FCNS: A Fuzzy Routing-Forwarding Algorithm Exploiting Comprehensive Node Similarity in Opportunistic Social Networks

Abstract

At the dawn of big data and 5G networks, end-to-end communication with large amounts of data between mobile devices is difficult to be implemented through the traditional face-to-face transmission mechanism in social networks. Consequently, opportunistic social networks proposed that message applications should choose proper relay nodes to perform effective data transmission processes. At present, several routing algorithms, based on node similarity, attempt to use the contextual information related to nodes and the special relationships between them to select a suitable relay node among neighbors. However, when evaluating the similarity degree between a pair of nodes, most existing algorithms in opportunistic social networks pay attention to only a few similar factors, and even ignore the importance of mobile similarity in the data transmission process. To improve the transmission environment, this study establishes a fuzzy routing-forwarding algorithm (FCNS) exploiting comprehensive node similarity (the mobile and social similarities) in opportunistic social networks. In our proposed scheme, the transmission preference of the node is determined through the fuzzy evaluation of mobile and social similarities. The suitable message delivery decision is made by collecting and comparing the transmission preference of nodes, and the sustainable and stable data transmission process is performed through the feedback mechanism. Through simulations and the comparison of social network algorithms, the delivery ratio in the proposed algorithm is 0.85 on average, and the routing delay and network overhead of this algorithm are always the lowest.

An Adaptive Routing-Forwarding Control Scheme Based on an Intelligent Fuzzy Decision-Making System for Opportunistic Social Networks

“…This approach adopts a significant social feature of mobile users which is degree centrality to effectively control the number of message replications. To improve the data dissemination environment, K. Liu et al [6] proposed a fuzzy routing-forwarding approach, which utilizes a type of comprehensive node similarity that is the combination of mobile and social similarities to make an accurate decision on relay node selection and message forwarding. Borrego C et al [22] recommended a composite routing-delivery scheme, namely explore and wait, for node profile-casting in OSNs.…”

“…Moreover, the fuzzy inference logic [40], which is capable of converting numerical or textual input vectors into an evaluation fuzzy subset [29], is a novel and feasible approach in the research field of opportunistic routing and forwarding, establishing a nonlinear or linear mathematical mapping from the social features of mobile users to the metric values of data dissemination [41]. Based on that, message carriers are able to make more reasonable next-hop node selections and message delivery decisions in the OSNs [6].…”

“…In a traditional fuzzy inference system, the goal of the defuzzifier component is to convert fuzzy membership subsets and membership degrees into an accurate judgment value. As a commonly-used approach to calculate the membership degree in a traditional fuzzy inference system [6], maximum membership principle means the membership degree of each level (low, medium, and high) is equal to the maximum membership of n quantization vectors from the corresponding level. Consequently, the membership degree A m (FI node x (i)) of fuzzy input FI node x (i) for membership subset MD m (FI node x (i)) could be calculated by…”

“…Additionally, the structure in OSNs is characterized by several features such as node mobility, network topology, and social attributes [5]. As reliable and continuous data connectivity can not be available in OSNs, nodes in unpredictable online communities typically take the opportunity of encountering the peers created by their social attributes to communicate with each other at unpredictable intervals [6]. In recent years, the research interests in OSNs mainly consist of the routing-forwarding approach [5], mobility patterns [7], security with privacy [8], and data storage and management [9].…”

“…As various applicable routing-forwarding strategies [15] have been proposed to tackle the problem of data dissemination for different scenarios in OSNs, most of them make an accurate message delivery decision by comprehensively assessing reliable social information associated with nodes such as social features [6], human mobility [1], contact history [13], or level of credibility. As a general rule, the social features of humans, which can be easily extracted from portable mobile devices, are the most widely utilized metric information for relay node selection in OSNs.…”