EARS: CogCloud: A Spectrum-Efficient and Green Cloud Platform for Radio-As-A-Service Over a Cognitive Radio Substrate

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Virtualization has been widely used in cloud computing to achieve performance isolation among multiple tenants, and to improve resource utilization and energy efficiency. However, research on wireless virtualization is still in its infancy. Due to the rapid growth in wireless networks in the last two decades and the fact that much of the prime wireless spectrum has already been allocated for specific service providers or services for exclusive use, the scarcity in the spectrum has become a serious concern. On the other hand, recent measurements have shown that the licensed spectrum is severely under-utilized. This has led to significant interest in cognitive radio transmission strategies.The objective of this project is to develop a spectrum-efficient cloud platform, namely CogCloud, to enable Radio-as-a-Service (RaaS) over a cognitive radio substrate, and minimize its energy consumption by designing a two-level closed-loop control framework that leverages cloud-level and BS-level optimization for coarse-grained and fine-grained control respectively over radio resources and wireless users. CogCloud is expected to have the following desirable properties: 1) RaaS for multiple independent Mobile Virtual Network Operators (MVNOs): Radio resources in a cognitive radio substrate are provided as a service to multiple independent MVNOs; 2) performance isolation: Changes in an MVNO (such as the number of wireless users, their traffic load, etc) do not affect the performance of wireless users of other MVNOs; 3) spectrum efficiency: spectrum availability is fully exploited by cognitive radios and efficiently managed by the cloud to support QoS-enabled wireless communications; 4) energy efficiency: the cognitive radio substrate and its radio resources are operated in the most energy-efficient way. To achieve these goals, the project is organized into four cohesive research thrusts: 1) system architecture design and implementation; 2) cloud-level optimization; 3) BS-level optimization for fine-grained control; and 4) validation and performance evaluation.The project is expected to make a significant impact on the advancement of cloud computing, cognitive radio networking and green communications, and advance public understanding of emerging research areas, such as wireless virtualization and cloud-based radio access networks (RANs), via publications, seminars, workshops and international collaborations. Special efforts are made to engage students from under-represented groups.