Revenue Maximization for Content-Oriented Wireless Caching Networks (CWCNs) with Repair and Recommendation Considerations

Yaru Fu, Quan Yu, Tony Q.S. Quek, Wanli Wen

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

To maintain reliability of content-oriented wireless caching networks (CWCNs), repair mechanism is of necessity to be considered due to the natural that storage entities are individually unreliable and thus subject to failure on account of hardware error, network congestion or software updating. Meanwhile, recommendation is tunable for edge caching performance improvement. In this paper, we study the revenue maximization problem for CWCNs with both repair and recommendation considerations. The formulated problem is an integer non-convex and non-linear problem, and thus is difficult to be solved. The difficulties are intrinsically derived from the implicit weighted sum costs (WSCs) as regards storage and repair of each content and the coupling among the Boolean variables. For the sake of analytical tractability, a two-step methodology is developed. Specifically, we first explore the optimal storage and repair amount among the content providers to minimize the WSCs in terms of successfully fixing any occurred data corruption for the stored contents. Thereof, an explicit instance is provided to show how the contents can be coded, stored and then repaired in our network given that an error occurs. Based on the obtained storage and repair amount vectors, we solve the resultant joint caching and recommendation decision making problem (DMP). To be more specific, we decouple the DMP into a pair of subproblems, namely a cache placement and a recommendation optimization subproblems. For each subproblem, a globally optimal and a time-efficient suboptimal solutions are developed, respectively. Later, a versatile iterative paradigm is devised to do the decision making jointly. The convergence performance and the complexity analysis of the proposed algorithms are rigorously analyzed. Numerical results confirm the convergence performance of our iterative algorithms and illustrate their revenue improvements compared to various baseline schemes.

Original languageEnglish
Article number9206079
Pages (from-to)284-298
Number of pages15
JournalIEEE Transactions on Wireless Communications
Volume20
Issue number1
DOIs
Publication statusPublished - 2021 Jan

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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