Dealing with the ever-increasing video traffic is certainly one of the major challenges facing Internet Service Providers (ISPs). In this context, the strategic placement of caches is seen as one of the most important remedies, especially with recent advances in the field of virtualization. Unlike the existing works, which only focus on the placement issue, we also consider the problem of determining the optimal amount of cache to place at each possible location. We formalize, in this paper, the problem of caches placement as a multi-objective optimization problem, in which we minimize both the average distance from which contents are retrieved and the peering links utilization. As the proposed problem is NP-hard, we propose to solve it using the Greedy Randomized Adaptive Search Procedure (GRASP) meta-heuristic. Simulations results reveal the quality of the obtained solutions compared to an exhaustive search method. At the same time, they reveal that the solution is not to put all resources at the edge or at the core, as some studies claim, but to partition them judiciously, which mainly depends on the objectives of the ISPs.

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基于GRASP的未来网络中动态缓存资源放置的方法

处理日益增长的视频流量无疑是Internet服务提供商（ISP）面临的主要挑战之一。在这种情况下，缓存的战略性放置被视为最重要的补救措施之一，尤其是随着虚拟化领域的最新发展。与仅关注放置问题的现有作品不同，我们还考虑了确定在每个可能位置放置最佳缓存量的问题。在本文中，我们将缓存放置的问题形式化为多目标优化问题，在该问题中，我们将检索内容的平均距离和对等链接的使用均减至最小。由于提出的问题是NP难题，因此我们建议使用贪婪随机自适应搜索过程（GRASP）元启发式算法来解决。仿真结果表明与穷举搜索方法相比，所获得解决方案的质量。同时，他们发现解决方案不是像某些研究声称的那样将所有资源置于边缘或核心，而是明智地进行分配，这主要取决于ISP的目标。