期刊
IEEE TRANSACTIONS ON COMMUNICATIONS
卷 65, 期 1, 页码 444-457出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2016.2620164
关键词
Cooperative caching; local caching; wireless network; file sharing; optimization; heterogeneous file preference
资金
- National University of Singapore Research [R263-000-B46-112]
- MOE Academic Research Fund Tier 2 [MOE2016-T2-1-173]
Local caching is an effective scheme for leveraging the memory of the mobile terminal (MT) and short range communications to save the bandwidth usage and reduce the download delay in the cellular communication system. In particular, the MTs first cache in their local memories in off-peak hours and then exchange the requested files with each other in the vicinity during peak hours. However, prior works largely overlook MTs(heterogeneity in file preferences and their selfish behaviors. In this paper, we practically categorize the MTs into different interest groups according to the MTs(preferences. Each group of MTs aims to increase the probability of successful file discovery from the neighboring MTs (from the same or different groups). Hence, we define the groups(utilities as the probability of successfully discovering the file in the neighboring MTs, which should be maximized by deciding the caching strategies of different groups. By modeling MTs(mobilities as homogeneous Poisson point processes, we analytically characterize MTs(utilities in the closed form. We first consider the fully cooperative case where a centralizer helps all groups to make caching decisions. We formulate the problem as a weighted-sum utility maximization problem, through which the maximum utility tradeoffs of different groups are characterized. Next, we study two benchmark cases under selfish caching, namely, partial and no cooperation, with and without inter-group file sharing, respectively. The optimal caching distributions for these two cases are derived. Finally, numerical examples are presented to compare the utilities under different cases and show the effectiveness of the fully cooperative local caching compared with the two benchmark cases.
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