IJCNIS Vol. 13, No. 5, 8 Oct. 2021
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Clustering, Energy efficiency, Error prediction, Routing, WSN
Cluster-based protocols are best for applications that require reliability and a continuous functioning environment with a sustainable lifetime of WSN. The dynamic nature of the sensor node makes energy conservation a challenging issue. Sensor node scheduled based on sensing error for energy conservation compromise the accuracy of prediction. The high data accuracy achieved using a single duty cycle controller at each node with compromised throughput and increased routing overhead. Duty Cycle Controller managing a more number of control messages at the network level leads to control packet interference with data packet transmission, increasing packet drop and minimizing throughput. Also, the single-duty cycle controller at the network level leads to increased control overhead. The proposed multilevel cluster-based approach focuses on the appropriate cluster design, selection of cluster head, and sensor nodes scheduling based on sensing error. The proposed method applies a multi-duty cycle controller at each cluster level, and control messages handled are related to nodes in a cluster. Thus has less interference and packet drop leading to maximum throughput than existing methods. The simulation results demonstrated that the proposed method with sensor nodes scheduled at individual cluster levels using a multi-duty cycle controller exhibited improved network lifetime, throughput, and reduced energy consumption compared with the state-of-the-art techniques.
Patil Yogita Dattatraya, Jayashree Agarkhed, Siddarama Patil, "Multi Duty Cycle Scheduled Routing in Wireless Sensor Network-lifetime Maximization", International Journal of Computer Network and Information Security(IJCNIS), Vol.13, No.5, pp.55-67, 2021. DOI: 10.5815/ijcnis.2021.05.05
[1] Younis, O., & Fahmy, S. (2004, March). Distributed clustering in ad-hoc sensor networks: A hybrid, energy-efficient approach. In IEEE INFOCOM 2004 (Vol. 1). IEEE.
[2] Agarkhed, J., Patil Y. D., & Patil, S. (2020). A Study of Wireless Sensor Networks to Comprehend their Relevance to Different Applications. Journal of Telecommunications and Information Technology,(vol.3)(pp. 1-11)
[3] Patil Y. D., & Agarkhed, J. (2015). A review on various issues and applications in wireless sensor networks. International Journal of Science and Research, 4(11), 2518-22.
[4] Mainwaring, A., Culler, D., Polastre, J., Szewczyk, R., & Anderson, J. (2002, September). Wireless sensor networks for habitat monitoring. In Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications (pp. 88-97).
[5] Kumar, P., Arunachalam, V. P., & Karthik, S. (2012). A Cluster Based Multipath Routing Protocol for Energy Conservation in Wireless Sensor Networks. European Journal of Scientific Research, 78(4), (pp. 559-569).
[6] Amrinder Singh and Sandeep Kautish. Study and comparative analysis of various energy efficiency techniques in wireless sensor networks.
[7] Li, Y., Ye, J., & Zhu, Y. H. (2012). An Energy-Aware Data Gathering Protocol for Wireless Sensor Networks Using Data Correlations. In 2011 International Conference in Electrics, Communication and Automatic Control Proceedings (pp. 75-83). Springer, New York, NY.
[8] Huang, J., Hong, Y., Zhao, Z., & Yuan, Y. (2017). An energy-efficient multi-hop routing protocol based on grid clustering for wireless sensor networks. Cluster Computing, 20(4), (pp. 3071-3083).
[9] Kumar, S., Ranjan, P., Ramaswami, R., & Tripathy, M. R. (2017). Resource efficient clustering and next hop knowledge based routing in multiple heterogeneous wireless sensor networks. International Journal of Grid and High Performance Computing (IJGHPC), 9(2), (pp. 1-20).
[10] Haseeb, K., Bakar, K. A., Abdullah, A. H., & Darwish, T. (2017). Adaptive energy aware cluster-based routing protocol for wireless sensor networks. Wireless Networks, 23(6), (pp. 1953-1966).
[11] Wang, J., Cao, J., Ji, S., & Park, J. H. (2017). Energy-efficient cluster-based dynamic routes adjustment approach for wireless sensor networks with mobile sinks. The Journal of Supercomputing, 73(7), (pp. 3277-3290).
[12] Agrakhed, J., Biradar, G. S., & Mytri, V. D. (2012, September). Adaptive multi constraint multipath routing protocol in wireless multimedia sensor network. In 2012 International Conference on Computing Sciences (pp. 326-331). IEEE.
[13] Elhoseny, M., Elleithy, K., Elminir, H., Yuan, X., & Riad, A. (2015). Dynamic clustering of heterogeneous wireless sensor networks using a genetic algorithm, towards balancing energy exhaustion. International Journal of Scientific & Engineering Research, 6(8), 1243-1252.
[14] Vijayalakshmi, K., & Anandan, P. (2019). A multi objective Tabu particle swarm optimization for effective cluster head selection in WSN. Cluster computing, 22(5), (pp. 12275-12282).
[15] Raman, C. J., & James, V. (2019). FCC: Fast congestion control scheme for wireless sensor networks using hybrid optimal routing algorithm. Cluster Computing, 22(5), (pp. 12701-12711).
[16] He, T., Krishnamurthy, S., Luo, L., Yan, T., Gu, L., Stoleru, R., ... & Abdelzaher, T. F. (2006). Vigilnet: An integrated sensor network system for energy-efficient surveillance. ACM Transactions on Sensor Networks (TOSN), 2(1), (pp. 1-38).
[17] Liu, H., Chandra, A., & Srivastava, J. (2006, April). eSENSE: energy efficient stochastic sensing framework for wireless sensor platforms. In 2006 5th International Conference on Information Processing in Sensor Networks (pp. 235-242). IEEE.
[18] Patil Yogita Dattatraya´a, Jayashree Agarkhed, and Siddarama R Patil.(2015) Error prediction scheduling for energy eļ¬cient routing in wireless sensor network. 8(5), (pp. 1893-1902).
[19] Zhang, Q., Fu, L., Gu, Y. J., Gu, L., Cao, Q., Chen, J., & He, T. (2013). Collaborative scheduling in dynamic environments using error inference. IEEE transactions on parallel and distributed systems, 25(3), (pp. 591-601).
[20] Luo, H., Wang, J., Sun, Y., Ma, H., & Li, X. Y. (2010, June). Adaptive sampling and diversity reception in multi-hop wireless audio sensor networks. In 2010 IEEE 30th International Conference on Distributed Computing Systems (pp. 378-387). IEEE.
[21] Yun, Z., Bai, X., Xuan, D., Lai, T. H., & Jia, W. (2010). Optimal Deployment Patterns for Full Coverage and $ k $-Connectivity $(k\leq 6) $ Wireless Sensor Networks. IEEE/ACM transactions on networking, 18(3), (pp. 934-947).
[22] Wang, X., Xing, G., Zhang, Y., Lu, C., Pless, R., & Gill, C. (2003, November). Integrated coverage and connectivity configuration in wireless sensor networks. In Proceedings of the 1st international conference on Embedded networked sensor systems (pp. 28-39).
[23] Zhou, Z., Das, S., & Gupta, H. (2004, October). Connected k-coverage problem in sensor networks. In Proceedings. 13th International Conference on Computer Communications and Networks (IEEE Cat. No. 04EX969) (pp. 373-378). IEEE.
[24] Zhang, Q., Gu, Y., He, T., & Sobelman, G. E. (2008, April). Cscan: A correlation-based scheduling algorithm for wireless sensor networks. In 2008 IEEE International Conference on Networking, Sensing and Control (pp. 1025-1030). IEEE.
[25] Muhammad Noman Riaz, "Clustering Algorithms of Wireless Sensor Networks: A Survey", International Journal of Wireless and Microwave Technologies, Vol.8, No.4, pp.40-53,2018.
[26] Saidu, M., Onwuka, E. N., Okwori, M., & Umar, A., "An enhanced leach routing algorithm for energy conservation in a wireless sensor network", International Journal of Wireless and Microwave Technologies, 6, pp.59-71, 2016.
[27] Anand Khandare, Abrar Alvi, "Efficient Clustering Algorithm with Enhanced Cohesive Quality Clusters", International Journal of Intelligent Systems and Applications, Vol.10, No.7, pp.48-57, 2018.
[28] Sundani, H., Li, H., Devabhaktuni, V., Alam, M., & Bhattacharya, P. (2011). Wireless sensor network simulators a survey and comparisons. International Journal of Computer Networks, 2(5), 249-265.
[29] Dattatraya, P. Y., & Agarkhed, J. (2016, March). Simulation an art of performance evaluation in wireless sensor networks. In 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT) (pp. 1-5). IEEE.
[30] Agarkhed, J., Dattatraya, P. Y., & Patil, S. R. (2017). Performance evaluation of QoS-aware routing protocols in wireless sensor networks. In Proceedings of the First International Conference on Computational Intelligence and Informatics (pp. 559-569). Springer, Singapore.