Spray and wait: an efficient routing scheme for intermittently connected mobile networks
Proceedings of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking
Distributed community detection in delay tolerant networks
Proceedings of 2nd ACM/IEEE international workshop on Mobility in the evolving internet architecture
Searching for content in mobile DTNs
PERCOM '09 Proceedings of the 2009 IEEE International Conference on Pervasive Computing and Communications
IEEE/ACM Transactions on Networking (TON)
Peoplerank: social opportunistic forwarding
INFOCOM'10 Proceedings of the 29th conference on Information communications
Power Law and Exponential Decay of Intercontact Times between Mobile Devices
IEEE Transactions on Mobile Computing
Overlapping communities in dynamic networks: their detection and mobile applications
MobiCom '11 Proceedings of the 17th annual international conference on Mobile computing and networking
BUBBLE Rap: Social-Based Forwarding in Delay-Tolerant Networks
IEEE Transactions on Mobile Computing
Exploiting Friendship Relations for Efficient Routing in Mobile Social Networks
IEEE Transactions on Parallel and Distributed Systems
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The increase in the size of mobile cloud as well as the volume of information necessitates efficient search mechanisms for finding the searched information or the target node. In this paper, we focus on search mechanisms to retrieve information from within a mobile cloud in which nodes have intermittent connectivity and hence operate on a store-carry-forward manner. We design an opportunistic search scheme in which the searching node spreads a limited number of replicas of the query to the nodes it meets and these nodes, so called seekers, perform the search on behalf of the searching node. We assume that nodes are grouped into communities based on their interest profiles, and seekers use this community information to forward the data and the query to the right community - the community that is more likely to store the searched content. Since people store and search for similar information in the scope of their interest, the nodes in the same community as the searching node have higher probability to store the searched content. We model this seeker-assisted search scheme as a continuous time Markov process and analyze its performance under various inter-community/intra-community meeting rate, number of replicas, and network population. Our analysis shows that seeker-assisted search achieves a good balance between the search response time and search cost compared to the two extremes of epidemic search and direct delivery search.