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Last decade has witnessed rapid development in wireless network. The traffic demand is driven by enormous application data that have high‐bandwidth requirement. From the operators perspective, device‐to‐device (D2D) communications are expected to provide an efficient way of offloading cellular traffic. Note that, in the high‐density gathering cases, the redundant traffic in the cellular infrastructure can be drastically offloaded by disseminating the duplicated content through D2D communications. According to this observation, we propose a novel social‐aware content dissemination scheme through D2D communications to effectively offload cellular traffic. We base our proposition on the inherent social aspects of user mobility, exploit three social structural metrics, namely, centrality, contact rate, and intercontact time. The contributions of this paper are two‐fold. First, we integrate the carry‐forward mechanism and multihop forwarding into our D2D content dissemination scheme to fully utilize the potential of D2D networks. Second, based on social pattern, we design a two‐stage social‐aware delay prediction scheme (SADP) to improve the D2D offloading utility gain. The two stages are decision‐making stage and content dissemination stage. Based on real trace data set, we evaluate the proposed method through opportunistic D2D communications, which utilizes the aforementioned metrics to enhance offloading performance and D2D transmission utility gain. By comparing with other two well‐known schemes, SA‐Epidemic and SA‐Prophet, it has been shown that our method is superior to them in terms of offloading ratio and message delay and can substantially enhance the content dissemination performance. Since SADP is designed based on a distributed insight, it ensures that it can be adaptive to mobile network. To that end, we also look forward to the future that SADP is a promising approach applied in the application scenario of 5G network.

Abstract. Cloud computing service is a new computing paradigm which consists of distributed and large scale computing resources. Effective classification managements for the resources is necessary. In this paper, we describe some concept and principle about classification, and present a classification algorithm based on non-uniform granularity. Experiments results carried on the blog posts illustrate the effectiveness of the new algorithm.