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Modeling of Epidemic Information Dissemination for MSNs

In this chapter, the modeling of epidemic information dissemination in MSNs is discussed. We introduce two new elements, i.e., pre-immunity and immunity. Then, we study the features of information dissemination for users. Based on the process of the epidemic information dissemination, a novel dissemination mechanism is proposed with four dissemination rules. An analytical model is also developed through ordinary differential equations to mimic epidemic information dissemination.

Information Dissemination in MSNs

The MSNs [1-4] enable users to exchange and share information via opportunistic peer-to-peer links with short range wireless communication techniques, such as Wi-Fi and Bluetooth [5-8]. With the opportunistic links in MSNs, users adopt store- carry-and-forward mode to disseminate information [9, 10]. When a user moves to the communication coverage area of others, the information can be successfully forwarded; when the user is out of the communication range of others, this user stores and carries the information and waits for the next connection with others.

As users receive information by employing opportunistic contacts (as shown in Fig. 2.1), the user’s mobility has a significant impact on information dissemination [11, 12]. However, since the opportunistic peer-to-peer links cannot be easily observed, the procedures of information dissemination are unpredictable. Therefore, a model to analyze the epidemic information dynamics of MSNs is necessary to efficiently capture the realistic features of information dissemination in MSNs.

Although many research studies [13-15] have investigated the analytical model for wireless networks, most of them assume that the transmission path between two nodes is stable so that they cannot be directly applied to MSNs. Moreover, the social ties among users have impacts on information dissemination in MSNs. For example, a © Springer International Publishing AG 2016

Z. Su et al., Modeling and Optimization for Mobile Social Networks, DOI 10.1007/978-3-319-47922-4_2

Epidemic information dissemination among users

Fig. 2.1 Epidemic information dissemination among users

user may be willing to help forward information from his friends or the users with high social ties instead of a stranger. It is preferred to select social friends to store-carry- and-forward the information other than the users with high mobility. Therefore, how to balance the social tie and mobility becomes a challenging issue for information dissemination in MSNs. In addition, the user’s interests may also vary during the information dissemination in MSNs. For example, in a local commercial street, a user has interests in food or Italian restaurant during the lunch time, while he may be interested in clothes and shoes after lunch. As the user changes his interests or social preferences, he would be willing to forward the current interested information rather than the one with old interests. Therefore, it is very important to develop an analytical model to investigate information dissemination in MSNs with the consideration of social impacts.

 
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