Data Aggregation through Hybrid Optimal Probability in Wireless Sensor Networks
DOI:
https://doi.org/10.4108/eetsis.4996Keywords:
WSN, Data Collection, Energy Efficient, Probabalistic, LEACH, Secure ProtocolAbstract
INTRODUCTION: In the realm of Wireless Sensor Networks (WSN), effective data dissemination is vital for applications like traffic alerts, necessitating innovative solutions to tackle challenges such as broadcast storms.
OBJECTIVES: This paper proposes a pioneering framework that leverages probabilistic data aggregation to optimize communication efficiency and minimize redundancy.
METHODS: The proposed adaptable system extracts valuable insights from the knowledge base, enabling dynamic route adjustments based on application-specific criteria. Through simulations addressing bandwidth limitations and local broadcast issues, we establish a robust WSN-based traffic information system.
RESULTS: By employing primal-dual decomposition, the proposed approach identifies optimal packet aggregation probabilities and durations, resulting in reduced energy consumption while meeting latency requirements.
CONCLUSION: The efficacy of proposed method is demonstrated across various traffic and topology scenarios, affirming that probabilistic data aggregation effectively mitigates the local broadcast problem, ultimately leading to decreased bandwidth demands.
References
Alkwai LM, Mohammed Aledaily AN, Almansour S, Alotaibi SD, Yadav K, Lingamuthu V. Vampire Attack Mitigation and Network Performance Improvement Using Probabilistic Fuzzy Chain Set with Authentication Routing Protocol and Hybrid Clustering-Based Optimization in Wireless Sensor Network. MPE. 2022; 2022:1-11.
Bhaskarwar RV, Pete DJ. Energy efficient clustering with compressive sensing for underwater wireless sensor networks. PPNA. 2022; 15;2289-2306.
Balamurugan A, Janakiraman S, Priya MD, Malar ACJ. Hybrid Marine predators optimization and improved particle swarm optimization-based Optimization cluster routing in wireless sensor networks (WSNs). CC. 2022; 19(6):219-247.
Yadav R, Sreedevi I, Gupta D. Bio-Inspired Hybrid Optimization Algorithms for Energy Efficient Wireless Sensor Networks: A Comprehensive Review. Electronics. 2022; 11(10):1-22.
Senthil GA, Raaza A, Kumar N. Internet of Things Energy Efficient Cluster-Based Routing Using Hybrid Particle Swarm Optimization for Wireless Sensor Network. WPC. 2022; 122(3):2603-2619.
Gamal M, Mekky NE, Soliman HH, Hikal NA. Enhancing the Lifetime of Wireless Sensor Networks Using Fuzzy Logic LEACH Technique-Based Particle Swarm Optimization. IEEE Access. 2022; 10:36935-36948.
Sahoo B M, Pandey H.M, Amgoth T. A Genetic Algorithm Inspired Optimized Cluster Head Selection Method in Wireless Sensor Networks. SEC. 2022; 75.
Yadav RK, Mahapatra RP. Hybrid metaheuristic algorithm for optimal cluster head selection in a wireless sensor network. PMC, 2022; 79.
Prakash PS, Kavitha D, Reddy PC. Delay-aware relay node selection for cluster-based wireless sensor networks. Measurement: Sensors. 2022; 24.
Amutha J, Sharma S, Sharma SK. An energy-efficient cluster based hybrid optimization algorithm with static sink and mobile sink node for Wireless Sensor Networks. ESA. 2022; 203.
Vanitha CN, Malathy S, Dhanaraj RK, Nayyar A. Optimized Pollard Route Deviation and Route Selection using Bayesian Machine Learning Techniques in Wireless Sensor Networks. Computer Networks. 2022; 216.
Muthukumar S, Rajesh DH. Optimal Cluster Based Routing Technique for Wireless Sensor Networks using Hybrid Optimization Algorithm for Maximizing Life of Sensors. WPC. 2022; 125:3479-3500.
Khalaf OI, Romero CAT, Hassan S, Iqbal MT. Mitigating hotspot issues in heterogeneous wireless sensor networks. JS. 2022; 2022:1-14.
Hegde K, & Dilli R. Wireless Sensor Networks: Network Life Time Enhancement using an Improved Grey Wolf Optimization Algorithm. ES. 2022; 19:186-197.
Manoharan G, Sumathi A. Efficient routing and performance amelioration using Hybrid Diffusion Clustering Scheme in heterogeneous wireless sensor network. IJCS. 2022; 35(13).
Gautam AK, Yadav R. Energy efficient hybrid routing protocol for Wireless Sensor Networks Using AI Technique. EAI ETSIS. 2022; 9(35):1-9.
Khera S, Turk, N., Kaur, N: HC-WSN - A Hibernated Clustering based framework for improving energy efficiency of wireless sensor networks. MTA. 2022; 82(3):3387-3894.
Joshi P, Kumar S, Raghuvanshi AS. A performance efficient joint clustering and routing approach for heterogeneous wireless sensor networks. ES. 2023; 40(5).
Rajesh L, Mohan HS. Adaptive Group Teaching Based Clustering and Data Aggregation with Routing in Wireless Sensor Network. WPC. 2022; 122(2):1839-1866.
Alom, M. K., Hossan, A., Choudhury, P. K: Improved Zonal Stable Election Protocol (IZ-SEP) for hierarchical clustering in heterogeneous wireless sensor networks. E-Prime-AEEE. 2022; 2.
Prasanth A, Sabeena G, Sowndarya, Pushpalatha, N. An artificial intelligence approach for energy-aware intrusion detection and secure routing in internet of things-enabled wireless sensor networks. CCPE. 2023; 35(23).
Paruthi Ilam Vazhuthi P, Prasanth A, Manikandan SP, Devi Sowndarya KK. A hybrid ANFIS reptile optimization algorithm for energy-efficient inter- cluster routing in Internet of Things-enabled Wireless Sensor Networks. PPNA. 2023; 16:1049-1068.
Vazhuthi P, Manikandan SP, Prasanth A. An Energy-Efficient Auto Clustering Framework for Enlarging Quality of Service in Internet of Things- enabled Wireless Sensor Networks using Fuzzy Logic System. CCPE. 2022; 34(25).
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Copyright (c) 2023 S Balaji, S Jeevanandham, Mani Deepak Choudhry, M Sundarrajan, Rajesh Kumar Dhanaraj
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