Effective Social-Context based Message Delivery using ChitChat in Sparse Delay Tolerant Networks

Delay tolerant networks (DTNs) have garnered much interest with the wide-spread adoption of portable smart devices capable of wirelessly connecting with one another, thus enabling the formation of a network for opportunistic data dissemination. This type of network is useful in a variety of applications where other form of network communication strategies are unavailable, such as an on-the-ground tactical military network in an active battlefield or an emergency network formed immediately after a catastrophic disaster. DTNs also provide opportunities for various other interesting applications such as location-based social networking, interests-based data dissemination, and geolocal advertising. One persistent challenge for DTNs is achieving sufficient message delivery due to the dynamic, unpredictable, and opportunistic nature of inter-device connections; this challenge is exacerbated when such connections are sparsely available. In this paper, a novel social-context based message routing system, called ChitChat, is proposed with the focus on message delivery through sparsely-connected DTNs. ChitChat is a hybrid geographic/data-centric routing system designed to exploit each user\u27s social (or mission) interests to opportunistically learn of multi-hop paths through the network, and to derive the social semantics of geographic locations using user travel itineraries and multi-hop social relationships. In turn, this information is used to make distributed routing decisions based on the likelihood an encountered node will connect with others capable of successfully delivering a message. An analysis of network sparsity is conducted against five real-world datasets. Through simulations using the two highest-sparsity real-world datasets, ChitChat is capable of achieving more successful deliveries against three recent state-of-the-art DTN routing schemes while incurring lower costs against flooding