Cloud Computing Based Cognitive Radio Networking

This chapter describes state-of-the art techniques to improve performance of spectrum sensing and spectrum management in Cognitive Radio Networks (CRN) by leveraging services available in cloud computing platforms. CRNs are capable of adaptive learning and reconfiguration to provide consistent communications in dynamic environments. However, ensuring adaptation and learning in CRN will require availability of large volume of data and fast processing. However, the performance and security of CRN is considerably constrained by its limited power, memory and computational capacity, it may not be able to achieve its full capability. Fortunately, the advent of cloud computing has the potential to mitigate these constraints due its vast storage and computational capacity.

[1]  Sai Shankar Nandagopalan,et al.  IEEE 802.22: An Introduction to the First Wireless Standard based on Cognitive Radios , 2006, J. Commun..

[2]  Leonardo Neumeyer,et al.  S4: Distributed Stream Computing Platform , 2010, 2010 IEEE International Conference on Data Mining Workshops.

[3]  Hsiao-Hwa Chen,et al.  Joint Angular and Time Diversity of Multi-Antenna CDMA Systems in Wireless Fading Channels , 2011, Int. J. Wirel. Networks Broadband Technol..

[4]  Geoffrey Ye Li,et al.  Cooperative Spectrum Sensing in Cognitive Radio, Part II: Multiuser Networks , 2007, IEEE Transactions on Wireless Communications.

[5]  Chandrasekharan Raman,et al.  Fair and Efficient Scheduling of Variable Rate Links via a Spectrum Server , 2006, 2006 IEEE International Conference on Communications.

[6]  Jaafar M. H. Elmirghani,et al.  An End-to-End QoS Framework for Vehicular Mobile Networks , 2010 .

[7]  C. Cordeiro,et al.  Spectrum agile radios: utilization and sensing architectures , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[8]  Xin Luo,et al.  Evolutionary Malware: Mobile Malware, Botnets, and Malware Toolkits , 2012, Int. J. Wirel. Networks Broadband Technol..

[9]  Bernhard Walke,et al.  Spectrum load smoothing: distributed quality-of-service support for cognitive radios in open spectrum , 2006, Eur. Trans. Telecommun..

[10]  Thomas Hunziker.  On the Employment of SMI Beamforming for Cochannel Interference Mitigation in Digital Radio , 2009 .

[11]  John Cosmas,et al.  Adaptive Coexistence between Cognitive and Fiber Networks , 2012 .

[12]  Yonghong Zeng,et al.  Spectrum-Sensing Algorithms for Cognitive Radio Based on Statistical Covariances , 2008, IEEE Transactions on Vehicular Technology.

[13]  Ian F. Akyildiz,et al.  NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey , 2006, Comput. Networks.

[14]  Yi-Hong Chu,et al.  Multi-System Integration Scheme for Intelligence Transportation System Applications , 2014, Int. J. Wirel. Networks Broadband Technol..

[15]  Geoff Hulten,et al.  Mining high-speed data streams , 2000, KDD '00.

[16]  Moeness G. Amin,et al.  Mobile Ad Hoc Networks Exploiting Multi-Beam Antennas , 2009 .

[17]  Sachin Shetty,et al.  Control-Free Dynamic Spectrum Access for Cognitive Radio Networks , 2010, 2010 IEEE International Conference on Communications.

[18]  Simon Haykin,et al.  Cognitive radio: brain-empowered wireless communications , 2005, IEEE Journal on Selected Areas in Communications.

[19]  Joseph M. Hellerstein,et al.  MapReduce Online , 2010, NSDI.

[20]  Sachin Shetty,et al.  Secure Radio Resource Management in Cloud Computing Based Cognitive Radio Networks , 2012, 2012 41st International Conference on Parallel Processing Workshops.

[21]  H. Urkowitz.  Energy detection of unknown deterministic signals , 1967 .

[22]  Benoît Escrig,et al.  DMT Optimal Cooperative MAC Protocols in Wireless Mesh Networks with Minimized Signaling Overhead , 2011, Int. J. Wirel. Networks Broadband Technol..

[23]  Gongjun Yan,et al.  Signal processing techniques for spectrum sensing in cognitive radio systems: Challenges and perspectives , 2009, 2009 First Asian Himalayas International Conference on Internet.

[24]  Friedrich K. Jondral,et al.  Air interface identification for software radio systems , 2007 .

[25]  Sasan Adibi,et al.  Fourth-generation Wireless Networks: Applications and Innovations , 2009 .

[26]  Jeffrey H. Reed,et al.  Convergence of cognitive radio networks , 2004, 2004 IEEE Wireless Communications and Networking Conference (IEEE Cat. No.04TH8733).

[27]  Henning Schulzrinne,et al.  Mobility support using SIP , 1999, WOWMOM '99.

[28]  Md. Abdul Matin.  Developments in Wireless Network Prototyping, Design, and Deployment: Future Generations , 2012 .

[29]  Kiran Challapali,et al.  Spectrum Agile Radio: Detecting Spectrum Opportunities , 2004 .

[30]  Gokhan Memik,et al.  Energy Detection Using Estimated Noise Variance for Spectrum Sensing in Cognitive Radio Networks , 2008, 2008 IEEE Wireless Communications and Networking Conference.

[31]  R.W. Brodersen,et al.  Implementation issues in spectrum sensing for cognitive radios , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[32]  Muthaiah Venkatachalam,et al.  QoS Architecture of WiMAX , 2010 .

[33]  J. Mitola,et al.  Cognitive radio for flexible mobile multimedia communications , 1999, 1999 IEEE International Workshop on Mobile Multimedia Communications (MoMuC'99) (Cat. No.99EX384).

[34]  Howard Gobioff,et al.  The Google file system , 2003, SOSP '03.

[35]  Asrar U. H. Sheikh,et al.  Spectrum Access and Sharing for Cognitive Radio , 2012 .

[36]  Juan Antonio Guerrero Ibáñez,et al.  Emerging Technologies in Transportation Systems: Challenges and Opportunities , 2012, Int. J. Wirel. Networks Broadband Technol..

[37]  Mohammad A. Al-Jarrah,et al.  Cooperative Space Time Coding for Semi Distributed Detection in Wireless Sensor Networks , 2012, Int. J. Wirel. Networks Broadband Technol..

[38]  P. De,et al.  Blind Sensing Algorithms for Cognitive Radio , 2007, 2007 IEEE Radio and Wireless Symposium.

[39]  Chen Sun,et al.  Handbook on Advancements in Smart Antenna Technologies for Wireless Networks , 2008 .

[40]  Garimella Rama Murthy,et al.  Doubly Cognitive Architecture Based Cognitive Wireless Sensor Networks , 2011, Int. J. Wirel. Networks Broadband Technol..

[41]  C. Jason Chiang,et al.  Cognitive Radio Rides on the Cloud , 2010, 2010 - MILCOM 2010 MILITARY COMMUNICATIONS CONFERENCE.

[42]  Neeraj Kumar,et al.  Load Balancing Aware Multiparty Secure Group Communication for Online Services in Wireless Mesh Networks , 2011, Int. J. Wirel. Networks Broadband Technol..

[43]  Gabriel-Miro Muntean,et al.  Wireless Multi-Access Environments and Quality of Service Provisioning: Solutions and Application , 2012 .

[44]  Luis A. Escobar,et al.  A Note on the Updating of Regression Estimates , 1993 .

[45]  R.W. Brodersen,et al.  Spectrum Sensing Measurements of Pilot, Energy, and Collaborative Detection , 2006, MILCOM 2006 - 2006 IEEE Military Communications conference.

[46]  Sasan Adibi,et al.  Quality of Service Architectures for Wireless Networks: Performance Metrics and Management , 2010 .

[47]  Tim Farnham,et al.  IST-TRUST: a perspective on the reconfiguration of future mobile terminals using software download , 2000, 11th IEEE International Symposium on Personal Indoor and Mobile Radio Communications. PIMRC 2000. Proceedings (Cat. No.00TH8525).