| Autor: |
Zhenchun Wei, Meng Li, Qing Zhao, Zengwei Lyu, Siwei Zhu, Zhen Wei |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 7, Pp 156217-156227 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2019.2949284 |
| Popis: |
The limited lifespan of the traditional Wireless Sensor Networks (WSNs) has always restricted the broad application and development of WSNs. The current studies have shown that the wireless power transmission technology can effectively prolong the lifetime of WSNs. In most present studies on charging schedules, the sensor nodes will be charged once they have energy consumption, which will cause higher cost and lower networks utility. It is assumed in this paper that the sensor nodes in Wireless Rechargeable Sensor Networks (WRSNs) will be charged only after its energy is lower than a certain value. Each node has a charging time window and is charged within its respective time window. In large-scale wireless sensor networks, single mobile charger (MC) is difficult to ensure that all sensor nodes work properly. Therefore, it is propoesd in this paper that the multiple MCs which are used to replenish energy for the sensor nodes. When the average energy of all the sensor nodes falls below the upper energy threshold, each MC begins to charge the sensor nodes. The genetic algorithm has a great advantage in solving optimization problems. However, it could easily lead to inadequate search. Therefore, the genetic algorithm is improved by 2-opt strategy. And then multi-MC charging schedule algorithm with time windows based on genetic algorithm is proposed and simulated. The simulation results show that the algorithm designed in this paper can timely replenish energy for each sensor node and minimize the total charging cost. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
