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首页> 外文期刊>Wireless Communications, IEEE Transactions on >Revenue Maximization for Content-Oriented Wireless Caching Networks (CWCNs) With Repair and Recommendation Considerations
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Revenue Maximization for Content-Oriented Wireless Caching Networks (CWCNs) With Repair and Recommendation Considerations

机译：通过修复和推荐考虑的内容导向无线缓存网络（CWCN）的收入最大化

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摘要

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.
机译：为了维持面向内容的无线缓存网络（CWCN）的可靠性，由于存储实体单独不可靠，因此由于硬件错误，网络拥塞或软件更新而受到故障，因此需要考虑维修机制是必要的。同时，建议可调谐边缘缓存性能改进。在本文中，我们研究了CWCN的收入最大化问题，以及修复和推荐考虑。制定的问题是整数非凸出和非线性问题，因此难以解决。关于每个内容的存储和修复和布尔变量之间的耦合，难以从隐式加权和成本（WSC）的内在源自隐式加权和成本（WSC）。为了分析途径，开发了两步方法。具体地，我们首先探讨内容提供商之间的最佳存储和维修量，以便在成功修复存储内容的任何发生的数据损坏方面最小化WSC。提供显式实例以显示如何在我们的网络中进行编码，并在我们的网络中修复内容，因为发生错误。基于所获得的储存和维修量向量，我们解决了结果联合缓存和推荐决策问题（DMP）。更具体地，我们将DMP解耦为一对子问题，即高速缓存放置和推荐优化子问题。对于每个子问题，分别开发全局最佳和节省时间效率的次优解决方案。后来，设计了一个多功能的迭代范式，以共同做出决定。将所提出的算法的收敛性能和复杂性分析严格分析。数值结果证实了我们迭代算法的收敛性能，并说明了与各种基线方案相比的收入改进。

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