Multi-Client File Download Time Reduction from Cloud/Fog Storage Servers

Abstract

We study the problem of reducing the download time of multiple files requested by multiple clients from multiple cloud/fog storage servers. Given possible previous file downloads by the clients, network coding can be efficiently exploited to expedite the download process. Since each client can tune to only one server at a time, the sets of clients served by the different servers must be disjoint in order to guarantee a maximum reduction in download time. To accomplish disjoint download mechanisms, a dual conflict network coding graph is proposed. Given the intractability of the long-term optimal solution, we propose an online algorithm using the designed dual conflict graph. For the case of one file request per client, both asymptotic lower and upper bounds of the performance of the proposed conflict-free algorithm are derived. Simulation results show that this proposed algorithm exhibits near optimum performance compared to the optimum solution, and a significant reduction in download time as compared to the per-server network coding scheme. Furthermore, imperfect feedback environment scenarios are investigated. A maximum likelihood approach is employed at the server to estimate the network state, which is then incorporated in our proposed algorithm to reduce the download time in such scenarios. Show more