Edge computing has attracted a lot of attention both from industry and academia in recent years and is considered as a key enabler for addressing the increasingly strict requirements of Next Generation applications. Contrary to Cloud computing, in Edge computing the computation are placed closer to the end-users into the so-called Edge, to facilitate low-latency and high-bandwidth applications and services that would not be feasible using cloud and far remote processing alone. However, the distributed, dynamic and heterogeneous environment in the Edge computing along with the diverse applications’ requirements make service placement in such infrastructure a challenging issue. One important aspect of Edge computing is the management of the placement of the applications in the network system so as to minimize each application’s runtime, given the resources of system’s devices and the capabilities of the system’s network. To this end, we propose an empirical experimental analysis, by comparing the results of different placements strategies and various edge communication networks. In particular, we model the problem of proactive placement of application images as a Minimum Vertex Cover problem. Our results demonstrate that the Greedy implementation seems to offer the best tradeoff in terms of performance, cost function and execution time.

中文翻译：

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边缘计算环境中的主动组件图像放置

近年来，边缘计算引起了工业界和学术界的广泛关注，被认为是满足下一代应用日益严格的要求的关键推动因素。与云计算相反，在边缘计算中，计算被放置在更靠近最终用户的所谓边缘中，以促进低延迟和高带宽的应用程序和服务，而这些应用程序和服务仅使用云和远程处理是不可行的。然而，边缘计算中的分布式、动态和异构环境以及多样化的应用程序需求使得此类基础设施中的服务放置成为一个具有挑战性的问题。边缘计算的一个重要方面是管理网络系统中应用程序的放置，以便在给定系统设备资源和系统网络功能的情况下最大限度地减少每个应用程序的运行时间。为此，我们通过比较不同放置策略和各种边缘通信网络的结果，提出了实证实验分析。特别是，我们将应用程序图像的主动放置问题建模为最小顶点覆盖问题。我们的结果表明，贪婪实现似乎在性能、成本函数和执行时间方面提供了最佳权衡。