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.

Release time:2024-03-13

Journal: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)

Abstract: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.

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

Translation or Not:no