Abstract
Beyond 3rd Generation (B3G) wireless communication systems are comprised from different Radio Access Technologies (RATs) in order to satisfy all user needs in services. The coexistence of many RATs in the same environment needs advanced network management systems in order to ensure efficient resources utilization while achieving the best possible Quality of Service (QoS) levels. Management functionality in the B3G era will have to solve complex problems, due to the existence of versatile options for satisfying stringent requirements, under difficult environment conditions. The introduction of cognitive systems in the B3G world is a direction for addressing the complexity, as it will enable reaching decisions faster and more reliably, by considering also knowledge and experience derived from past interactions of the system with the network environment. Our work presents an approach for identifying whether a context, encountered by the network segment, has also been dealt in the past. In this case context knowledge can be exploited for fast and cost efficient network reconfiguration and adaptation to the environment conditions.
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References
Third (3rd) Generation partnership project. (3GPP) (2008). Web site, www.3gpp.org.
Institute of electrical and electronics engineers. (IEEE) (2008). 802 standards, www.ieee802.org.
WiMAX forum. (2008). http://www.wimaxforum.org.
Wireless world research forum (WWRF). (2008). www.wireless-world-research.org.
Project end-to-end reconfigurability (E 2R). (2004–2007). www.e2r.motlabs.com, 6th framework programme (FP6) of the european commission, information society technologies (IST).
Project end-to-end efficiency (E 3). (2008). www.ict-e3.eu, 7th framework programme (FP7) of the european commission, information and communication technologies (ICT).
Hasselbring W., Reussner R. (2006) Toward trustworthy software systems. Computer 39(4): 91–92. doi:10.1109/MC.2006.142
International telecommunication union—telecommunications standardization bureau (ITU-T). (2001). Communications quality of service: A framework and definitions, recommendation G1000.
International telecommunications union—telecommunications standardization bureau (ITU-T). (2003). End-user multimedia QoS categories, recommendation G1010.
Song Q., Jamalipour A. (2005) Network selection in integrated wireless LAN and UMTS environment using mathematical modelling and computing techniques. IEEE Wireless Communications Magazine 12(3): 42–48
Bari F., Leung V. (2007) Automated network selection in a heterogeneous wireless network environment. IEEE Network 21(1): 34–40
Strassner, J. S. (2004).Policy-based network management: Solution for the next generation. In Elsevier science and technology books. Morgan Kaufmann. ISBN:1558608591, 9781558608597
Demestichas P., Koutsouris N., Koundourakis G., Tsagkaris K., Oikonomou A., Stavroulaki V., Papadopoulou L., Theologou M., Vivier G., El-Khazen K. (2003) Management of networks and services in a composite radio context. IEEE Wireless Communications Magazine 10(4): 44–51
Tsagkaris K., Dimitrakopoulos G., Saatsakis A., Demestichas P. (2007) Distributed radio access technology selection for adaptive networks in high-Speed, B3G infrastructures. International Journal of Communication Systems 20(8): 969–992
Thomas R.W., Friend D.H., DaSilva L.A., McKenzie A.B. (2006) Cognitive networks: Adaptation and learning to achieve end-to-end performance objectives. IEEE Communications Magazine 44(12): 51–57. doi:10.1109/MCOM.2006.273099
Demestichas P., Dimitrakopoulos G., Strassner J., Bourse D. (2006) Introducing reconfigurability and cognitive networks concepts in the wireless world: Research achievements and challenges. IEEE Vehicular Technology Magazine 1(2): 33–39
Mahonen P., Zorzi M. (2007) Cognitive wireless networks. IEEE Wireless Communications Magazine 14(4): 4–5. doi:10.1109/MWC.2007.4300976
Venkatesha Prasad R.V., Pawelczak P., Hoffmeyer J.A., Steven Berger H. (2008) Cognitive functionality in next generation wireless networks: Standardization efforts. IEEE Communications Magazine 46(4): 72–78. doi:10.1109/MCOM.2008.4481343
Sherman M., Mody A.N., Martinez R., Rodriguez C., Reddy R. (2008) IEEE standards supporting cognitive radio and networks, dynamic spectrum access, and coexistence. IEEE Communications Magazine 46(7): 72–79. doi:10.1109/MCOM.2008.4557045
Mitchell T. (1997) Machine learning. McGraw-Hill, New York
Van Sinderen M. J., Van Halteren A. T., Wegdam M., Meeuwissen H. B., Henk Eertink E. (2006) Supporting context-aware mobile applications. IEEE Communications Magazine 44(9): 96–104
Bellavista P., Corradi A., Montanari R., Tononelli A. (2006) Context–aware semantic discovery for next generation mobile systems. IEEE Communications Magazine 44(9): 62–71
Tsagkaris K., Katidiotis A., Demestichas P. (2008) Neural network-based learning schemes for cognitive radio systems. Computer Communications Journal 31(14): 3394–3404. doi:10.1016/j.comcom.2008.05.040
Liu X., Shankar N. S. (2006) Sensing-based opportunistic channel access. Mobile Networks and Applications Journal 11(4): 577–591
Kim H., Shin K. G. (2008) Efficient discovery of spectrum opportunities with MAC-layer sensing in cognitive radio networks. IEEE Transactions on Mobile Computing 7(5): 533–545
Perez-Romero, J., Sallent, O., Agusti, R., & Giupponi, L. (2007). A novel on-demand cognitive pilot channel enabling dynamic spectrum allocation. In Proceeding of 2nd international symposium on new frontiers in dynamic spectrum access networks 2007 (DySPAN 2007), Dublin, Ireland.
Kephart J., Chess D. (2003) The vision of autonomic computing. IEEE Computer 36(1): 41–50
Demestichas P., Boscovic D., Stavroulaki V., Lee A., Strassner J. (2006) m@ANGEL: Autonomic management platform for seamless wireless cognitive connectivity. IEEE Communications Magazine 44(6): 118–127
Nolan K., Doyle L. (2007) Teamwork and collaboration in cognitive wireless networks. IEEE Wireless Communications Magazine 14(4): 22–27
Mas-Collel A. (1995) Microeconomics. Oxford University Press, Oxford
Demestichas P., Dimitrakopoulos G., Tsagkaris K., Stavroulaki V., Katidiotis A. (2007) Introducing cognitive systems to the B3G wireless world, cognitive wireless networks: Concepts, methodologies and visions inspiring the age of enlightenment of wireless communications. Springer, Dordrecht, The Netherlands, pp 253–269
Dimitrakopoulos, G., Tsagkaris, K., Demestichas, K., Adamopoulou, E., & Demestichas, P. A management scheme for distributed cross-layer reconfigurations in the context of cognitive B3G infrastructures. accepted for publication in the Computer Communications journal.
Zhan, Y., Chen, H., & Zhang, G.-C. (2006). An optimization algorithm of K-NN classification. In Proceeding of international conference on machine learning and cybernetics (pp. 2246–2251).
Samet H. (2008) K-Nearest neighbor finding using MaxNearestDist. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(2): 243–252
Yu, X.-G., & Yu, X.-P. (2006). The research on an adaptive K-NN classifier. In Proceeding of fifth international conference on machine learning and cybernetics.
Demestichas P., Tzifa E., Anagnostou M. (1998) Traffic adaptive aggregate channel allocation for future cellular communication systems. International Journal of Communication Systems 11: 337–349
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Saatsakis, A., Demestichas, P. Context Matching for Realizing Cognitive Wireless Network Segments. Wireless Pers Commun 55, 407–440 (2010). https://doi.org/10.1007/s11277-009-9807-z
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DOI: https://doi.org/10.1007/s11277-009-9807-z