Information Search Algorithm Based On Markov Model In The Mobile Social Network

Mobile Social Network is an application of Delay Tolerant Networks. Mobile social network is a kind of interpersonal network which form in the virtual network space through mobile phone, Bluetooth, pad, etc all kinds of portable mobile devices.With the rapid development of Internet, especially with the maturity of 3G technology, the arrival of the 4G technology and the popularity of smart phones, the mobile social network users have increased year by year, and led to the rapid development of mobile Internet. In today’s society, people every day even every moment in dealing with information. The role of information in social life is becoming increasing important. Thus, how to search information quickly and efficiently is the modern talents must master skills. Recently, the research on information search algorithm is hot in DTNs.First, this thesis investigates the development of mobile social networking, the difference between the mobile social network and social network and connection, the basic characteristics of mobile social network, several common types of mobile social networks and several typical information search algorithms. Then, the paper introduces the preliminary knowledge of Markov chain, discrete time and continuous time Markov chain and Markov chain prediction method, Markov chain steady distribution and the application of Markov chain.In the end, the thesis proposes a new three-hop information search algorithm in delay-tolerant networks. In this algorithm, information search is divided into two phases, query and feedback. In the query phase, the query’s source user entrusts neighbors as query nodes to reach the purpose community and obtain the relevant information.In the feedback phase, every query node entrusts his neighbors as feedback nodes to give the information feedback to the query’s source user. We apply a semi-Markov model to predict the user’s future location. In the former phase, we select the nodes with higher query probabilities as the query delegations. Then the concept of first arrival time is defined here. In the latter phase, if the feedback probability of a neighbor node is higher than that of the query node, we will select it as a feedback node. We define this algorithm as QFD (Query and Feedback Delegation).Through simulation, the results show that QFD not only improves the information query ratio but also reduces average delay for information query compared with the existing query schemes.