Abstract
An opportunistic network is a special type of wireless mobile ad hoc network that does not require any infrastructure, does not have stable links between nodes, and relies on node encounters to complete data forwarding. The unbalanced energy consumption of ferry nodes in an opportunistic network leads to a sharp decline in network performance. Therefore, identifying the ferry node group plays an important role in improving the performance of the opportunistic network and extending its life. Existing research studies have been unable to accurately identify ferry node clusters in opportunistic networks. In order to solve this problem, the concepts of k-core and structural holes have been combined, and a new evaluation indicator, namely, ferry importance rank, has been proposed in this study for analyzing the dynamic importance of nodes in a network. Based on this, a ferry cluster identification model has been designed for accurately identifying the ferry node clusters. The results of the simulations conducted for verifying the performance of the proposed model show that the accuracy of the model to identify the ferry node clusters is 100%.
Highlights
An opportunistic network is a type of wireless mobile ad hoc network, which does not require a complete link between nodes and can realize communication between disconnected subdomains [1]
Based on the importance of structural holes and k-cores, an ferry importance rank (FIR) indicator has been proposed in this study for evaluating the importance of nodes in the opportunistic network
Compared to the VC model based on the betweenness centrality index, the FIRbased model is able to accurately identify the ferry node groups in a variety of application scenarios
Summary
An opportunistic network is a type of wireless mobile ad hoc network, which does not require a complete link between nodes and can realize communication between disconnected subdomains [1]. Kitsak et al [27] proposed a node importance evaluation indicator based on the importance of the position of the node in the entire network and used the number of cores obtained by k-core decomposition as the basis for judging the importance of the node This method is only suitable for complex networks with a static topology and cannot be used in opportunistic networks with constantly changing topologies. In a changing and multipropagation source opportunistic network, the dynamic importance of nodes can be accurately evaluated by the proposed FIR indicator On this basis, an FIR-based opportunistic network ferry node cluster identification model has been developed, which divides the operation information of the network over a period of time into equal-length time slices. The nodes that can have significant influence are calculated on the basis of the FIR indicator, and the ferry node cluster in the network is selected according to the nodes selected in the different time slices
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
