Cluster-based Sleep Scheduling Protocol for Mobile Wireless Sensors Network

Majlesi Journal of Electrical Engineering

مقاله 3، دوره 16، شماره 2، شهریور 2022، صفحه 31-39   

نوع مقاله: Review Article

شناسه دیجیتال (DOI): 10.30486/mjee.2022.696493

نویسندگان

Omnia Mezghani^{* 1}؛ Mahmoud Mezghani²

¹LAB-STA, National Engineering School of Sfax, Tunisia

²LAB-STA, National Engineering School of Sfax, Sfax University, Sfax, Tunisia

چکیده

Mobile Wireless Sensors Networks (MWSNs) are used in several applications presenting difficult/dangerous environment and/or requiring the movement of sensors after initial deployment. Optimizing the use of the limited energy resource in a MWSN is a key challenge for researchers to maintain longer network survival. This paper attempts to provide an energy-efficient data routing solution for large MWSNs. The aim of this work is to propose a cluster-based scheduling protocol for MWSN.  The network is firstly divided into an optimal number of clusters according to sensors connectivity. Secondly, a sleep scheduling algorithm is proposed to save the energy consumption by turning off the overlapped nodes in the sensing field. This method is distributed among sensor nodes in each cluster. It is based on the perimeter coverage level of mobile sensor nodes to schedule their activities according to their weights. The weight is used to balance the energy consumption for all sensor nodes in a cluster. The proposed approach ranges from sensors deployment, their organization to their operational mode. Experimental results demonstrate that the proposed cluster-based scheduling algorithm, based on the perimeter coverage of sensors, provides higher energy efficiency and longer lifetime coverage for MWSNs as compared to other protocols.

کلیدواژه‌ها

Mobile WSN؛ energy consumption؛ Clustering؛ sleep-scheduling؛ perimeter coverage

مراجع

[1] P. L. Nguyen, T. H. Nguyen and K. Nguyen, “A Path-Length Efficient, Low-Overhead, Load-Balanced Routing Protocol for Maximum Network Lifetime in Wireless Sensor Networks with Holes,” Journal of Sensors, Vol. 20, No. 9, pp.1-32, 2020.

[2] H. Mehdi, H. Zarrabi, A. KhademZadeh, and A. M. Rahmani, “Self-Adaptive Sampling Rate to Improve Network Lifetime using Watchdog Sensor and Context Recognition in Wireless Body Sensor Networks,” Majlesi Journal of Electrical Engineering, Vol.14, No. 3, pp. 11-22, 2020.

[3] O. Mezghani and M. Abdellaoui, “Mobi-sim: A Simulation Environment for Mobile Wireless Sensors Network,” presented at the 3rd International Conference on Control, Decision and Information Technologies, Malte, 2016.

[4] O. Mezghani and M. Abdellaoui, “Improving Network Lifetime with Mobile LEACH Protocol for Wireless Sensors Network,” presented at the 15th International conference on Sciences and Techniques of Automatic control & computer engineering, Hammamet, Tunisia, 2014.

[5] S. Zafar, A. Bashir and S. A. Chaudhry, “Mobility-Aware Hierarchical Clustering in MobileWireless Sensor Networks,” IEEE Access, Vol. 7, pp. 20394-20403, 2019.

[6] D. P. Shantala and B. P. Vijayakumar, “Clustering in Mobile Wireless Sensor Networks: A Review,” International Journal of Advanced Networking & Applications, Vol. 8, No. 1, pp. 134-136, 2016.

[7] J. Sumathi and R. L. Velusamy, “A review on distributed cluster based routing approaches in mobile wireless sensor networks,” Journal of Ambient Intelligence and Humanized Computing, No. 12, pp. 835-849, 2020.

[8] M. Mezghani, “An efficient multi-hops clustering and data routing forWSNs based on Khalimsky shortest paths,” Journal of Ambient Intelligence and Humanized Computing, Vol. 10, No. 9, pp. 1275-1288, 2019.

[9] J. Amutha, S. Sharma and J. Nagar, “WSN Strategies Based on Sensors, Deployment, Sensing Models, Coverage and Energy Efficiency: Review, Approaches and Open Issues,” Journal of Wireless Personal Communications, Vol. 111, No. 4, pp. 1089-1115, 2020.

[10] O. Mezghani and M. Abdellaoui, “Efficient Clustering Protocol Based on Stochastic Matrix & MCL and Data Routing for Mobile Wireless Sensors Network,” International Journal of Communication Networks and Information Security, Vol. 10, No. 1, pp. 188-198, 2018.

[11] Y. Wu, X. Y. Li, Y. H. Liu and W. Lou, “ Energy-Efficient Wake-Up Scheduling for Data Collection and Aggregation,” Journal of IEEE Transactions on Parallel and Distributed Systems, Vol. 21, No. 2, pp. 275-287, 2010.

[12] X. Xu, X. Y. Li and M. Song, “Efficient Aggregation Scheduling in Multihop Wireless Sensor Networks with SINR Constraints,” IEEE Transactions on Mobile Computing, Vol. 12, No. 12, pp. 2518-2528, 2013.

[13] S. S. Ponde and S. S. Lomte, “Adaptive Sleep Scheduling for Cluster Based Wireless Sensor Networks for Precision Agriculture,” presented at the International Conference on Advances in Communication and Computing Technology, Sangamner, India, 2018.

[14] R. Elhabyan, W. Shi and M. St-Hilaire, “Coverage Protocols for Wireless Sensor Networks: Review and Future Directions,” Journal of Communications and Networks, Vol. 17, No. 4, pp. 1-16, 2019.

[15] R. Elhabyan, W. Shi and M. St-Hilaire, “A full area coverage guaranteed, energy efficient network configuration strategy for 3d wireless sensor networks,” presented at the IEEE Canadian Conference on Electrical Computer Engineering, Quebec, QC, Canada, 2018.

[16] M. Y. Ruwaida and H. H. Sokaena, “Unequal Clustering and Scheduling in Wireless Sensor Network using Advance Genetic Algorithm,” Journal of Physics Conference Series, Vol. 1530, pp. 1-9, 2020.

[17] G. Ollos and R. Vida, “Sleep Scheduling Protocol for Mobile WSNs,” presented at the 73rd IEEE Vehicular Technology Conference, Spring, Yokohama, Japan, 2011.

[18] S. Jothi and M. Chandrasekaran, “Energy Efficient Sleep-Scheduling for Cluster Based Aggregation in Wireless Sensor Network,” Asian Journal of Information Technology, Vol. 15, No. 19, pp. 3718-3724, 2016.

[19] O. Mezghani and M. Abdellaoui, “Intelligent Wireless Sensors Network. Multitasks-Generic-Intelligent-Efficiency-Secure WSNs and theirs Applications,” LAMBERT Academic Publishing (LAP), pp. 108-141, 2017.

[20] K. S. Hung and K. S. Lui, “Perimeter Coverage Scheduling in Wireless Sensor Networks Using Sensors with a Single Continuous Cover Range,” EURASIP Journal on Wireless Communications and Networking, No. 1, pp. 1-17, 2010.

[21] K. Idrees, K. Deschinkel, M. Salomon and R. Couturier, “Perimeter based coverage optimization to improve lifetime in wireless sensor networks,” Journal of Engineering Optimization, Vol. 48, No. 11, pp. 1951-1972, 2016.

[22] S. Jothi and M. Chandrasekaran, “Energy Effcient Sleep-Scheduling for Cluster Based Aggregation in Wireless Sensor Network,” Asian Journal of Information Technology, Vol. 15, No. 19, pp. 3718-3724, 2016.