Abstract
Recently, with the development of big data and 5G networks, the number of intelligent mobile devices has increased dramatically, therefore the data that needs to be transmitted and processed in the networks has grown exponentially. It is difficult for the end-to-end communication mechanism proposed by traditional routing algorithms to implement the massive data transmission between mobile devices. Consequently, opportunistic social networks propose that the effective data transmission process could be implemented by selecting appropriate relay nodes. At present, most existing routing algorithms find suitable next-hop nodes by comparing the similarity degree between nodes. However, when evaluating the similarity between two mobile nodes, these routing algorithms either consider the mobility similarity between nodes, or only consider the social similarity between nodes. To improve the data dissemination environment, this paper proposes an effective data transmission strategy (MSSN) utilizing mobile and social similarities in opportunistic social networks. In our proposed strategy, we first calculate the mobile similarity between neighbor nodes and destination, set a mobile similarity threshold, and compute the social similarity between the nodes whose mobile similarity is greater than the threshold. The nodes with high mobile similarity degree to the destination node are the reliable relay nodes. After simulation experiments and comparison with other existing opportunistic social networks algorithms, the results show that the delivery ratio in the proposed algorithm is 0.80 on average, the average end-to-end delay is 23.1% lower than the FCNS algorithm (A fuzzy routing-forwarding algorithm exploiting comprehensive node similarity in opportunistic social networks), and the overhead on average is 14.9% lower than the Effective Information Transmission Based on Socialization Nodes (EIMST) algorithm.
Highlights
In recent years, the deployment of mobile devices has become increasingly extensive, and the massive data transmission requirements of mobile devices has put increasing pressure on infrastructure.Emerged from mobile ad hoc networks (MANETs) [1] and the Social Network Service (SNS) [2], opportunistic social networks (OSNs) [3,4,5] have been regarded as a complex intermittently connected network architecture, which have been identified as a promising network model to improve network transmission reliability and dissemination environment
The remainder of the paper is organized as follows: In Section 2, we introduce the previous related work; The MSSN data transmission strategy will be discussed in Section 3; in Section 4, we evaluate the performance of our algorithms through extensive simulation results
The neighbor nodes in the opportunistic social network are relative to similarity between two nodes by judging how many common neighbor nodes exist between nodes
Summary
The deployment of mobile devices has become increasingly extensive, and the massive data transmission requirements of mobile devices has put increasing pressure on infrastructure. The store-carry-forward mechanism can effectively alleviate network pressure and provide users, with a more comfortable and convenient network service experience It is extremely important for mobile nodes carrying data in OSNs to select relay nodes to perform effective data forwarding process. Various routing and forwarding algorithms have been proposed to deal with data dissemination problems in different scenarios Most of these algorithms only consider a single factor, either the mobile similarity [17] between nodes or the social similarity [18] of nodes. To tackle the above-mentioned problems, this work proposes an effective data transmission strategy (MSSN) utilizing mobile and social similarities in opportunistic social networks This scheme evaluates the mobile similarity and social similarity between nodes by using their moving trajectories, the number of common neighbor nodes and their social attributes. The conclusion of the paper is shown in the last section
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