International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

International Journal of Computer Networks and Applications (IJCNA)

International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

Probabilistic Based Optimized Adaptive Clustering Scheme for Energy-Efficiency in Sensor Networks

Author NameAuthor Details

Vasudha, Anoop Kumar

Vasudha[1]

Anoop Kumar[2]

[1]Department of Computer Science Engineering, Banasthali Vidyapith, Rajasthan, India

[2]Department of Computer Science Engineering, Banasthali Vidyapith, Rajasthan, India

Abstract

The key factor affecting the life span of the sensor network when node battery capacity is constrained is communication energy utilization. Although these networks are commonly used, they still require research to make full use of their outstanding features in communication. The utilization of energy is a major issue for which an optimization strategy to minimize energy usage and enhance the service life of the network is recommended. It was achieved by cultivating the energy balance of all Sensor Nodes (SNs) in clusters to reduce the dissipation of energy during data transmission. The aim of this paper is to implement an optimized refined probabilistic methodology to address the issue of how to conserve energy, maintain a balanced system throughput, and extend the lifespan of sensor network. The suggested scheme strengthens the Cluster Head (CH) selection threshold by taking into account the node's residual power, distance between the node, Base Station (BS), node dormancy mechanism and CH Re-election process. The proposed technique employs clustering with set time frame for transmission, which minimizes count of nodes involved in actual data transfer and will increase the lifespan. The proposed methodology helps to choose energy-aware CHs based on a fitness feature that takes SN's remaining energy and the neighboring SN's energy number. Furthermore, the proposed protocol L-DDRI’s (LEACH -Distance Degree Residual Index) efficiency is measured against other common contemporary routing protocols such as Low-energy adaptive clustering hierarchy (LEACH), Uneven Clustering Strategy (UCS) and Distributed Energy-Efficient Clustering (DEEC). Analytical research and extensive simulation demonstrate shows improvement of proposed protocol L-DDRI in terms of lifespan, number of CHs, energy utilization, performance and overall reliability of the network and number of packets sent to Base station other existing technique.

Index Terms

Energy Efficiency

Cluster Head Selection

Distance Degree Residual Index (DDRI)

Threshold

Reference

  1. 1.
    I. Sohn, J. Lee, S. H. Lee, "Low-Energy Adaptive Clustering Hierarchy Using Affinity Propagation for Wireless Sensor Networks," in IEEE Communications Letters, vol. 20, no. 3, pp. 558-561, March 2016. doi: 10.1109/LCOMM.2016.2517017.
  2. 2.
    Alnawafa, E., Marghescu, I., “New Energy Efficient Multi-Hop Routing Techniques for Wireless Sensor Networks: Static and Dynamic Techniques”, Sensors 2018, 18, 1863. https://doi.org/10.3390/s18061863
  3. 3.
    Hongju Cheng, Zhihuang Su, Naixue Xiong, Yang Xiao, “Energy-efficient node scheduling algorithms for wireless sensor networks using Markov Random Field model”,Information Sciences,Volume 329, pp.461–477, 2016.doi.org/10.1016/j.ins.2015.09.039.
  4. 4.
    D. C. Hoang, P. Yadav, R. Kumar and S. K. Panda, "Real-Time Implementation of a Harmony Search Algorithm-Based Clustering Protocol for Energy-Efficient Wireless Sensor Networks," in IEEE Transactions on Industrial Informatics, vol. 10, no. 1, pp. 774-783, Feb. 2014, doi: 10.1109/TII.2013.2273739.
  5. 5.
    Noh, Y.; Lee, D., “BCoPS: An energy-efficient routing protocol with coverage preservation”, IET Communications 2017, Volume 11, Issue 12, pp. 1933 – 1940, 24 August 2017.
  6. 6.
    Hongxia Miao, Xuanxuan Xiao, Bensheng Qi and Kang Wang, "Improvement and application of LEACH Protocol based on Genetic Algorithm for WSN," 2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD), Guildford, UK, 7–9 September 2015, pp. 242-245, 2015. doi: 10.1109/CAMAD.2015.7390517.
  7. 7.
    Zhang, Yiming; Liu, Mandan; Liu, Qingwei., "An Energy-Balanced Clustering Protocol Based on an Improved CFSFDP Algorithm for Wireless Sensor Networks" Sensors 18, no. 3: 881, 2018. https://doi.org/10.3390/s18030881
  8. 8.
    M. Shurman, N. Awad, M. F. Al-Mistarihi and K. A. Darabkh, "LEACH enhancements for wireless sensor networks based on energy model," 2014 IEEE 11th International Multi-Conference on Systems, Signals & Devices (SSD14), pp. 1–4, 2014. doi: 10.1109/SSD.2014.6808823.
  9. 9.
    Mazumdar, N, Om, H., “Distributed fuzzy approach to unequal clustering and routing algorithm for wireless sensor networks”. International Journal of Communication Systems, Vol. 31, Issue 12, 2018. doi.org/10.1002/dac.3709
  10. 10.
    Ding, XX., Ling, M., Wang, ZJ. & Song, F., “DK-LEACH: An Optimized Cluster Structure Routing Method Based on LEACH in Wireless Sensor Networks”. Wireless Personal Communications, Volume 96, pp 6369-6379, 2017.https://doi.org/10.1007/s11277-017-4482-y
  11. 11.
    Mao Ye, Chengfa Li, Guihai Chen and J. Wu, "EECS: an energy efficient clustering scheme in wireless sensor networks," PCCC 2005. 24th IEEE International Performance, Computing, and Communications Conference, pp. 535-540, 2005. doi: 10.1109/PCCC.2005.1460630.
  12. 12.
    Y. Liu, J. Gao, Y. Jia, et al., “A cluster maintenance algorithm based on LEACH-DCHS protocol”, Computer Engineering & Applications 45(30), Palladam, INDIA, pp.165–166, 2009.
  13. 13.
    H. Jiman, K. Joongjin, L. Sangjun, K. Dongseop, & Y. Sangho, “T-LEACH: The method of threshold-based cluster head replacement for wireless sensor networks”, Information Systems Frontiers, volume 11, pp.513-521, 2009.
  14. 14.
    P. Zhiyong & L. Xiaojuan, “The improvement and simulation of LEACH protocol for WSNs”, IEEE International Conference on Software Engineering and Service Sciences, Beijing, China, pp. 500-503, 2010.
  15. 15.
    R. Hou, W. Ren and Y. Zhang, "A Wireless Sensor Network Clustering Algorithm Based on Energy and Distance," 2009 Second International Workshop on Computer Science and Engineering, pp. 439-442, 2009. doi: 10.1109/WCSE.2009.705.
  16. 16.
    S. H. Kang and T. Nguyen, "Distance Based Thresholds for Cluster Head Selection in Wireless Sensor Networks," in IEEE Communications Letters, vol. 16, no. 9, pp. 1396-1399, September 2012. doi: 10.1109/LCOMM.2012.073112.120450.
  17. 17.
    Haseeb, K., Bakar, K.A., Abdullah, A.H. & Darwish, T., “Adaptive energy aware cluster-based routing protocol for wireless sensor networks”, Wireless Network, Vol 23, pp 1953–1966, 2017.
  18. 18.
    Smaragdakis, G., Matta, I., & Bestavros, A., “2004-05-31 SEP: A Stable Election Protocol for clustered heterogeneous wireless sensor networks” OpenBU, 2004.
  19. 19.
    M M Islam,M A Matin, T K Mondol, “Extended Stable Election Protocol(SEP) for Three level Hierarchical Clustered Heterogeneous WSN”, IET onference on Wireless Sensor Systems(WSS 2012), 18-19 June 2012, London, UK, 2012.
  20. 20.
    F. Javeed, A. Naz, T. N. Qureshi, A. Basit and N. Iltaf, "A review on variant clustering designs in heterogeneous WSNs," 2015 National Software Engineering Conference (NSEC), pp. 48-54, 2015.doi: 10.1109/NSEC.2015.7396344.
  21. 21.
    Parul Saini, Ajay K Sharma, “Energy Efficient Scheme for Clustering Protocol Prolonging the Lifetime of Heterogeneous Wireless Sensor Networks”, International Journal of Computer Applications, Volume 6– No.2, pp30-36, September 2010.
  22. 22.
    Omari, M., & Laroui, S., “Simulation, comparison and analysis of wireless sensor networks protocols: LEACH, LEACH -C, LEACH-1R, and HEED”, 2015 4th International Conference Electrical Engineering (ICEE), pp. 1–5, 2015.
  23. 23.
    Y.-Z. Li, A.-L. Zhang, Y.-Z. Liang, “Improvement of LEACH protocol for wireless sensor networks”, Third International Conference on Instrumentation Measurement Computer Communication and Control, pp. 322–326, 2013.
  24. 24.
    H.Liang, S.Yang, L. Li, et al. “ Research on routing optimization of WSNs based on improved LEACH protocol” EURASIP Journal on Wireless Communications and Networking , pp-194, 2019.
  25. 25.
    Remika Ngangbam, Ashraf Hossain & Alok Shukla, “Improved low energy adaptive clustering hierarchy and its optimum cluster head selection”, International Journal of Electronics, 107:3, 390-402,2019. doi:10.1080/00207217.2019.1661023
  26. 26.
    Jain K., Kumar A., Jha C.K. (2020) Probabilistic-Based Energy-Efficient Single-Hop Clustering Technique for Sensor Networks. In: Bansal J., Gupta M., Sharma H., Agarwal B. (eds) Communication and Intelligent Systems. ICCIS 2019. Lecture Notes in Networks and Systems, vol 120. Springer, Singapore, 2020. https://doi.org/10.1007/978-981-15-3325-9_27
  27. 27.
    K.Jain, and A.Kumar, “An optimal RSSI-based cluster-head selection for sensor networks’, International Journal of Adaptive and Innovative Systems, Vol.2 No.4, pp.349 - 361, 2019.
  28. 28.
    Alghamdi, T.A., “Energy efficient protocol in wireless sensor network: optimized cluster head selection model”, Telecommunication Systems, volume 74, pages331–345, 2020.
  29. 29.
    Ramadhani Sinde, Feroza Begum, Karoli Njau, Shubi Kaijage | Kuei-Ping Shih (Reviewing editor), “Lifetime improved WSN using enhanced-LEACH and angle sector-based energy-aware TDMA scheduling”, Cogent Engineering, 7:1, 1795049, 2020, DOI: 10.1080/23311916.2020.1795049
  30. 30.
    Amir Abbas Baradaran, Keivan Navi, “HQCA-WSN: High-quality clustering algorithm and optimal cluster head selection using fuzzy logic in wireless sensor networks”, Fuzzy Sets and Systems, Vol 389, pp 114-144,2020.
  31. 31.
    Hamid Reza Farahzadi, Mostafa Langarizadeh,Mohammad Mirhosseini, Seyed Ali Fatemi Aghda, “An improved cluster formation process in wireless sensor network to decrease energy consumption”, Wireless Networks, volume 27, issue 2, pages1077–1087, 2021.
  32. 32.
    Safa’a S. SalehTamer F. MabroukRana A. Tarabishi, “An improved energy-efficient head election protocol for clustering techniques of wireless sensor network”, Egyptian Informatics Journal,2021, doi.org/10.1016/j.eij.2021.01.003
  33. 33.
    TM Behera,UC Samal, S.K. Mohapatra, “Energy-efficient modified LEACH protocol for IoT application”, IET Wireless Sensor System 2018, Vol. 8, Issue 5, pp.223–228, 2018.
  34. 34.
    M.S.Obaidat, S.Misra, “Principles of Wireless Sensor Networks”, Cambridge Univ. Press: Cambridge, UK, 2014.
  35. 35.
    D. Kim and Y. Chung, "Self-Organization Routing Protocol Supporting Mobile Nodes for Wireless Sensor Network," First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06), pp. 622-626, 2006. doi: 10.1109/IMSCCS.2006.265.
  36. 36.
    Hicham Ouchitachen, Abdellatif Hair, Najlae Idrissi, “Improved multi-objective weighted clustering algorithm in Wireless Sensor Network”, Egyptian Informatics Journal, volume 18, Issue 1, pp 45–54, 2017.
  37. 37.
    Vasudha and A. Bhola, "Investigations on Lifetime and Energy Optimization of WSN based on Hybrid Clustering Algorithm," 2019 6th International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India, 2019, pp. 932-937, 2019.
SCOPUS
SCImago Journal & Country Rank