Opportunistic Content Distribution : A System Design Approach

Sammanfattning: The penetration of smart pocket-size devices that provide constant Internet connectivity, such as mobile phones, has significantly changed the way people obtain, view and share information. Content provision is not anymore a prerogative to professionals; individuals are not solely customers, but also act as content generators and distributors. This shift in social behavior requires changes in the way information is delivered to target audiences in an efficient, interest-based and location-aware manner.This thesis explores a solution for opportunistic content distribution in a content-centric network that primarily targets content dissemination among mobile users in urban areas. The term ’opportunistic’ here refers to a concept which rejects the assumption of always-connected user devices and instead allows nodes to leverage sporadic contacts which occur when two neighbors come into direct radio communication range. Such communication mode allows data exchanges to occur in areas with little or no infrastructure; moreover, it is a potential solution for offloading the increasing traffic volumes observed by mobile operators.The contributions of this thesis lie in three areas. We first outline a general architecture and design for opportunistic content-centric networking. We implement our proposal on the Google Android platform, and provide application scenarios which illustrate the potential of mobile peer-to-peer communication. Our tests however show that energy consumption turns out to be a major issue for opportunistic networks. Therefore, our second effort is in the area of energy-efficiency. We propose a dual-radio architecture for opportunistic communication, and evaluate it through extensive simulations on realistic human mobility traces. Our final study lies in the area of content dissemination when nodes in the network act altruistically and are willing to solicit data on behalf of other participants. We propose a number of relaying and caching strategies, and evaluate them through simulations in environments that exhibit different churn levels.