Abstract
Bat algorithm (BA) is developed by Xin She Yang in 2010 and gaining popularity due to its astonishing feature of echolocation. It has drawn the attention of many researchers, to contribute in the performance enhancement of the algorithm. The proposed variant of Bat algorithm computes ‘distance’ by calculating the similarity among the pulse emitted by artificial bats and the received echo. This work also focuses on the applicability of the proposed variant of BA for finding optimal route in wireless sensor network, while reducing the delay, which may occur due to heavy traffic on the optimal path. The results of the proposed algorithm are evaluated, in terms of best, mean, worst, median and standard deviation, for the time required to obtain optimal results on the basis of distance (as fitness value) between the sensing nodes and outperforms standard BA.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Blum, C., Roli, A.: Metaheuristics in combinatorial optimization: overview and conceptual comparison. ACM Comput. Surv. (CSUR) 35(3), 268–308 (2003)
Prathap, U., Shenoy, P.D., Venugopal, K.R., Patnaik, L.M.: Wireless sensor networks applications and routing protocols: survey and research challenges. In: 2012 International Symposium on Cloud and Services Computing (ISCOS), pp. 49–56, Dec 2012
Singh, S.P., Sharma, S.C.: A survey on cluster based routing protocols in wireless sensor networks. Procedia Comput. Sci. 45, 687–695 (2015)
Sharma, M.: Wireless sensor networks: routing protocols and security issues. In: 2014 International Conference on Computing, Communication and Networking Technologies (ICCCNT), pp. 1–5. IEEE
Sharma, S., Luhach, A.K., Jyoti, K.: Research and analysis of advancements in BAT algorithm. In: 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), pp. 2391–2396. IEEE (2016)
Tyagi, S., Kumar, N.: A systematic review on clustering and routing techniques based upon LEACH protocol for wireless sensor networks. J. Netw. Comput. Appl. 36(2), 623–645 (2013)
Zengin, A., Tuncel, S.: A survey on swarm intelligence based routing protocols in wireless sensor networks. Int. J. Phys. Sci. 5(14), 2118–2126 (2010)
Jadhav, P., Satao, R.: A survey on opportunistic routing protocols for wireless sensor networks. Procedia Comput. Sci. 79, 603–609 (2016)
Jung, S.G., Kang, B., Yeoum, S., Choo, H.: Trail-using ant behavior based energy-efficient routing protocol in wireless sensor networks. Int. J. Distrib. Sens. Netw. (2016)
Bhatt, M., Sharma, S., Prakash, A., Pandey, U. S., Jyoti, K.: Traffic collision avoidance in VANET using computational intelligence. Int. J. Eng. Technol. (2016)
Shahi, B., Dahal, S., Mishra, A., Kumar, S.V., Kumar, C.P.: A review over genetic algorithm and application of wireless network systems. Procedia Comput. Sci. 78, 431–438 (2016)
Camilo, T., Carreto, C., Silva, J. S., Boavida, F.: An energy-efficient ant-based routing algorithm for wireless sensor networks. In: International Workshop on Ant Colony Optimization and Swarm Intelligence, pp. 49–59. Springer, Berlin, Heidelberg Sep 2006
Chen, Y.-T., Shieh, C.-S., Horng, M.-F., Liao, B.-Y., Pan, J.-S., Tsai, M.-T.: A guidable bat algorithm based on Doppler effect to improve solving efficiency for optimization problems. Comput. Collect. Intell. Technol. Appl. 8733, 373–383 (2014)
Mirjalili, S.M., Yang, X.-S., Mirjalili, S.: Binary bat algorithm. Neural Comput. Appl. 663–681 (2014)
Zhou, Y., Li, L.: A novel complex-valued bat algorithm. Neural Comput. Appl. 25(6), 1369–1381 (2014)
Manshahia, M.S., Dave, M., Singh, S.B.: Improved bat algorithm based energy efficient congestion control scheme for wireless sensor networks. Wirel. Sens. Netw. 8(11), 229 (2016)
Kalko, E.K.: Insect pursuit, prey capture and echolocation in pipestirelle bats (Microchiroptera). Anim. Behav. 50(4), 861–880 (1995)
Simmons, J.A.: A view of the world through the bat’s ear: the formation of acoustic images in echolocation. Cognition 33(1–2), 155–199 (1989)
Yang, X.S.: A new metaheuristic bat-inspired algorithm. In: Nature Inspired Cooperative Strategies for Optimization, pp. 65–74. Springer, Berlin, Heidelberg (2010)
Osaba, E., Yang, X.S., Diaz, F., Lopez-Garcia, P., Carballedo, R.: An improved discrete bat algorithm for symmetric and asymmetric traveling salesman problems. Eng. Appl. Artif. Intell. 48, 59–71 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sharma, S., Verma, S., Jyoti, K. (2019). A New Bat Algorithm with Distance Computation Capability and Its Applicability in Routing for WSN. In: Wang, J., Reddy, G., Prasad, V., Reddy, V. (eds) Soft Computing and Signal Processing . Advances in Intelligent Systems and Computing, vol 898. Springer, Singapore. https://doi.org/10.1007/978-981-13-3393-4_17
Download citation
DOI: https://doi.org/10.1007/978-981-13-3393-4_17
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-3392-7
Online ISBN: 978-981-13-3393-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)