3 research outputs found

    Social Data Offloading in D2D-Enhanced Cellular Networks by Network Formation Games

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    Recently, cellular networks are severely overloaded by social-based services, such as YouTube, Facebook and Twitter, in which thousands of clients subscribe a common content provider (e.g., a popular singer) and download his/her content updates all the time. Offloading such traffic through complementary networks, such as a delay tolerant network formed by device-to-device (D2D) communications between mobile subscribers, is a promising solution to reduce the cellular burdens. In the existing solutions, mobile users are assumed to be volunteers who selfishlessly deliver the content to every other user in proximity while moving. However, practical users are selfish and they will evaluate their individual payoffs in the D2D sharing process, which may highly influence the network performance compared to the case of selfishless users. In this paper, we take user selfishness into consideration and propose a network formation game to capture the dynamic characteristics of selfish behaviors. In the proposed game, we provide the utility function of each user and specify the conditions under which the subscribers are guaranteed to converge to a stable network. Then, we propose a practical network formation algorithm in which the users can decide their D2D sharing strategies based on their historical records. Simulation results show that user selfishness can highly degrade the efficiency of data offloading, compared with ideal volunteer users. Also, the decrease caused by user selfishness can be highly affected by the cost ratio between the cellular transmission and D2D transmission, the access delays, and mobility patterns

    Cross-layer optimization for cooperative content distribution in multihop device-to-device networks

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    With the ubiquity of wireless network and the intelligentization of machines, Internet of Things (IoT) has come to people's horizon. Device-to-device (D2D), as one advanced technique to achieve the vision of IoT, supports a high speed peer-to-peer transmission without fixed infrastructure forwarding which can enable fast content distribution in local area. In this paper, we address the content distribution problem by multihop D2D communication with decentralized content providers locating in the networks. We consider a cross-layer multidimension optimization involving frequency, space, and time, to minimize the network average delay. Considering the multicast feature, we first formulate the problem as a coalitional game based on the payoffs of content requesters, and then, propose a time-varying coalition formation-based algorithm to spread the popular content within the shortest possible time. Simulation results show that the proposed approach can achieve a fast content distribution across the whole area, and the performance on network average delay is much better than other heuristic approaches

    Efficient resource allocation for mobile social networks in D2D communication underlaying cellular networks

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    With the fast development of mobile terminals and wireless communication networks, mobile social networks (MSNs) play an important role in everyday lives to access social activities. However, most research on MSNs typically focuses on the relations of the users' physical location, but not make sufficient use of social ties. Consequently, in this paper, we consider a scenario of MSNs with online social networks and offline Device-to-Device (D2D) communication underlaying cellular networks, and study the problem of data dissemination to the mobile users under the constraint of limited spectrum resources. We first present a novel approach to formulate the social relationships for the offline mobiles by comparing the similarity of mobile users' social activities with the Bayesian model. And then we realize efficient data propagation using coalitional graph game. Finally, we provide simulation results to verify effectiveness of our studies. ? 2014 IEEE.EI
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