Improved DV-Hop based on parallel and compact whale optimization algorithm for localization in wireless sensor networks
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In this article , the authors proposed an algorithm with parallel and compact techniques based on Whale Optimization Algorithm (PCWOA) to improve DV-Hop performance and save memory consumption by reducing the original population.Abstract:
Improving localization performance is one of the critical issues in Wireless Sensor Networks (WSN). As a range-free localization algorithm, Distance Vector-Hop(DV-Hop) is well-known for its simplicity but is hindered by its low accuracy and poor stability. Therefore, it is necessary to improve DV-Hop to achieve a competitive performance. However, the comprehensive performance of WSN is limited by computing and storage capabilities of sensor nodes. In this paper, we propose an algorithm with parallel and compact techniques based on Whale Optimization Algorithm (PCWOA) to improve DV-Hop performance. The compact technique saves memory consumption by reducing the original population. The parallel techniques enhance the ability to jump out of local optimization and improve the solution accuracy. The proposed algorithm is tested on CEC2013 benchmark functions and compared with some popular algorithms and compact algorithms. Experimental results show that the improved algorithm achieves competitive results over compared algorithms. Finally, simulation research is conducted to verify the localization performance of our proposed algorithm. read more
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References
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The Whale Optimization Algorithm
Seyedali Mirjalili,Andrew Lewis +1 more
TL;DR: Optimization results prove that the WOA algorithm is very competitive compared to the state-of-art meta-heuristic algorithms as well as conventional methods.
Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization
Ponnuthurai Nagaratnam Suganthan,Nikolaus Hansen,Jing Liang,Kalyanmoy Deb,Y. P. Chen,Anne Auger,Santosh Tiwari +6 more
TL;DR: This special session is devoted to the approaches, algorithms and techniques for solving real parameter single objective optimization without making use of the exact equations of the test functions.
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Ad hoc positioning system (APS)
Dragos Niculescu,Badri Nath +1 more
TL;DR: This work is proposing APS - a distributed, hop by hop positioning algorithm, that works as an extension of both distance vector routing and GPS positioning in order to provide approximate location for all nodes in a network where only a limited fraction of nodes have self location capability.
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The compact genetic algorithm
TL;DR: The compact genetic algorithm (cGA) is introduced which represents the population as a probability distribution over the set of solutions and is operationally equivalent to the order-one behavior of the simple GA with uniform crossover.
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Hybrid Whale Optimization Algorithm with Simulated Annealing for Feature Selection
Majdi Mafarja,Seyedali Mirjalili +1 more
TL;DR: The experimental results confirm the efficiency of the proposed approaches in improving the classification accuracy compared to other wrapper-based algorithms, which insures the ability of WOA algorithm in searching the feature space and selecting the most informative attributes for classification tasks.
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