A Case for Generic Interfaces in Cognitive Radio Networks

1. Vinay Kolar, Petri Mähönen, Marina Petrova, Janne Riihijärvi RWTH Aachen University Germany Mahesh Sooriyabandara, Tim Farnham Toshiba Research Europe Limited, United Kingdom A Case for Generic Interfaces in Cognitive Radio Networks

2. Overview • Motivation • Research objectives • Approach • Architecture • Design • Link layer interfaces • Network level interfaces • Application interfaces • Conclusions and outlook

3. Motivation • Capabilities of CRNs: Agile radios, powerful optimisation • But, solutions are infeasible at a system level • Heterogeneity: Portability, stakeholder cooperation • Harder to express application needs • Higher development cost and skill-requisite • Direct impact: • Realization of cognitive radio network systems is harder. • Weak motivation for business cases. • Development is hindered

4. Research Objectives • Develop Generic APIs for Cognitive radio network systems • Identify parameters and functionalities at different layers • Should help cross-layered solutions • Classify the interfaces and map them to stakeholders • Propose system architecture and design a proof-of-concept solution

5. System Architecture • Generic APIs in a system • How and where? • Identify heterogeneity • Functionality • Stakeholders Application CAPRI Cognitive Resource Manager Transport GENI Network Link ULLA Radio

6. Design – ULLA • ULLA Core • ULLA Query processing: • SELECT interfaceId FROM Link WHERE jitter < 2ms • ULLA command processing: • UPDATE Link SET modulation=BPSK WHERE dest=nodeB • ULLA event handling: • Notify when link attribute matches a subscription request

7. Design – GENI • Captures the notion of network and transport layer • New provider and information classes • Query and command similar to ULLA UPDATE Conn SET tcpFlavour='reno' WHERE dest=nodeB • Provide transparency for distributed operations • Common control Channel • Propagate queries to other nodes, collect and merge results

8. CAPRI • Utility maximization is a popular theoretical problem • e.g. General Network Utility Maximization (GNUM) • Goal: Realize them in systems for providing QoS • Each application specifies its utility • attach_utility(utilitySpecification, id) utilitySpecification = "minimize (alpha*delay + (1-alpha) throughput)", "delay < 10ms" id = unique identifier for the application (e.g. process id)

9. CAPRI • Utility specification • Express simple mathematical expressions in a textual format • CAPRI completes the formulation of the the overall optmisation problem • Maximize/Minimize <utlitySpecification> • such that • <application Constraints> • <system Constraints> • <policy Constraints> • Provide macros for common utility specification for easing development costs

10. Conclusion and outlook • Proposed architecture and functionality of generic interfaces • Enables realism • Enhances portability • Cuts down development costs • Identified and mapped stakeholders as one of the key consideration for interface design • New business opportunities through cooperation • Stakeholders can still protect proprietary functionality • Overall effort towards bringing in realism and ease in development of cognitive radio network systems

11. Future Work • Immediate goals: • Refine CAPRI by enabling rich mathematical constructs • Sniffing and measuring key parameters (at all layers) • Short-term goals: • Building an intelligent Cognitive Resource Manager that includes Generic Interfaces as a sub-component • Long-term: • Providing necessary functionalities for specific forms of cognitive radio networks • Realizing commercial deployments

12. Questions? • And my thanks to all ARAGORN members