Multi-objective Data Aggregation for Clustered Wireless Sensor Networks

  • Sukhchandan Randhawa
  • Sushma Jain
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 710)


Maximizing the energy efficiency is one of the major challenges in Wireless Sensor Networks. Research works have shown that by cluster formation of nodes, energy can be more efficiently used. In this research work, a Multi-objective Data Aggregation Clustering (MDAC) technique is proposed based on multi-objective optimization approach. Non-dominated Sorting Genetic Algorithm-II is utilized for cluster formation which can consider the several objective functions defined simultaneously. The main objectives are to minimize the communication cost among cluster heads, base station and cluster members and also to maximize the number of nodes within a cluster. The selection of CH nearer to BS is also avoided in order to prevent the hot spot problem. NSGA-II presents different solutions in a solution set which result in different topologies. Every solution in a solution set represents the best solution based on objective functions. BS considers every solution instance in solution set and selects the most suitable solution based on the desired criteria. The experimental evaluation results show that the proposed MDAC technique performs better than existing multi-objective clustering techniques in terms of throughput, total energy consumption, network lifetime, number of active nodes, data received at BS and variation in network lifetime and energy with varying selection choices of NSGA-II algorithm.


Wireless sensor networks Load balancing Data aggregation Clustering NSGA-2 Multi-objective optimization 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Computer Science and Engineering DepartmentThapar UniversityPunjabIndia

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