Abstract
Wireless Body Area Networks (WBANs) consists of various sensors which are attached on or even implanted in the body to improve health care and the quality of life. Soft computing techniques including fuzzy logic have been successfully applied to WBANs. However, most of the existing research works considered only single-level fuzzy logic controls (FLCs). In this paper, we propose a two-level control scheme at both the sensor level and the coordinator level to improve both the reliability and performance of Medium Access Controls (MAC) in WBANs. We also propose to use Cooperative PSO (CPSO) to automate the design of our two-level control scheme. With the goal of improving network reliability while keeping the communication delay at a low level, we have particularly experimented on four different collaborator selection methods for CPSO. Specifically, we show that network knowledge can help CPSO to select collaborators more effectively. Moreover, the FLCs designed by our approach is also shown to outperform some recently developed algorithms and the IEEE 802.15.4 standard.
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References
IEEE Standard for local and metropolitan area networks–part 15.4: Low-Rate Wireless Personal Area Networks (LR-WPANs). IEEE Std 802.15.4-2011 (Revision of IEEE Std 802.15.4-2006), pp. 1–314. September 2011
van den Bergh, F., Engelbrecht, A.P.: A cooperative approach to particle swarm optimization. IEEE Trans. Evol. Comput. 8(3), 225–239 (2004)
Cavalcanti, D., Schmitt, R., Soomro, A.: Performance analysis of 802.15.4 and 802.11e for body sensor network applications. In: Leonhardt, S., Falck, T., Mähönen, P. (eds.) BSN 2007. IFMBE Proceedings, vol. 13, pp. 9–14. Springer, Heidelberg (2007)
Cavallari, R., Martelli, F., Rosini, R., Buratti, C., Verdone, R.: A survey on wireless body area networks: technologies and design challenges. IEEE Commun. Surv. Tutor. 16(3), 1635–1657 (2014)
Fleming, P., Purshouse, R.: Evolutionary algorithms in control systems engineering: a survey. Control Eng. Pract. 10(11), 1223–1241 (2002)
Huang, Y.K., Pang, A.C., Hung, H.N.: An adaptive GTS allocation scheme for IEEE 802.15.4. IEEE Trans. Parallel Distrib. Syst. 19(5), 641–651 (2008)
Li, X., Yao, X.: Tackling high dimensional nonseparable optimization problems by cooperatively coevolving particle swarms. In: 2009 IEEE Congress on Evolutionary Computation, pp. 1546–1553. May 2009
Mouzehkesh, N., Zia, T., Shafigh, S., Zheng, L.: D\(^2\)MAC: dynamic delayed medium access control (MAC) protocol with fuzzy technique for wireless body area networks. In: IEEE International Conference on Body Sensor Networks (BSN), pp. 1–6. May 2013
Nekooei, S.M., Chen, G., Rayudu, R.K.: Automatic design of fuzzy logic controllers for medium access control in wireless body area networks an evolutionary approach. Appl. Soft Comput. 56, 245–261 (2017)
Otal, B., Alonso, L., Verikoukis, C.: Highly reliable energy-saving MAC for wireless body sensor networks in healthcare systems. IEEE J. Sel. Areas Commun. 27(4), 553–565 (2009)
Potter, M.A., De Jong, K.A.: A cooperative coevolutionary approach to function optimization. In: Davidor, Y., Schwefel, H.-P., Männer, R. (eds.) PPSN 1994. LNCS, vol. 866, pp. 249–257. Springer, Heidelberg (1994). doi:10.1007/3-540-58484-6_269
Taparugssanagorn, A., Rabbachin, A., Hämäläinen, M., Saloranta, J., Iinatti, J., Member, S.: A review of channel modelling for wireless body area network in wireless medical communications. In: The 11th International Symposium on Wireless Personal Multimedia Communications. WPMC 2008 (2008)
Wiegand, R.P., Liles, W.C., Jong, K.A.D.: An empirical analysis of collaboration methods in cooperative coevolutionary algorithms. In: Proceedings of the 3rd Annual Conference on Genetic and Evolutionary Computation, GECCO 2001, pp. 1235–1242 (2001)
Xue, B., Zhang, M., Browne, W.: Particle swarm optimization for feature selection in classification: a multi-objective approach. IEEE Trans. Cybern. 43(6), 1656–1671 (2013)
Zhou, J., Guo, A., Xu, J., Su, S.: An optimal fuzzy control medium access in wireless body area networks. Neurocomputing 142, 107–114 (2014). SI Computational Intelligence Techniques for New Product Development
Acknowledgments
The author(s) wish to acknowledge the contribution of NeSI high-performance computing facilities to the results of this research. NZ’s national facilities are provided by the NZ eScience Infrastructure and funded jointly by NeSI’s collaborator institutions and through the Ministry of Business, Innovation & Employment’s Research Infrastructure programme. URL https://www.nesi.org.nz.
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Nekooei, S.M., Chen, G., Rayudu, R. (2017). Cooperative Design of Two Level Fuzzy Logic Controllers for Medium Access Control in Wireless Body Area Networks. In: Shi, Y., et al. Simulated Evolution and Learning. SEAL 2017. Lecture Notes in Computer Science(), vol 10593. Springer, Cham. https://doi.org/10.1007/978-3-319-68759-9_71
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DOI: https://doi.org/10.1007/978-3-319-68759-9_71
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