TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
A Learning Automata-based Algorithm for Area Coverage Problem in Directional Sensor Networks |
| 영문제목(English Title) |
A Learning Automata-based Algorithm for Area Coverage Problem in Directional Sensor Networks |
| 저자(Author) |
Zhimin Liu
Zhangdong Ouyang
|
| 원문수록처(Citation) |
VOL 11 NO. 10 PP. 4804 ~ 4822 (2017. 10) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Coverage problem is a research hot spot in directional sensor networks (DSNs). However, the major problem affecting the performance of the current coverage-enhancing strategies is that they just optimize the coverage of networks, but ignore the maximum number of sleep sensors to save more energy. Aiming to find an approximate optimal method that can cover maximum area with minimum number of active sensors, in this paper, a new scheduling algorithm based on learning automata is proposed to enhance area coverage, and shut off redundant sensors as many as possible. To evaluate the performance of the proposed algorithm, several experiments are conducted. Simulation results indicate that the proposed algorithm have effective performance in terms of coverage enhancement and sleeping sensors compared to the existing algorithms. |
| 키워드(Keyword) |
Coverage enhancement
energy consumption
directional sensor networks
learning automat
|
| 파일첨부 |
PDF 다운로드
|
