An Energy Efficient and Scalable WSN with Enhanced Data Aggregation Accuracy
DOI:
https://doi.org/10.26636/jtit.2024.2.1510Keywords:
Wireless sensor networks, Data aggregation compression, Lempel-Ziv-Welch algorithm, Lossless compression, Scheduling, Energy consumptionAbstract
This paper introduces a method that combines the K-means clustering genetic algorithm (GA) and Lempel-Ziv-Welch (LZW) compression techniques to enhance the efficiency of data aggregation in wireless sensor networks (WSNs). The main goal of this research is to reduce energy consumption, improve network scalability, and enhance data aggregation accuracy. Additionally, the GA technique is employed to optimize the cluster formation process by selecting the cluster heads, while LZW compresses aggregated data to reduce transmission overhead. To further optimize network traffic, scheduling mechanisms are introduced that contribute to packets being transmitted from sensors to cluster heads. The findings of this study will contribute to advancing packet scheduling mechanisms for data aggregation in WSNs in order to reduce the number of packets from sensors to cluster heads. Simulation results confirm the system's effectiveness compared to other compression methods and non-compression scenarios relied upon in LEACH, M-LEACH, multi-hop LEACH, and sLEACH approaches.
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References
S. Yoo et al., "Technological Advances in Wireless Sensor Networks Enabling Diverse Internet of Things Applications", International Journal of Distributed Sensor Networks, vol. 14, no. 3, 2018. DOI: https://doi.org/10.1177/1550147718763220
View in Google Scholar
K. Lee and H. Lee, "An Energy-Efficient Cooperative Communication Method for Wireless Sensor Networks", International Journal of Distributed Sensor Networks, vol. 10, no. 3, p. 689-710, 2014. DOI: https://doi.org/10.1155/2014/689710
View in Google Scholar
L. Cao, Y. Yue, and Y. Zhang, "A Data Collection Strategy for Heterogeneous Wireless Sensor Networks Based on Energy Efficiency and Collaborative Optimization", Computational Intelligence and Neuroscience, vol. 2021, art. no. 9808449, 2021. DOI: https://doi.org/10.1155/2021/9808449
View in Google Scholar
M. Wu, L. Tan, and N. Xiong, "A Structure Fidelity Approach for Big Data Collection in Wireless Sensor Networks", Sensors, vol. 15, no. 1, pp. 248-273, 2014. DOI: https://doi.org/10.3390/s150100248
View in Google Scholar
G.P. Agbulu, G.J.R. Kumar, and A.V. Juliet, "A Lifetime-enhancing Cooperative Data Gathering and Relaying Algorithm for Cluster-based Wireless Sensor Networks", International Journal of Distributed Sensor Networks, vol. 16, no. 2, 2020. DOI: https://doi.org/10.1177/1550147719900111
View in Google Scholar
S. Harizan and P. Kuila, "Coverage and Connectivity Aware Energy Efficient Scheduling in Target Based Wireless Sensor Networks: An Improved Genetic Algorithm Based Approach", Wireless Networks, vol. 25, no. 4, pp. 1995-2011, 2019. DOI: https://doi.org/10.1007/s11276-018-1792-2
View in Google Scholar
A. Makris et al., "Evaluating the Effect of Compressing Algorithms for Trajectory Similarity and Classification Problems", GeoInformatica, vol. 25, no. 4, pp. 679-711, 2021. DOI: https://doi.org/10.1007/s10707-021-00434-1
View in Google Scholar
D. Meenakshi and S. Kumar, "Energy Efficient Hierarchical Clustering Routing Protocol for Wireless Sensor Networks", Advances in Computer Science and Information Technology. Networks and Communications, pp. 409-420, 2012. DOI: https://doi.org/10.1007/978-3-642-27299-8_43
View in Google Scholar
S.N. Sajedi, M. Maadani, and M.N. Moghadam, "F-LEACH: a Fuzzy-based Data Aggregation Scheme for Healthcare IoT Systems", Journal of Supercomputing, vol. 78, no. 5, pp. 1030-1047, 2022. DOI: https://doi.org/10.1007/s11227-021-03890-6
View in Google Scholar
P.M. Mwangi, J.G. Ndia, and G.M. Muketha, "Cluster Head Selection Algorithms for Enhanced Energy Efficiency in Wireless Sensor Networks: A Systematic Literature Review", International Journal of Computer Science & Engineering Survey, vol. 13, no. 3, 2022. DOI: https://doi.org/10.5121/ijcses.2022.13303
View in Google Scholar
Q. Ren and G. Yao, "An Energy-Efficient Cluster Head Selection Scheme for Energy-Harvesting Wireless Sensor Networks", Sensors, vol. 20, no. 1, art. no. 187, 2020. DOI: https://doi.org/10.3390/s20010187
View in Google Scholar
R. Rajagopalan and P.K. Varshney, "Data Aggregation Techniques in Sensor Networks: A Survey", IEEE Communications Surveys & Tutorials, vol. 8, no. 4, pp. 48-63, 2006. DOI: https://doi.org/10.1109/COMST.2006.283821
View in Google Scholar
D.P. Kumar, T. Amgoth, and C.S.R. Annavarapu, "Machine Learning Algorithms for Wireless Sensor Networks: A Survey", Information Fusion, vol. 49, pp. 1-25, 2019. DOI: https://doi.org/10.1016/j.inffus.2018.09.013
View in Google Scholar
L. Krishnamachari, D. Estrin, and S. Wicker, "The Impact of Data Aggregation in Wireless Sensor Networks", Proc. of 22nd International Conference on Distributed Computing Systems Workshops, IEEE, pp. 575-578, 2002.
View in Google Scholar
M. Kaur and A. Munjal, "Data Aggregation Algorithms for Wireless Sensor Network: A Review", Ad Hoc Networks, vol. 100, 2020. DOI: https://doi.org/10.1016/j.adhoc.2020.102083
View in Google Scholar
M. Al-Shalabi, M. Anbar, T.-C. Wan, and A. Khasawneh, "Variants of the Low-energy Adaptive Clustering Hierarchy Protocol: Survey, Issues and Challenges", Electronics, vol. 7, no. 8, art. no. 136, 2018. DOI: https://doi.org/10.3390/electronics7080136
View in Google Scholar
I. Yoon, H. Kim, and D. K. Noh, "Adaptive Data Aggregation and Compression to Improve Energy Utilization in Solar-powered Wireless Sensor Networks", Sensors, vol. 17, no. 6, art. no. 1226, 2017. DOI: https://doi.org/10.3390/s17061226
View in Google Scholar
O. Younis and S. Fahmy, "HEED: a Hybrid, Energy-efficient, Distributed Clustering Approach for ad hoc Sensor Networks", IEEE Transactions on Mobile Computing, vol. 3, no. 4, pp. 366-379, 2004. DOI: https://doi.org/10.1109/TMC.2004.41
View in Google Scholar
P. Jesus, C. Baquero, and P.S. Almeida, "A Survey of Distributed Data Aggregation Algorithms", IEEE Communications Surveys & Tutorials, vol. 17, no. 1, pp. 381-404, 2014. DOI: https://doi.org/10.1109/COMST.2014.2354398
View in Google Scholar
V. Freschi and E. Lattanzi, "A Study on the Impact of Packet Length on Communication in Low Power Wireless Sensor Networks under Interference", IEEE Internet of Things Journal, vol. 6, no. 2, pp. 3820-3830, 2019. DOI: https://doi.org/10.1109/JIOT.2019.2891841
View in Google Scholar
G. Vijayaraghavan, "Intereference Management in LTE-Advanced Heteogeneous Network", Ms. Thesis, Aalto University, Finland, 2015.
View in Google Scholar
C. La Palombara, V. Tralli, B.M. Masini, and A. Conti, "Relay-assisted Diversity Communications", IEEE Transactions on Vehicular Technology, vol. 62, no. 1, pp. 415-421, 2012. DOI: https://doi.org/10.1109/TVT.2012.2218841
View in Google Scholar
N.R. Saadallah and S.A. Alabady, "Using Hybrid GA/PSO-Mobile Sink to Improve Energy Efficiency and Network Lifetime for LEACH Protocol in WSNs", 2023 IEEE 13th International Conference on System Engineering and Technology (ICSET), Shah Alam, Malaysia, 2023. DOI: https://doi.org/10.1109/ICSET59111.2023.10295105
View in Google Scholar
Z. Yuan et al., "Energy Prediction for Energy-Harvesting Wireless Sensor: A Systematic Mapping Study", Electronics, vol. 12, no. 20, art. no. 4304, 2023. DOI: https://doi.org/10.3390/electronics12204304
View in Google Scholar
S. Roundy et al., "Power Sources for Wireless Sensor Networks", European Workshop on Wireless Sensor Networks, Berlin, Germany, 2004. DOI: https://doi.org/10.1007/978-3-540-24606-0_1
View in Google Scholar
F. Mazunga and A. Nechibvute, "Ultra-low Power Techniques in Energy Harvesting Wireless Sensor Networks: Recent Advances and Issues", Scientific African, vol. 11, art. no. e00720, 2021. DOI: https://doi.org/10.1016/j.sciaf.2021.e00720
View in Google Scholar
B. Kumar, U.K. Tiwari, and S. Kumar, "Energy Efficient Quad Clustering Based on K-means Algorithm for Wireless Sensor Network", 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC), Waknaghat, India, 2020. DOI: https://doi.org/10.1109/PDGC50313.2020.9315853
View in Google Scholar
A. Et-Taleby, B. Mohammed, and M. Benslimane, "Faults Detection for Photovoltaic Field Based on K-means, Elbow, and Average Silhouette Techniques through the Segmentation of a Thermal Image", International Journal of Photoenergy, art. no. 6617597, 2020. DOI: https://doi.org/10.1155/2020/6617597
View in Google Scholar
H. Harb et al., "K-means Based Clustering Approach for Data Aggregation in Periodic Sensor Networks", 2014 IEEE 10th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Larnaca, Cyprus, 2014. DOI: https://doi.org/10.1109/WiMOB.2014.6962207
View in Google Scholar
T.M. Behera et al., "Residual Energy-based Cluster-head Selection in WSNs for IoT Application", IEEE Internet of Things Journal, vol. 6, no. 3, pp. 5132-5139, 2019. DOI: https://doi.org/10.1109/JIOT.2019.2897119
View in Google Scholar
H.R. Ali and H.A. Lafta, "Energy Threshold-based Cluster Head Rotation for Routing Protocol in Wireless Sensor Networks", Journal of University of Babylon for Pure and Applied Sciences, vol. 26, no. 7, pp. 92-106, 2018. DOI: https://doi.org/10.29196/jubpas.v26i7.1416
View in Google Scholar
N.R. Saadallah, S.A. Alabady, and F. Al-Turjman, "Energy-Efficient Cluster Head Selection via Genetic Algorithm", Al-Rafidain Engineering Journal, pp. 12-25, 2024. DOI: https://doi.org/10.33899/rengj.2023.143955.1293
View in Google Scholar
M.A. Razzaque, C. Bleakley, and S. Dobson, "Compression in Wireless Sensor Networks: A Survey and Comparative Evaluation", ACM Transactions on Sensor Networks, vol. 10, no. 1, pp. 1-44, 2013. DOI: https://doi.org/10.1145/2528948
View in Google Scholar
J. Jeong et al., "A QoS-aware Data Aggregation in Wireless Sensor Networks", 2010 The 12th International Conference on Advanced Communication Technology (ICACT), 2010 (https://ieeexplore.ieee.org/document/5440486?arnumber=5440486).
View in Google Scholar
K.C. Barr and K. Asanović, "Energy-aware Lossless Data Compression", ACM Transactions on Computer Systems, vol. 24, no. 3, pp. 250-291, 2006. DOI: https://doi.org/10.1145/1151690.1151692
View in Google Scholar
M. Aslam et al., "Survey of Extended LEACH-Based Clustering Routing Protocols for Wireless Sensor Networks", 2012 IEEE 14th International Conference on High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems, Liverpool, UK, 2012. DOI: https://doi.org/10.1109/HPCC.2012.181
View in Google Scholar
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