WCA: A Weighted Clustering Algorithm for Mobile Ad Hoc Networks
Cluster Computing
MDDV: a mobility-centric data dissemination algorithm for vehicular networks
Proceedings of the 1st ACM international workshop on Vehicular ad hoc networks
VanetMobiSim: generating realistic mobility patterns for VANETs
Proceedings of the 3rd international workshop on Vehicular ad hoc networks
Traffic-adaptive packet relaying in VANET
Proceedings of the fourth ACM international workshop on Vehicular ad hoc networks
Interactive wifi connectivity for moving vehicles
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
Cabernet: vehicular content delivery using WiFi
Proceedings of the 14th ACM international conference on Mobile computing and networking
Multiagent based information dissemination in vehicular ad hoc networks
Mobile Information Systems
ACAR: Adaptive Connectivity Aware Routing for Vehicular Ad Hoc Networks in City Scenarios
Mobile Networks and Applications
MASD: mobile agent based service discovery in ad hoc networks
HiPC'07 Proceedings of the 14th international conference on High performance computing
VWCA: An efficient clustering algorithm in vehicular ad hoc networks
Journal of Network and Computer Applications
Enhancing VANET Performance by Joint Adaptation of Transmission Power and Contention Window Size
IEEE Transactions on Parallel and Distributed Systems
A Novel Adaptive Distributed Cooperative Relaying MAC Protocol for Vehicular Networks
IEEE Journal on Selected Areas in Communications
Agent societies and social networks for ubiquitous computing
Personal and Ubiquitous Computing
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Vehicular ad hoc network (VANET) is an emerging technology which can be used in various applications such as intelligent transport technology, safety applications, etc. But one of the major issues in VANETs is how to cluster the vehicles on the road for efficient operations such as routing, mobility management and generating safety alarms. Clustering of vehicles has been widely used for routing and data dissemination in VANETs. But due to the high mobility of the vehicles/nodes on the road, it is quite difficult to find the exact route in VANETs. Keeping in view of the above issue, in this paper, we propose a new agent learning---based clustering and routing in VANETs. Agents learn from the environment in which they are deployed, and accordingly, their action performed is rewarded or penalized with certain values. Each agent performs its task in collaboration with the other agents, i.e. agents communicate with each other in collaborative manner for information sharing. The deployed agents estimate the mobility of the vehicles, and based upon their learning, clustering of vehicles is performed. An Agent Learning---based Algorithm for Clustering is proposed. The performance of the proposed scheme is evaluated using extensive simulation with respect to the various metrics such as message transmission ratio, percentage of connectivity, node participation, cluster head duration, and connectivity preservation ratio. The results obtained show that the proposed scheme is effective in performing fast clustering and converges quickly to the final solution.