TY - JOUR
T1 - K-Coverage Model Based on Genetic Algorithm to Extend WSN Lifetime
AU - Elhoseny, Mohamed
AU - Tharwat, Alaa
AU - Farouk, Ahmed
AU - Hassanien, Aboul Ella
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/8
Y1 - 2017/8
N2 - Currently, wireless sensor networks (WSNs) are extensively used in target monitoring applications. Classical target coverage methods often assume that the environment is perfectly known, and each target is covered by only one sensor. Such algorithms, however, are inflexible, especially if a sensor died, i.e., ran out of energy, and hence, a target may need to be covered by more than one sensor, which is known as the K-coverage problem. The K-coverage problem is a time and energy consuming process, and the organization between sensors is required all the time. To address this problem, this article proposes a K-coverage model based on genetic algorithm to extend a WSN lifetime. In the search for the optimum active cover, different factors such as targets positions, the expected consumed energy, and coverage range of each sensor are taken into account. A set of experiments were conducted using different K-coverage cases. Compared to some state-of-the-art methods, the proposed model improved the WSN's performance regarding to the amount of the consumed energy, the network lifetime, and the required time to switch between different covers.
AB - Currently, wireless sensor networks (WSNs) are extensively used in target monitoring applications. Classical target coverage methods often assume that the environment is perfectly known, and each target is covered by only one sensor. Such algorithms, however, are inflexible, especially if a sensor died, i.e., ran out of energy, and hence, a target may need to be covered by more than one sensor, which is known as the K-coverage problem. The K-coverage problem is a time and energy consuming process, and the organization between sensors is required all the time. To address this problem, this article proposes a K-coverage model based on genetic algorithm to extend a WSN lifetime. In the search for the optimum active cover, different factors such as targets positions, the expected consumed energy, and coverage range of each sensor are taken into account. A set of experiments were conducted using different K-coverage cases. Compared to some state-of-the-art methods, the proposed model improved the WSN's performance regarding to the amount of the consumed energy, the network lifetime, and the required time to switch between different covers.
KW - genetic algorithm
KW - K-coverage
KW - Sensor networks
KW - target monitoring
KW - wirless sensor network (WSN) lifetime
UR - http://www.scopus.com/inward/record.url?scp=85144244810&partnerID=8YFLogxK
U2 - 10.1109/LSENS.2017.2724846
DO - 10.1109/LSENS.2017.2724846
M3 - Article
AN - SCOPUS:85144244810
SN - 2475-1472
VL - 1
JO - IEEE Sensors Letters
JF - IEEE Sensors Letters
IS - 4
M1 - 7973054
ER -