Charging path optimization for wireless rechargeable sensor network
- PDF / 756,936 Bytes
- 10 Pages / 595.276 x 790.866 pts Page_size
- 59 Downloads / 221 Views
Charging path optimization for wireless rechargeable sensor network Qian Wang 1 & Zhihua Cui 1 & Lifang Wang 1 Received: 1 June 2020 / Accepted: 17 September 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract In wireless rechargeable sensor networks(WRSNs), charging path planning becomes more and more important. In this paper, a charging path planning model based on high-dimensional multi-objective optimization is proposed, which takes life cycle, distance, energy consumption and charging time into consideration. At the same time, an improved algorithm is proposed to improve the crossover mode and diversity of the reference-point-based many-objective evolutionary algorithm following nondominated sorting genetic algorithm(NSGA)&NSGA-II framework(we call it NSGA-III) for charging path planning. In the end, the validity of the charging process and the rationality of the charging path are verified by experimental comparison. Keywords WRSNs . MCs . Charging path . Improved NSGA-III
1 Introduction As the internet of things is more and more widely used, wireless sensor technology has been constantly improved, which is the most important and basic technology of information acquisition. A mass of sensor nodes constitutes a multi-hop selforganized network system through wireless correspondence, which called wireless sensor networks, or WSNs for short. At present, WSNs are widely applied in biomedical health monitoring [1, 2], structural monitoring [3] and localization techniques [4], etc. A general sensor network is comprised of a lot of nodes and a base station. These nodes have the capacity of data processing and transmission. However, in processes of data transmission, the energy consumption will be an unavoidable issue. Every sensor node has limited energy powered by batteries [5]. It is hard to replace the battery in harsh conditions. Too many death nodes could shorten network lifetime. From this perspective, researchers have put forward different approaches prolonging the life span of entire network.
* Zhihua Cui [email protected] Qian Wang [email protected] Lifang Wang [email protected] 1
School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan 030024, China
In general, three methods can be used to deal with the problem. One of the methods is to save energy which designs a low power routing protocol to prolong the WSN’s life cycle. The impact on network performance cannot be ignored, although some protocols had made efforts to as little as possible the level of energy consumption in the WSN, So now, the limited lifetime is still the crucial factor to ensure sensors work steadily and efficiently. Besides, some scholars are committed to collecting energy for wireless sensor networks. They have carried out many kinds of research on getting collecting it come from ambient, for example, wave power [6], solar power [7] as well as thermal energy [8]. Nonetheless, whether the energy harvested is unstable and uncontrollable becomes the most commo
Data Loading...