Resource Management in Edge Computing Systems
Tuesday, September 15, 2020 (Central Time) — 12:45PM - 1:30PM
Efficient utilization of computing resources has always been an important challenge for service providers, leading to significant efforts on developing solutions, either in the form of new technology or new ways to enhance the performance of existing technologies. Edge Computing~(EC) is the latest technology developed to tackle the high latency in cloud computing systems which mainly stems from the long distance between cloud servers and the end user. Edge Computing systems are expected to improve the Quality of Service (QoS) by bringing servers closer to the end user, but when it comes to the cost of services, these systems face significant challenges. The operating cost of EC systems is higher than that of the remote clouds, due to the small servers which are distributed across the network. On the other hand, compared to the cloud data centers, edge nodes have more restricted capacity. Another challenge in EC systems is the mobility of users, that might make the current allocation of resources inefficient or even infeasible in few minutes. These issues become more challenging in the Vehicular Edge Computing (VEC) systems where each vehicle can be considered as an edge node. In this dissertation, we address some of the existing challenges of resource management in EC systems. Our contribution consists of designing efficient resource allocation algorithms that are suitable for real world edge systems. In our proposed approaches, major performance metrics such as energy consumption and QoS are taken into account.