Congestion Mitigation in Densely Crowded Environments for Augmenting QoS in Vehicular Clouds

Abstract

Parking lots in densely crowded environments such as stadiums, theaters and hospitals provide great opportunities for vehicular cloud services. A cloud environment formed by individual vehicles, where each vehicle offers its resources as a service has shown feasible practices in 5G network scenarios. Moreover, resource management in 5G must be achieved in accordance with user-centric QoS requirements. In alignment with this, a key enabler of the user-centric service scheme is Network Slicing. The formation of multiple slices in such a dense environment, the congestion between sender and receiver, and resource management and allocation are topics of current research. This paper has the following contribution: First, a framework of Vehicular Clouds being restricted to individual slices in 5G cellular networks is proposed. Second, a queuing strategy for congestion control in a densely crowded environment such as parking lots is designed. Finally, a resource allocation algorithm that enables maximum matching between the tasks to be executed and the candidate slices is developed. The novelty of this approach comes from the fact that congestion control is performed at the Access Points (AP). We do this by introducing a control module that makes queuing decisions at the time of request arrival. By incorporating control module in AP, our aim is to provide AP resources in terms of transmission period to different slices, thereby, allowing WiFi resources to be shared along with the 5G radio resources. The performance benefits of the proposed solution has been investigated through simulation tests.