Why Us? >>

  • - Open Access
  • - Peer-reviewed
  • - Rapid publication
  • - Lifetime hosting
  • - Free indexing service
  • - Free promotion service
  • - More citations
  • - Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.

 

Contact Us >>

WhatsApp  +86 18163351462(WhatsApp)
   
Paper Publishing WeChat
Book Publishing WeChat
(or Email:book@scirp.org)

Article citations

More>>

X. Wang, G. Xing, Y. Zhang, C. Lu, R. Pless and C. Gill, “Integrated Coverage and Connectivity Configuration in Wireless Sensor Networks,” Proceedings of the First International Conference on Embedded Networked Sensor Systems (Sen-Sys’03), 2003, p. 28.

has been cited by the following article:

  • TITLE: Optimal Node Scheduling for Desired Percentage of Coverage in Wireless Sensor Networks

    AUTHORS: Hamid Khosravi

    KEYWORDS: Wireless Sensor Networks; Connected Sensor Cover; Connectivity; Coverage; Energy Conservation

    JOURNAL NAME: Wireless Sensor Network, Vol.4 No.5, May 3, 2012

    ABSTRACT: Recent developments in wireless communication and embedded computing technologies have led to the advent of wireless sensor network technology. Hundreds of thousands of these micro sensors can be deployed in many areas including health, environment and battlefield in order to monitor the domain with desired level of accuracy. When wireless sensors are deployed in an area, the lifetime of the network should last as long as possible according to the original amount of energy. Therefore, reducing energy consumption in WSNs is of primary concern. We have proposed a node scheduling solution that solves the coverage and connectivity problem in sensor networks in an integrated manner. In this way we will divide network life time to finite number of rounds and in each round we will generate a coverage bitmap of sensors of the domain and based on this bitmap it will decided which sensors remain active or go to sleep. We will check the connection of the sensor network by using Laplacian of adjancy graph of active nodes in each round. Also the network will be capable of producing desired percentage of coverage by using coverage bitmap. We will define the connected coverage problem as an optimization problem and we will seek a solution for the problem by using Genetic Algorithm optimization method.