In recent network architectures, multi-MEC cooperative caching has been introduced to reduce the transmission latency of VR videos, in which MEC servers' computing and caching capability are utilized to optimize the transmission process. However, many solutions that use the computing capability of MEC servers ignore the additional arithmetic power consumed by the codec process, thus making them infeasible. Besides, the minimum cache unit is usually the entire VR video, which makes caching inefficient. To address these challenges, we split VR videos into tile files for caching based on the current popular network architecture and provide a reliable transmission mechanism and an effective caching strategy. Since the number of different tile files N is too large, the current cooperative caching algorithms do not cope with such large-scale input data. We further analyze the problem and propose an optimized k-shortest paths (OKSP) algorithm with an upper bound time complexity of O((K * M + N) * M * logN)), and suitable for shortest paths with restricted number of edges, where K is the total number of tiles that all M MEC servers can cache in the collaboration domain. And we prove the OKSP algorithm can compute the caching scheme with the lowest average latency in any case, which means the solution given is the exact solution. The simulation results show that the OKSP algorithm has excellent speed for solving large-scale data and consistently outperforms other caching algorithms in the experiments.
翻译:在最近的网络架构中,引入了多MEC合作缓存,以减少 VR 视频的传输延缓度,其中使用MEC 服务器的计算和缓存能力优化传输过程。然而,许多使用MEC 服务器计算能力的解决方案忽略了代码化过程所消耗的额外算术能力,从而使它们无法实现。此外,最小缓存单位通常是整个 VR 视频,这使得缓存效率低。为了应对这些挑战,我们将 VR 视频分解为基于当前广受欢迎的网络架构的缓存文件,以提供一个可靠的传输机制和有效的缓存战略。由于不同的磁盘文件N数量太大,目前合作的缓存算算法无法应对如此大规模的输入数据。我们进一步分析这一问题,并提议优化 kshort路径(OKSP) 算法,该算法通常使 O(K * M + N) 和 M * M * logN) 的缩略图适合短路径的缓存路径,其中K是所有 MEC 服务器的整数,而其总缩缩缩略图的缩缩图则能够显示所有 MIC 解算法的快速解算方法,而所有 MECL 直径化的缩算法则可以显示所有的缩算法的缩算法的缩算法的缩算方法可以证明。</s>