Social-Driven Information Dissemination for Mobile Wireless Sensor Networks

• Main Authors: Basim MAHMOOD, Marcello TOMASINI, Ronaldo MENEZES
• Format: Article
• Language: English
• Published: IFSA Publishing, S.L. 2015-06-01
• Series: Sensors & Transducers
• Subjects: Social Networks; Social Network of Sensors; Human Mobility; Information Dissemination.
• Online Access: http://www.sensorsportal.com/HTML/DIGEST/june_2015/Vol_189/P_2666.pdf
• ISSN: 2306-8515; 1726-5479

As we move into the so-called Internet of Things (IoT), the boundary between sensor networks and social networks is likely to disappear. Moreover, previous works argue that mobility in sensor networks may become a consequence of human movement making the understanding of human mobility crucial to the design of sensor networks. When people carry sensors, they become able to use concepts from social networks in the design of sensor network infrastructures. However, to this date, the utilization of social networks in designing protocols for wireless sensor networks has not received much attention. In this paper, we focus on the concept of information dissemination in a framework where sensors are carried by people who, like most of us, are part of a social network. We propose two social-based forwarding approaches for what has been called Social Network of Sensors (SNoS). To this end, we exploit two important characteristics of ties in social networks, namely strong ties and weak ties. The former is used to achieve rapid dissemination to nearby sensors while the latter aims at dissemination to faraway sensors. We compared our results against two well-known approaches in the literature: Epidemic and PRoPHET protocols. We evaluate our approaches according to four criteria: information-dissemination distance, information-dissemination coverage area, the number of messages exchanged, and information delivery time. We believe this is the first work that investigates the issues of information-dissemination distance and information-dissemination coverage area using an approach inspired on social network concepts.