Routing Mechanism In Opportunistic Social Networks Based On Expectation

Opportunistic network was a self-organizing and delay tolerant network, the source node that produced and carried a copy of messages completed message delivery when node meet and entered each other’s communication range so that message can reach destination node smoothly. With the rapid spread of the terminal mobile equipment, message transmission between people with mobile devices was more and more popular. Different with ordinary mobile nodes in opportunistic networks, human movement had a certain social purpose, the research to opportunistic network composed of people gradually evolved specialized research direction for opportunistic social networks. Because of opportunistic social networks without fixed network infrastructure, it had strong flexibility, it also had been widely used in communication on campus, vehicle network and switching network by hand, so it had wide application prospect and profound. Based on analysis to mobile characteristics of social node in realistic opportunistic social networks scenarios, message routing mechanism was designed based on similarity between relay nodes and destination node. This paper presented two kinds of routing mechanism in opportunistic social networks based expectation:1) Aiming at the problem that objectives and repetitive characteristics of mobility was less considered in campus opportunistic network, routing mechanism based on expected behavior in opportunistic social networks combined forecasting method was proposed. Domain of interest in campus that node moved to was inducted, prediction model of length of time that node stayed in domain of interest was established based on knowledge of human dynamics, expected time was processed with normalization method, time ratio was used to measured expected degree which node visited each domain of interest, expected mobile behavior was described by vector. Based on optimal selection method, message was delivered to relay node which expected mobile behavior was similar to destination node, until destination node. Results of the simulation indicated that forwarding routing can improve routing performance and reduce network overhead in campus opportunistic network with large node density and limited buffer.2) The characteristics of multi regions caused the uncertainty of mobile behavior of node, so it was difficult to accurately predict the domain of interest that node stayed at current time window, routing mechanism based on interest expectation in campus opportunistic network was presented. Probability that node moved to domain of interest was predicted based on history records of mobile behavior access to each domain of interest on campus,the Beta distribution, Bayesian estimation method and interest factor models of human dynamics, then "certainty" moving behavior was measured by vector consisted of probability in order to describe mobile behavior of node in campus. Message was transferred from source node to destination node based on computing matching values between relay nodes and destination node. The results shown that forwarding routing had certain advantages in transmission success rate compared with routing mechanism based on expected mobile behavior in opportunistic social networks.Simulation experiments shown that due to differences in expectation method, the two routing mechanism reflected the respective advantage in different routing performance evaluation in the same campus scene, routing mechanism need to be improved constantly, message routing mechanism in campus opportunistic network that comprehensive evaluation were better still need to be designed.