Resource Allocation in Adaptive Virtualized Wireless Networks with Mobile Edge Computing

Due to ubiquitous presence of wireless connectivity and surge in internet of things (IoT) devices, the next generation wireless network is predicted to face crunch of resources. Wireless virtualization is regarded as a viable approach to enhance resource utilization efficiency by sharing and reusing the physical resources in the form of slices or virtual networks (VNs). Mobile edge computing (MEC), on the other hand, facilitates task offloading as well as fast content delivery by bringing the computation and cache resources to the edge of the network. In this paper, we investigate virtualization of physical infrastructure that is embedded with MEC resources. In particular, this paper presents resource allocation in adaptive virtualized wireless networks with mobile edge computing. First, we investigate how to create VNs for mobile virtual network operators (MVNOs) based upon demand from users. Second, after creating the VN, how the MVNO can allocate resources to its users so that the utility (aka revenue) of the MVNO is maximized while satisfying users' quality of service (QoS). For the first problem, we propose an algorithm that incorporates demanded area of the MVNO, demanded spectrum, and computation and cache resources. Next, we present a collaborative resource allocation for maximizing the utility of MVNO while meeting the QoS requirements in terms of rates of the users. The performance is evaluated through numerical results obtained from Monte Carlo simulations. Numerical results show that the proposed approach gives better results in terms of utility and spectrum utilization efficiency.