Zhao, Yiming2023-03-012023-03-012018https://unbscholar.lib.unb.ca/handle/1882/13658With the high penetration rate of smart mobile devices, it is appealing to exploit device-to-device (D2D) communications for data dissemination. The popularity of social networks also offers good opportunity to expedite data dissemination. In this thesis, we focus on designing schemes to perform effective social-aware data dissemination via D2D communications in wireless networks. Specifically, we aim to (1) balance between total energy consumption and transmission finishing time of data dissemination; (2) minimize total energy consumption of data dissemination while satisfying users’ social incentive and power budget constraint; (3) maximize users’ total preferences for messages while satisfying their incentives regarding social community; and (4) exploit social-awareness and opportunistic contacts with user mobility for data dissemination. Firstly, we propose spanning tree based algorithms for seed selection and transmission scheduling with a single seed and multiple seeds. Secondly, we propose a coalitional graph game based approach, which iteratively derives a proper transmission graph to coordinate the data transmission of the base station and D2D users. Thirdly, a seed selection algorithm is proposed, which models seed selection as a weighted maximum coverage problem and an approximate algorithm is proposed to solve it. Two incentive mechanisms are further proposed respectively to incentivize seeds to forward data to the remaining target users. Fourthly, we propose a three-phase approach, which consists of one phase of seed selection and two phases of data forwarding. The performance of the proposed schemes is extensively evaluated through simulations in various scenarios. The simulation results demonstrate the effectiveness of our proposed schemes for social-aware data dissemination via D2D communications in wireless networks.text/xmlxvi, 169 pageselectronicen-CAhttp://purl.org/coar/access_right/c_abf2doctoral thesis2023-03-01Song, WeiComputer Science