Abstract
The current trend in Wireless Sensor Network (WSN) is based on multihop networking which is used to transmit data through various networks. The usage of multihop forwarding in large-scale WSNs cause an energy hole problem, which results in a considerable amount of transmission overhead. In this paper, a multiple portable sink-based information gathering method that combines energy balanced clustering as well as Artificial Bee Colony-based data gathering is proposed in order to address these concerns. The remaining energy of the node is used to determine which node will serve as the cluster’s centre of gravity. According to the findings of this research, mobile sink balancing may be approached from three different perspectives: data gathering expansion, mobile route distance reduction, and network reliability optimization. This study is conducted with the use of a significant and intense WSN that enables a specific level of data delay to be tolerated in order to be successful. The paper proposes the optimization technique which is known as Artificial Bee Colony optimization technique that can accept the reduction losses in data communication, improve network lifetime, save the energy of the system, maintain the reliability of the system, and increase the network efficiency.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
G. Xing, M. Li, T. Wang et al., Efficient rendezvous algorithms for mobility-enabled wireless sensor networks. IEEE Trans. Mob. Comput. 11(1), 47–60 (2012). https://doi.org/10.1109/TMC.2011.66
Y. Yue, J. Li, H. Fan, et al., Optimization-based artificial bee colony algorithm for data collection in large-scale mobile wireless sensor networks. J Sens. 2016, Article ID 7057490, 12 (2016). [Web of Science ®], [Google Scholar]
L. Malathi, R.K. Gnanamurthy, K. Channdrasekaran, Energy efficient data collection through hybrid unequal clustering for wireless sensor networks. Comput. Electr. Eng. 48, 358–370 (2015). https://doi.org/10.1016/j.compeleceng.2015.06.019
S.J. Tang, J. Yuan, X.Y. Li, et al., DAWN: energy efficient data aggregation in WSN with mobile sinks, in Proceedings of the IEEE 18th International Workshop on Quality of Service (IWQoS ‘10) (IEEE, Beijing, China, 2010). pp. 1–9
M. Ma, Y. Yang, Sencar: an energy-efficient data gathering mechanism for large-scale multihop sensor networks. IEEE Trans. Parallel Distrib. Syst. 18(10), 1476–1488 (2007). https://doi.org/10.1109/TPDS.2007.1070
S. Basagni, A. Carosi, E. Melachrinoudis et al., Controlled sink mobility for prolonging wireless sensor networks lifetime. Wirel Netw. 14(6), 831–858 (2008). https://doi.org/10.1007/s11276-007-0017-x
S. Basagni, A. Carosis, E. Melachrinoudis, et al., A new MILP formulation and distributed protocols for wireless sensor networks lifetime maximization, in Proceedings of the IEEE International Conference on Communications (ICC ‘06) (IEEE, Istanbul, Turkey, 2006), pp. 3517–3524
H.T. Nguyen, L. Van Nguyen, H.X. Le, Efficient approach for maximizing lifespan in wireless sensor networks by using mobile sinks. ETRI J. 39(3), 353–363 (2017). https://doi.org/10.4218/etrij.17.0116.0629
J. Luo, J.-P. Hubaux, Joint sink mobility and routing to maximize the lifetime of wireless sensor networks: the case of constrained mobility. IEEE/ACM Trans Networking. 18(3), 871–884 (2010). https://doi.org/10.1109/TNET.2009.2033472
J. Luo, J. Panchard, M. Piórkowski, et al., Routing towards a mobile sink for improving lifetime in sensor networks, in Proceedings of Distributed Computing in Sensor Systems: 2nd IEEE International Conference, DCOSS 2006, vol. 4026 (San Francisco, CA, USA, 2006)
B. Bhushan, G. Sahoo, E2 SR2: an acknowledgement-based mobile sink routing protocol with rechargeable sensors for wireless sensor networks. Wirel. Netw. 25(5), 1–25 (2019). https://doi.org/10.1007/s11276-019-01988-7
R. Mitra, S. Sharma, Proactive data routing using controlled mobility of a mobile sink in wireless sensor networks. Comput. Electr. Eng. 70, 21–36 (2018). https://doi.org/10.1016/j.compeleceng.2018.06.001
J. Wang, J. Cao, R.S. Sherratt et al., An improved ant colony optimization-based approach with mobile sink for wireless sensor networks. J. Supercomput. 74(12), 6633–6645 (2018). https://doi.org/10.1007/s11227-017-2115-6
R. Akl, U. Sawant, Grid-based coordinated routing in wireless sensor networks, in 4th IEEE Consumer Communications and Networking Conference (CCNC ‘07) (2007), pp. 860–864
S. Sharma, On energy efficient routing protocols for wireless sensor networks. Ph.D. thesis. National Institute of Technology Rourkela; 2016
V. Arulkumar, C. Selvan, V. Vimal Kumar, Big data analytics in healthcare industry. An analysis of healthcare applications in machine learning with big data analytics. IGI Glob. Big Data Anal. Sustain. Comput. 8(3) (2019)
V. Arulkumar, C. Puspha Latha, D. Dasig, Jr, Concept of implementing big data in smart city: applications, services, data security in accordance with Internet of Things and AI. Int. J. Recent Technol. Eng. 8(3)
V. Arulkumar, M.A. Lakshmi, B.H. Rao, Super resolution and demosaicing based self learning adaptive dictionary image denoising framework, in 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS) (2021), pp. 1891–1897. https://doi.org/10.1109/ICICCS51141.2021.9432182
V. Arulkumar, An intelligent face detection by corner detection using special morphological masking system and fast algorithm, in 2021 2nd International Conference on Smart Electronics and Communication (ICOSEC) (2021), pp 1556–1561
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Senthil Kumar, S., Naveeth Babu, C., Arthi, B., Aruna, M., Charlyn Pushpa Latha, G. (2022). Energy Efficient Data Accumulation Scheme Based on ABC Algorithm with Mobile Sink for IWSN. In: Jacob, I.J., Kolandapalayam Shanmugam, S., Bestak, R. (eds) Expert Clouds and Applications. Lecture Notes in Networks and Systems, vol 444. Springer, Singapore. https://doi.org/10.1007/978-981-19-2500-9_10
Download citation
DOI: https://doi.org/10.1007/978-981-19-2500-9_10
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-2499-6
Online ISBN: 978-981-19-2500-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)