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Smart Deployment of Sensor Nodes Using SA & GFA
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- 발행기관
- 보안공학연구지원센터(IJGDC) 바로가기
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- 간행물
- International Journal of Grid and Distributed Computing SCOPUS 바로가기
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- 통권
- Vol.9 No.2 (2016.02)바로가기
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- 페이지
- pp.157-168
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A271596
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- In wireless sensor networks, network connectivity problems and sensor coverage are mainly affected by the restricted communication and sensing range of the nodes. To solve all these problems, many studies have been undertaken till now but most of these works is limited to be applied to the real environments because these do not consider various environmental factors that affect wireless sensor network deployment. In this paper, we propose a node deployment strategy that considers environmental factors and the number of nodes for surveillance .Deployment of the sensor nodes, and relay nodes considering all features of the surveillance and reconnaissance sensor networks as well as environmental factors. Smarty deploying the sensor nodes is very important if we are considering the performance of wireless sensor nodes (wsn). This paper focuses on real time deployment of sensor nodes using unmanned aerial vehicle (UAV). Smart deployment has importance in battlefield surveillance, disaster monitoring, environmental and habitat monitoring etc. It plays a very important role mainly in disasters affecting areas like flood affected or fire affected forests for sensing different conditions and physical data out there. The objective of this paper is to deploy sensor nodes smartly only in terrain of interest not in fire or water so that it can conserve environment and can reduce the loss of sensor nodes from being deploy in fire or water. Image segmentation of the images captured by camera situated on a board of UAV.. Comparison of these optimization tools SA and GFA are presented here for different images. Simulation results show that GFA performs better than SA when compared with no. of individuals and SA is faster than GFA.
목차
Abstract
I. Introduction
II. Bio Inspired Algorithm: Detailed
III. SA and GFA Based Image Thresholding for Autonomous Deployment
IV. Numerical Simulation and Results
V. Conclusion and Future Work
References
키워드
Simulated Annealing Algorithm (SA) image thresholding Gravitational Field Algorithm (GFA) Wireless Sensor Networks (WSNs).저자
간행물 정보
발행기관
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- 발행기관명
- 보안공학연구지원센터(IJGDC) [Science & Engineering Research Support Center, Republic of Korea(IJGDC)]
- 설립연도
- 2006
- 분야
- 공학>컴퓨터학
- 소개
- 1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업
간행물
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- 간행물명
- International Journal of Grid and Distributed Computing
- 간기
- 격월간
- pISSN
- 2005-4262
- 수록기간
- 2008~2016
- 십진분류
- KDC 505 DDC 605
이 권호 내 다른 논문 / International Journal of Grid and Distributed Computing Vol.9 No.2
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