邓晓衡

教授 博士生导师 硕士生导师

入职时间:2006-01-05

所在单位:电子信息学院

职务:院长

学历:博士研究生毕业

性别:男

联系方式:Email:dxh@csu.edu.cn

学位:博士学位

在职信息:在职

主要任职:湖南省数据传感与交换设备工程中心 主任 IEEE RS Chapter长沙 主席CCF普适计算专委 委员 CCF长沙 执委

毕业院校:中南大学

学科:信息与通信工程
计算机科学与技术

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X. Deng, H. Chen, R. Cai, et al. A knowledge-based multiplayer collaborative routing in opportunistic networks[C]//2019 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). IEEE, 2019: 16-21.

发布时间:2024-03-13

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发表刊物:2019 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)

摘要:Wireless opportunistic networks are self-organizing networks which communication devices suffer from intermittent connectivity or disconnections. Users in such networks carry the messages while they are moving, and forward them when encounter with other ones. The existing two types of routings in opportunistic networks have their own shortcomings. The forwarding-based approach can reduce cost but cannot guarantee the latency and delivery probability. The flooding-based approach have higher efficiency but consume a large amount of resource. Therefore, how to make a tradeoff between the two schemes is a challenge issue. So in this paper, we propose a new routing named Knowledge-based Multiplayer Collaborative (KBMC) Routing. In KBMC, we take some useful knowledge into consideration, such as energy consumption, delivery probability, node velocity, message carrying time. Then using the Nash bargaining game theory to construct a proper utility function in order to decide which message can delivery to which node. That can avoid random and blindfold forwarding, save the network resources. We determine the number of copies of the message by computing activity function based on the knowledge to limit flooding. Through extensive simulations, we demonstrate that our proposed KBMC performs better compared to some classical protocols in terms of overhead, average latency, delivery probability and average hops.

备注:http://faculty.csu.edu.cn/dengxiaoheng/zh_CN/lwcg/10445/content/49262.htm

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附件:

  • 47-A_Knowledge-Based_Multiplayer_Collaborative_Routing_in_Opportunistic_Networks.pdf

  • 上一条: J. Yan, Z. Kuang, F. Yang, et al. Mode selection and resource allocation algorithm in energy-harvesting D2D heterogeneous network[J]. IEEE Access, 2019, 7: 179929-179941.

    下一条: J. Luo, X. Deng, H. Zhang, et al. QoE-driven computation offloading for edge computing[J]. Journal of Systems Architecture, 2019, 97: 34-39.