Cognitive radio virtual networks environment: definition, modeling and mapping of secondary virtual networks onto wireless substrate - BALIEIRO, Andson Marreiros (2015)
The wireless technologies are progressing at a rapid pace such that the future of digital communication will be dominated by a dense, ubiquitous and heterogeneous wireless network. Along with this, there is a growing demand for wireless services with different requirements. In this respect, the management of this complex wireless ecosystem becomes challenging, and the wireless virtualization is pointed as an efficient solution to perform it, where different virtual wireless networks can be created, sharing and running on the same wireless infrastructure, and providing differentiated services to users. However, to satisfy the high demand for mobile communications, it is necessary the availability of a natural and scarce resource, the electromagnetic spectrum. Although the insertion of virtualization in wireless networks provides better resources utilization, the current approaches to employ the wireless virtualization can cause resource underutilization. To overcome this underutilization and enable that new wireless virtual networks can be deployed, the wireless virtualization can be combined with the cognitive radio technology and dynamic spectrum access (DSA) techniques in order to achieve the deepest level of wireless virtualization and to improve the resource utilization through the deployment of opportunistic resource sharing. Thus, virtual wireless networks with different access priorities to the resources (e.g. primary and secondary) can be deployed in an overlay form, sharing the same substrate wireless network, where the secondary virtual network (SVN) accesses the resources only when the primary one (PVN) is not using them. However, this new scenario brings new challenges: from the mapping to operation of these networks. The SVN mapping is a NP-hard problem and presents some constraints and objectives related to both PVNs and SVNs. Achieving all objectives simultaneously is a challenging process. This thesis addresses the SVNs mapping problem onto substrate network considering the existence of the PVNs on the same substrate network. It discloses the environment composed by these networks, denoted as cognitive radio virtual network environment (CRVNE), models this environment by using a M/M/N/N queue with preemptive and priority service, and delineates a multi-objective problem formulation for the SVNs mapping. Moreover, a scheme based on Genetic Algorithms to solve the SVNs mapping problem is proposed and evaluated in terms of collision, secondary user (SU) dropping, and SU blocking probabilities, and joint utilization, achieving better results than other based on the First-Fit strategy.