd of devices at the network edge leverage the network-assisted D2D collaboration for computation and communication resource sharing among each other. A key objective of this framework is to achieve energy-efficient collaborative task executions at network-edge for mobile users. Specifically, we first introduce the D2D Crowd system model in details, and then formulate the energy-efficient D2D Crowd task assignment problem by taking into account the necessary constraints. We next propose a graph matching based optimal task assignment policy, and further evaluate its performance through extensive numerical study, which shows a superior performance of more than 50% energy consumption reduction over the case of local task executions. Finally, we also discuss the directions of extending the D2D Crowd framework by taking into variety of application factors.