A modified differential evolution-based combined routing and sleep scheduling scheme for lifetime maximization of wireless sensor networks

2014 ◽  
Vol 19 (3) ◽  
pp. 637-659 ◽  
Author(s):  
Souvik Kundu ◽  
Swagatam Das ◽  
Athanasios V. Vasilakos ◽  
Subhodip Biswas
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Differential Evolution ◽  
Wireless Sensor ◽  
Sleep Scheduling ◽  
Lifetime Maximization ◽  
Scheduling Scheme

scholarly journals Differential Evolution for Lifetime Maximization of Heterogeneous Wireless Sensor Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Yulong Xu ◽  
Jian’an Fang ◽  
Wu Zhu ◽  
Wenxia Cui
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Differential Evolution ◽  
Wireless Sensor ◽  
Lifetime Maximization ◽  
Solution Quality ◽  
Data Set ◽  
Heterogeneous Wireless Sensor Networks ◽  
Disjoint Sets ◽  
Generate Test Data

Maximizing the lifetime of wireless sensor networks (WSNs) is a hot and significant issue. However, using differential evolution (DE) to research this problem has not appeared so far. This paper proposes a DE-based approach that can maximize the lifetime of WSN through finding the largest number of disjoint sets of sensors, with every set being able to completely cover the target. Different from other methods in the literature, firstly we introduce a common method to generate test data set and then propose an algorithm using differential evolution to solve disjoint set covers (DEDSC) problems. The proposed algorithm includes a recombining operation, which performs after initialization and guarantees at least one critical target’s sensor is divided into different disjoint sets. Moreover, the fitness computation in DEDSC contains both the number of complete cover subsets and the coverage percent of incomplete cover subsets. Applications for sensing a number of target points, named point-coverage, have been used for evaluating the effectiveness of algorithm. Results show that the proposed algorithm DEDSC is promising and simple; its performance outperforms or is similar to other existing excellent approaches in both optimization speed and solution quality.

A novel sleep scheduling scheme in green wireless sensor networks

2014 ◽  
Vol 71 (3) ◽  
pp. 1067-1094 ◽  
Author(s):  
Jing Zhang ◽  
Li Xu ◽  
Shuming Zhou ◽  
Xiucai Ye
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Sleep Scheduling ◽  
Scheduling Scheme
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