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A Provably Efficient Online Collaborative Caching Algorithm for Multicell-Coordinated Systems

机译:一种有效的多单元协同系统在线协同缓存算法

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摘要

Caching at the base stations brings the contents closer to the users, reduces the traffic through the backhaul links, and reduces the delay experienced by the cellular users. The cellular network operator may charge the content providers for caching their contents. Moreover, content providers may lose their users if the users are not getting their desired quality of service, such as maximum tolerable delay in Video on Demand services. In this paper, we study the collaborative caching problem for a multicell-coordinated system from the point of view of minimizing the total cost paid by the content providers. We formulate the problem as an Integer Linear Program and prove its NP-completeness. We also provide an online caching algorithm that does not require any knowledge about the contents popularities. We prove that the online algorithm achieves a competitive ratio of $mathcal {O}(log (n))$ , and we show that the best competitive ratio that any online algorithm can achieve is $Omega (frac{log (n)}{log log (n)})$ . Therefore, our proposed caching algorithm is provably efficient. Through simulations, we show that our online algorithm performs very close to the optimal offline collaborative scheme, and can outperform it when contents popularities are not properly estimated.
机译:基站的缓存使内容更接近用户,减少了通过回程链路的流量,并减少了蜂窝用户所经历的延迟。蜂窝网络运营商可以向内容提供商收取用于缓存其内容的费用。此外,如果用户未获得其期望的服务质量(例如,视频点播服务中的最大可容忍延迟),则内容提供商可能会失去其用户。在本文中,我们将从最小化内容提供商支付的总成本的角度研究多单元协调系统的协作缓存问题。我们将问题表达为整数线性程序,并证明其NP完备性。我们还提供了一种在线缓存算法,该算法不需要任何有关内容受欢迎程度的知识。我们证明了在线算法达到了$ mathcal {O}(log(n))$的竞争比,并且我们证明了任何在线算法都可以达到的最佳竞争比是$ Omega(frac {log(n)} { log log(n)})$。因此,我们提出的缓存算法可证明是有效的。通过仿真,我们证明了我们的在线算法的性能非常接近最佳的离线协作方案,并且在内容流行度未得到正确估计的情况下,它的性能可能会优于该算法。

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