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Solving the energy efficient coverage Problem in Wireless Sensor Networks: A Distributed Genetic Algorithm Approach with Hierarchical Fitness Evaluation

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ENERGIES 2018年第12期11卷

作者： Wang, Zi-Jia Zhan, Zhi-Hui Zhang, Jun Sun Yat Sen Univ Sch Data & Comp Sci Guangzhou 510006 Guangdong Peoples R China South China Univ Technol Sch Comp Sci & Engn Guangdong Prov Key Lab Computat Intelligence & Cy Guangzhou 510006 Guangdong Peoples R China

This paper proposed a distributed genetic algorithm (DGA) to solve the energy efficient coverage (EEC) problem in the wireless sensor networks (WSN). Due to the fact that the EEC problem is Non-deterministic Polynomial-Complete (NPC) and time-consuming, it is wise to use a nature-inspired meta-heuristic DGA approach to tackle this problem. The novelties and advantages in designing our approach and in modeling the EEC problems are as the following two aspects. Firstly, in the algorithm design, we realized DGA in the multi-processor distributed environment, where a set of processors run distributed to evaluate the fitness values in parallel to reduce the computational cost. Secondly, when we evaluate a chromosome, different from the traditional model of EEC problem in WSN that only calculates the number of disjoint sets, we proposed a hierarchical fitness evaluation and constructed a two-level fitness function to count the number of disjoint sets and the coverage performance of all the disjoint sets. Therefore, not only do we have the innovations in algorithm, but also have the contributions on the model of EEC problem in WSN. The experimental results show that our proposed DGA performs better than other state-of-the-art approaches in maximizing the number of disjoin sets.

关键词： wireless sensor networks energy efficient coverage distributed genetic algorithm

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A novel enhanced coverage optimization algorithm for effectively solving energy optimization problem in WSN

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Research Journal of Applied Sciences, Engineering and Technology 2014年第4期7卷 696-701页

作者： Senthil Kumar, M. Chaturvedi, Ashish Department of ECE CMJ University Shillong Meghalaya India Arni School of Computer Science and Applications Arni University Indora (Kathgarh) Himachal Pradesh India

In Wireless Sensor Networks (WSN), efficient-energy coverage (EEC) is one of the important issues for considering the (WSNs) implementation. In this study, we have developed the new algorithm ECO (Enhanced coverage Optimization) for solving the EEC problem effectively. The proposed algorithm uses three types of major work for effectively solving the problem. One of the three pheromones is the local pheromone, which helps an ant organize its coverage set with fewer sensors. The other two pheromones are global pheromones, one of which is used to optimize the number of required active sensors per Point of Interest (PoI) and the other is used to form a sensor set that has as many senses as an ant has selected the number of active sensors by using the former pheromone. This study also introduces one technique that leads to a more realistic approach to solving the EEC problem that is to utilize the probabilistic sensor detection model. The main goal of ECO is efficient coverage on target area with minimum energy consumption and increased network's lifetime. © Maxwell Scientific Organization, 2014.

关键词： Ant Colony Optimization (ACO) energy efficient coverage Point of interest (PoI) Probabilistic sensor detection Three types of pheromones

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