| Citation: | Ruyan WANG, Xuan NIE, Dapeng WU, Hongxia LI. Social Attribute Aware Task Scheduling Strategy in Edge Computing[J]. Journal of Electronics & Information Technology, 2020, 42(1): 271-278. doi: 10.11999/JEIT190301
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Unbalanced load on the edge computing server will seriously affect service capabilities, a task scheduling strategy Reinforced Q-learning-Automatic Intent Picking (RQ-AIP) for edge computing scenarios is proposed. Firstly, the load balance of the entire network is measured based on the load distribution of the server. By combining the reinforcement learning method, the appropriate edge server is matched for the task to meet the resource differentiation needs of sensor node tasks. Then, a mapping relationship between task delay and terminal transmit power is constructed to satisfy the constraints of the physical domain. Combining the social attributes of terminal, the appropriate relay terminal is continuously selected for the task to achieve the load balancing of network by terminal-assisted scheduling. Simulation results show that compared with other load balancing strategies, the proposed strategy can effectively alleviate the load between the edge servers and the traffic of the core network, reduce task processing latency.
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KUMAR K, LIU Jibang, LU Y H, et al. A survey of computation offloading for mobile systems[J]. Mobile Networks and Applications, 2013, 18(1): 129–140. doi: 10.1007/s11036-012-0368-0
|
|
ZENG Deze, GU Lin, GUO Song, et al. Joint optimization of task scheduling and image placement in fog computing supported software-defined embedded system[J]. IEEE Transactions on Computers, 2016, 65(12): 3702–3712. doi: 10.1109/TC.2016.2536019
|
|
MAO Yuyi, ZHANG Jun, and LETAIEF K B. Dynamic computation offloading for mobile-edge computing with energy harvesting devices[J]. IEEE Journal on Selected Areas in Communications, 2016, 34(12): 3590–3605. doi: 10.1109/JSAC.2016.2611964
|
|
CHEN Xu, JIAO Lei, LI Wenzhong, et al. Efficient multi-user computation offloading for mobile-edge cloud computing[J]. IEEE/ACM Transactions on Networking, 2016, 24(5): 2795–2808. doi: 10.1109/TNET.2015.2487344
|
|
MACH P and BECVAR Z. Mobile edge computing: A survey on architecture and computation offloading[J]. IEEE Communications Surveys & Tutorials, 2017, 19(3): 1628–1656. doi: 10.1109/COMST.2017.2682318
|
|
SAHNI Y, CAO Jiannong, and LEI Yang. Data-aware task allocation for achieving low latency in collaborative edge computing[J]. IEEE Internet of Things Journal, 2019, 6(2): 3512–3524. doi: 10.1109/JIOT.2018.2886757
|
|
LI Tianze, WU Muqing, ZHAO Min, et al. An overhead-optimizing task scheduling strategy for ad-hoc based mobile edge computing[J]. IEEE Access, 2017, 5: 5609–5622. doi: 10.1109/ACCESS.2017.2678102
|
|
SCHÄFER D, EDINGER J, ECKRICH J, et al. Hybrid task scheduling for mobile devices in edge and cloud environments[C]. 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, Athens, Greece, 2018: 669–674. doi: 10.1109/PERCOMW.2018.8480201.
|
|
THAM C K and CHATTOPADHYAY R. A load balancing scheme for sensing and analytics on a mobile edge computing network[C]. The 18th IEEE International Symposium on A World of Wireless, Mobile and Multimedia Networks, Macau, China, 2017: 1–9. doi: 10.1109/WoWMoM.2017.7974307.
|
|
CHEN Lixing, ZHOU Sheng, and XU Jie. Computation peer offloading for energy-constrained mobile edge computing in small-cell networks[J]. IEEE/ACM Transactions on Networking, 2018, 26(4): 1619–1632. doi: 10.1109/TNET.2018.2841758
|
|
YOUNES H, BOUATTANE O, YOUSSFI M, et al. New load balancing framework based on mobile AGENT and ant-colony optimization technique[C]. 2017 Intelligent Systems and Computer Vision, Fez, Morocco, 2017: 1–6.
|
|
MASOOD A, MUNIR E U, RAFIQUE M M, et al. HETS: Heterogeneous edge and task scheduling algorithm for heterogeneous computing systems[C]. The 17th IEEE International Conference on High Performance Computing and Communications, New York, USA, 2015: 1865–1870. doi: 10.1109/HPCC-CSS-ICESS.2015.295.
|
|
TIAN Rui, JIAO Zhenzhen, BIAN Guiyun, et al. A social-based data forwarding mechanism for V2V communication in VANETs[C]. The 10th International Conference on Communications and Networking in China, Shanghai, China, 2015: 595–599. doi: 10.1109/CHINACOM.2015.7498007.
|
|
Cisco visual networking index: Global mobile data traffic forecast update, 2015–2020[EB/OL]. https://www.cisco.com/c/dam/m/en_in/innovation/enterprise/assets/mobile-white-paper-c11-520862.pdf, 2016.
|
|
ZHAO Pengtao, TIAN Hui, QIN Cheng, et al. Energy-saving offloading by jointly allocating radio and computational resources for mobile edge computing[J]. IEEE Access, 2017, 5: 11255–11268. doi: 10.1109/ACCESS.2017.2710056
|
|
PAN Hui, CROWCROFT J, and YONEKI E. BUBBLE Rap: Social-based forwarding in delay-tolerant networks[J]. IEEE Transactions on Mobile Computing, 2011, 10(11): 1576–1589. doi: 10.1109/TMC.2010.246
|
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