Enhanced Social-based Routing Protocols in Opportunistic Mobile Social Network - Mohamad, Alrfaay (Universiti Malaysia Sarawak (UNIMAS), 2020)
An Opportunistic Network (OppNet) is a new paradigm of the Delay Tolerant Network (DTN). The dynamic topology of the OppNet degrades the efficiency of data dissemination. To cope with this challenge, exploiting the social features of the mobile users is a strong and effective research trend for efficient routing in OppNet. Opportunistic Mobile Social Networks (OMSN) has emerged as a new communication paradigm of OppNet, where social information is exploited for data dissemination purposes. The challenges are which social features to be exploited, how to combine the social features with other routing-related factors, and how multiple social features can be integrated to improve routing performance in OMSN. In this thesis, social information is combined with the Epidemic protocol to grab the advantages of Epidemic protocol in terms of high delivery ratio and low latency, and to decrease the overhead by exploiting social information. Messages’ Time to Live (TTL) is decreased according to nodes' social degree when forwarding it. Experimental results show that the proposed protocol, Epidemic Social-based protocol (EpSoc), decreases the delivery overhead ratio and average hop count significantly. The reduction is up to 72%, 44% in overhead ratio and up to 41%, 56% in average hop count compared with Epidemic and Bubble Rap respectively. In addition, this thesis investigates exploiting the similarity between the users' social characteristics and the regularity of the people’s social behaviour in daily life to improve routing performance in OMSN. Based on this, a Social-based Ranking protocol (SOR) is proposed. It ranks social characteristics according to nodes’ social activity and exploits them to forward messages in OMSN. SOR has the highest delivery ratio compared with the benchmark protocols; the increase is up to 150%, 24%, and 65% compared with Epidemic, PRoPHET, and Bubble Rap respectively for the scenarios of low buffer size and high TTL value. SOR also decreases overhead ratio with 75%, 45%, and decreases the average hop count with 64% and 23% on average compared with Epidemic and PRoPHET respectively, while it has a slightly higher average hop count compared with Bubble Rap. Finally, this thesis explores exploiting multiple social metrics with the consideration of the mutual impacts and the correlation among them. Multipliable Social Metrics-based (MSM) routing protocol is proposed based on this idea. In MSM, social activity, similarity, and degree centrality and their mutual impacts are utilized to form the message's forwarding decision. Results show that MSM outperforms the benchmark protocols in terms of overhead ratio and average hop counts, and has competitive achievements regarding delivery ratio and average latency. The reduction in overhead ratio is ,on average, 95%, 93%, and 90% , and up to 81%, 60%, and 42% in average hop counts compared with Epidemic, PRoPHET, and Bubble Rap respectively. According to this study, social information plays a critical role in enhancing the efficiency of information sharing in the new emerged communication paradigms such as OMSN and device-to-device (D2D) networks.