On-demand resource provisioning for vehicular networks using flying fog

Abstract Since the inception of smart cities, vehicular networks has introduced new dimensions for delay-sensitive applications. The use of backend cloud data centers is no longer a viable solution due to incurred latency. Thus, to support such applications, computing devices are placed at edge locations to reduce communication delay improving the quality of service. However, in a congested environment, these locations become overloaded due to a large number of computing requests resulting in degradation of the overall system performance. In this paper, we present a computing framework addressing this problem by introducing the concept of resource allocation and provisioning in the form of flying fog units. The lease period for the allocated resources is defined based on preemptive resource provisioning model. The results demonstrate the effectiveness of the proposed framework compared to baseline approaches with wait times reduced by 9% while improving the system efficiency by 9%.