Pro-active component image placement in Edge computing environments

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.