Multi-Objective Mobile Edge Provisioning in Small Cell Clouds
Vincenzo De Maio, Ivona Brandić · 2019
In recent years, Mobile Cloud Computing (MCC) has been proposed as a solution to enhance the capabilities of user equipment (UE), such as smartphones, tablets and laptops. However, offloading to conventional Cloud introduces significant execution delays that are inconvenient in case of near real-time applications. Mobile Edge Computing (MEC) has been proposed as a solution to this problem. MEC brings computational and storage resources closer to the UE, enabling to offload near real-time applications from the UE while meeting strict latency requirements. However, it is very difficult for Edge providers to determine how many Edge nodes are required to provide MEC services, in order to guarantee a high QoS and to maximize their profit. In this paper, we investigate the static provisioning of Edge nodes in a area representing a cellular network in order to guarantee the required QoS to the user without affecting providers' profits. First, we design a model for MEC offloading considering user satisfaction and provider's costs. Then, we design a simulation framework based on this model. Finally, we design a multi-objective algorithm to identify a deployment solution that is a trade-off between user satisfaction and provider profit. Results show that our algorithm can guarantee a user satisfaction above 80%, with a profit for the provider of up 4 times their cost.