Search delay and success in combined social and communication networks

This paper addresses the problem of search with local information in combined social and communication networks. Social networks are modeled with short-range and long-range connections representing small-world and scale-free network characteristics. By distinguishing the delay and success probability on different social links, the end-to-end delay distribution and success probability are derived as functions of the social separation from the destination. Also, greedy routing algorithms are developed to improve the delay and chain completion success. Then, the analysis is extended to the combined social and communication networks, where wireless communication becomes the underlay to route information with the aid of social connections. The analytical results are validated via simulated search results on a combined social and communication network. Our results show how social connections can help reduce the search delay and increase the success probability in chain completion.