Social-Aware Collaborative Caching Based on User Preferences for D2D Content Sharing

• Can Zhang,
• Dan Wu,
• Liang Ao,
• Meng Wang,
• Yueming Cai,

Vol. 14, No. 3, March 31, 2020
10.3837/tiis.2020.03.009, Download Paper (Free):

• D2D content sharing
• user preferences
• social aware collaborative caching
• submodular function
• greedy algorithm

Abstract

With rapid growth of content demands, device to device (D2D) content sharing is e x ploited to effectively improve t he service quality of users. Considering the limited storage space and various content demands of users, caching schemes are significant. However, most of them ignore the influence of the asynchronous content reuse and the selfishness of users. In this wor k, the user preferences are defined by exploiting the user oriented content popularity and the current caching situation, and further, we propose the social aware rate, which compr e- hensively reflects the achievable contents download rate affected by the so cial ties, the caching indicators, and the user preferences. Guided by this, we model the collaborative caching problem by making a trade off between the redundancy of caching contents and the cache hit ratio, with the goal of maximizing the sum of social aware rate over the constraint of limited storage space. Due to its intractability, it is computationally reduced to the maxim i- zation of a monotone submodular function, subject to a matroid constraint. Subsequently, two social aware collaborative caching a lgorithms are designed by leveraging the standard and continuous greedy algorithms respectively, which are proved to achieve different approxim a- tion rati os in unequal polynomial time. We present the simulation results to illustrate the performance of our s chemes.

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