We consider a system consisting of a server, which receives updates for $N$ files according to independent Poisson processes. The goal of the server is to deliver the latest version of the files to the user through a parallel network of $K$ caches. We consider an update received by the user successful, if the user receives the same file version that is currently prevailing at the server. We derive an analytical expression for information freshness at the user. We observe that freshness for a file increases with increase in consolidation of rates across caches. To solve the multi-cache problem, we first solve the auxiliary problem of a single-cache system. We then rework this auxiliary solution to our parallel-cache network by consolidating rates to single routes as much as possible. This yields an approximate (sub-optimal) solution for the original problem. We provide an upper bound on the gap between the sub-optimal solution and the optimal solution. Numerical results show that the sub-optimal policy closely approximates the optimal policy.
翻译:我们考虑一个由服务器组成的系统,该服务器根据独立的 Poisson 程序接收$N 文件的更新。 服务器的目标是通过一个由$K$缓存组成的平行网络向用户提供文件的最新版本。 我们考虑用户收到的更新成功, 如果用户收到服务器目前使用的相同文件版本。 我们为用户的信息更新度提供分析表达方式。 我们观察到,随着缓存速度的整合增加,文件的新鲜度会增加。 为了解决多缓存问题, 我们首先解决单缓存系统的辅助问题。 然后我们尽可能将速率合并到单一路径, 将这一辅助解决方案重新应用到平行缓存网络中。 这为最初的问题提供了一种近似( 亚最佳) 的解决方案。 我们为次最佳解决方案和最佳解决方案之间的差距提供了一个上层。 数字结果显示, 亚最佳政策接近最佳政策 。