Influential nodes selection to enhance data dissemination in mobile social networks: A survey. (1st November 2020)

• Record Type: Journal Article
• Authors: Tulu, Muluneh Mekonnen; Mkiramweni, Mbazingwa E.; Hou, Ronghui; Feisso, Sultan; Younas, Talha
• Is Part Of: Journal of network and computer applications. Volume 169(2020)
• Publication Date: 2020-11-01
• Subjects: Influential nodes -- Mobile social networks -- Data dissemination -- Wireless communications; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2020.102768
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: Downloading of contents on mobile devices has been increasing rapidly since the introduction of mobile communication technologies. The huge traffic load presents a significant challenge to mobile network operators. Therefore, mobile social network (MSN) has been proposed to leverage cellular links by offloading mobile traffic via device-to-device communications. To do so, applying effective algorithm to identify influential spreader in MSN is of critical importance. Recently, various techniques have been proposed, each with its particular points of interest and impediments. In this paper, we provide a comprehensive survey of different techniques used to identify influential nodes in MSNs. In this regard, we discuss the advantages and disadvantages of the methods used to select initial seeds. We also review MSNs with regard to characteristics, platforms, classification, benefits, and challenges. In addition, we review data dissemination algorithms in MSNs. We then analyze and indicate the node selection complication in future networks. Finally, we outline possible future research directions and summarize the major challenges for on-going node selection in MSNs research.