Opportunistic Mobile Social Networks

The widespread availability of mobile devices along with recent advancements in networking capabilities make opportunistic mobile social networks (MSNs) one of the most promising technologies for next-generation mobile applications. Opportunistic Mobile Social Networks supplies a new perspective of these networks that can help you enhance spontaneous interaction and communication among users that opportunistically encounter each other, without additional infrastructure support.

The book explores recent developments in the theoretical, algorithmic, and application-based aspects of opportunistic MSNs. It presents the motivation behind opportunistic MSNs, describes their underpinning and key concepts, and also explores ongoing research.

• Supplies a systematic study of the constrained information flow problem
• Reviews the recent literature on social influence in complex social networks
• Presents a complete overview of the fundamental characteristics of link-level connectivity in opportunistic networks
• Explains how mobility and dynamic network structure impact the processing capacity of opportunistic MSNs for cloud applications
• Provides a comprehensive overview of the routing schemes proposed in opportunistic MSNs

Taking an in-depth look at multicast protocols, the book explains how to provide pervasive data access to mobile users without the support of cellular or Internet infrastructures. Considering privacy and security issues, it surveys a collection of cutting-edge approaches for minimizing privacy leakage during opportunistic user profile exchange.

The book concludes by introducing a framework for mobile peer rating using a multi-dimensional metric scheme based on encounter and location testing. It also explains how to develop a network emulation test bed for validating the efficient operation of opportunistic network applications and protocols in scenarios that involve both node mobility and wireless communication.

Jie Wu and Yunsheng Wang, Department of Computer and Information Sciences, Temple University.