Research On The Key Thchnologies Of Social-Based Delay Tolerant Networks

With the increasing demand for wireless communications, wireless networks gradually extended to more variable topology and harsh channel environments, such as interstellar communication, wildlife monitoring, mobile social networking, and disaster relief. The common features of these applications are:stable communication between nodes can not be guaranteed, leading to the absence of end to end path between the source and sink. Delay tolerant networks, as one of the best solutions to these situations, using the "store-carry-forward" mechanism, bridge the gaps of the challenged networks at the expense of data latency and cache space for successful delivery.In recent years, the development of cross-disciplinary research pushes the research of DTN’s key technology to a new level. The spread of ubiquitous networks and Information collection technology allow the researches to realize that nodes are often attached to the individuals with self-consciousness, whose movement shows complex statistical regularity. The development of complex networks and social networks let us study the impact of social relationships between individuals on network performance from a whole new perspective. The rise of semantic web and data mining reveals the content property of data bits, allowing researchers to handle the content transfer process from a higher level. With the introduction of these new features, social-based DTNs have become a hot research.In the social-based DTNs, individuals’ preference to specific locations, relationship between individuals, community and groups, individuals’ preferences to contents can be seen as refelections of social properties. This article is based on the influence of introduction of social properties on the performance of traditional DTNs. The social properties are summarized as sociability of mobility model, heterogeneity of network topology, content of data and selfishness of data forwarding, the four of which will be investigated in this article. In the term of social mobility model, we study the cause of complex movement behavior from an evolutionary point of view. The power and resistance of movement are modeled as social gains and movement cost. By seeing the ratio of benefit and cost as the criteria ability of individuals to adapt to environmental criteria, complex social behavior emerged from generations of evolutions. A genetic algorithm based mobility model (GAMM) to generate synthetic traces for network simulation. Using "less movement cost, more social gains" as the metric of individual’s fitness to environment, Levy Walk pattern emerges from generations of evolutions, accompanied by the reduction of location entropy. To verify the scalability of GAMM, possible extension mechanisms, denoted as community model, explorers’model and transportation model, are proposed as the foundation of subsequent studies.As for the heterogeneity of network topology, firstly, we investigate the impact of the introduction of advanced nodes to DTN theoretically utilizing the similarity between the spread of infectious diseases and the dissemination of messages. The obtain the closed-form of the performance of DTN under different routing protocols using infectious disease model in complex networks and extended it to heterogeneous scenarios to study the adaptability of routing mechanism to info-station system. In order to discover and fully take advantage of high-capacity cache and high-speed link information between info-stations, Info-based MF is proposed to allow the traditional routing protocols to support info-stations, accompanied by a novel buffer control mechanism, noted as Info-based BM. Besides, a redundant copy control mechanism, denoted by Info-based CC, is proposed to utilize the high speed diffusion capacity of info-stations. The effectiveness of info-station systems and improved mechanisms are demonstrated from both theoretical analysis and simulation tests.To address the content forwarding in DTN, a content centric framework of DTN is proposed, based on the study of how to control the message spread from a high-level point of view. The architecture connects the location preference, customer’s hobby and content preference together by defining the description vector, while combining the features of the next generation network architecture and DTN. CCDTN architecture provides an application layer supporting social network file sharing, publishing/subscribing and other new business, and reserves plenty of social-property-detection interfaces to improve the scalability of the architecture. Based on CCDTN, the closeness of individuals, the similarity of messages, and the preference of nodes to consents are also introduced to improve the overall performance of DTN using social properties.The selfness is a side effect of the introduction of social properties into networks. We find out that due to the preference of individuals to locations and contents, in additional to the constraint of buffer space; the selfness in DTN shows the content selectivity. With the help of the theoretical model, the reasons for the selfish behavior of selective content are analyzed. A solution to this kind of selfness is proposed from the buffer control perspective, in which, the complementary message is defined and a selfishness restrain mechanism is introduced to improve the fairness of content spreading. The performances of CCDTN and selfishness restrain mechanism are also analyzed by simulation.