Earticle

초록

영어

Sensor network has lot applications in the early warning and assistant of disaster environment such as debris flows, floods and forest fires. However, such disaster environment pose an interesting challenge for data collection since sensor nodes may be destroyed unpredictably and centrally, resulting in the decrease of data persistence in the network. Growth Codes Protocol (GCP) first focuses on increase sensor network data persistent in the disaster. However, the completely random data transmission way in GCP may cause a large number of invalid data transmissions and therefore, the efficiency of data collection of the protocol is not ideal in the late stage of data collection. In this paper, we propose an efficient data collection protocol (DGCP) to maximize sensor network data persistence by changing the completely random data transmission way. Packet classification mechanism and a novel dynamic probability model of data transmission in DGCP are proposed to control the effective direction of data flow. Furthermore, we found that the parameter optimization problem of the probabilistic model is a problem of searching the optimal solution in a mathematical view. Based on this property, we propose a genetic algorithm to optimize the dynamic probability model. The performance of the proposed DGCP is shown by a comparative experimental study. When compared with GCP, our DGCP has better performance in a variety of environments

목차

Abstract
 1. Introduction
 2. Related Works
 3. Network Model
 4. About GA Parameters
 5. DGCP
  5.1. Data Packet Classification Mechanism
  5.2. A Novel Data Transmission Probability Model
  5.3. DGCP
 6. Experimental Results
 7. Conclusions
 References

키워드

저자

• Jian Wan [ Department of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China / Zhejiang University of Science and Technology, Hangzhou, China / Key Laboratory of Complex Systems Modeling and Simulation, Ministry of Education, Hangzhou, China ]
• Li Yang [ Department of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China ]
• Wei Zhang [ Department of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China / Key Laboratory of Complex Systems Modeling and Simulation, Ministry of Education, Hangzhou, China ]
• Huayou Si [ Department of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, China / Key Laboratory of Complex Systems Modeling and Simulation, Ministry of Education, Hangzhou, China ]
• Jin Feng [ PLA the Rocket Force Command College，Wuhan，China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Future Generation Communication and Networking

• 간기

  격월간

• pISSN

  2233-7857

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605