Author
Listed:
- Arpit Tripathi
(Indian Institute of Information Technology and Management Gwalior, India)
- Pulkit Gupta
(Indian Institute of Information Technology and Management Gwalior, India)
- Aditya Trivedi
(Indian Institute of Information Technology and Management Gwalior, India)
- Rahul Kala
(Indian Institute of Information Technology and Management Gwalior, India)
Abstract
The ease of use and re-configuration in a wireless network has played a key role in their widespread growth. The node deployment problem deals with an optimal placement strategy of the wireless nodes. This paper models a wireless sensor network, consisting of a number of nodes, and a unique sink to which all the information is transmitted using the shortest connecting path. Traditionally the systems have used Genetic Algorithms for optimal placement of the nodes that usually fail to give results in problems employing large numbers of nodes or higher areas to be covered. This paper proposes a hybrid Genetic Programming (GP) and Genetic Algorithm (GA) for solving the problem. While the GP optimizes the deployment structure, the GA is used for actual node placement as per the GP optimized structure. The GA serves as a slave and GP serves as master in this hierarchical implementation. The algorithm optimizes total coverage area, energy utilization, lifetime of the network, and the number of nodes deployed. Experimental results show that the algorithm could place the sensor nodes in a variety of scenarios. The placement was found to be better than random placement strategy as well as the Genetic Algorithm placement strategy.
Suggested Citation
Arpit Tripathi & Pulkit Gupta & Aditya Trivedi & Rahul Kala, 2011.
"Wireless Sensor Node Placement Using Hybrid Genetic Programming and Genetic Algorithms,"
International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 7(2), pages 63-83, April.
Handle:
RePEc:igg:jiit00:v:7:y:2011:i:2:p:63-83
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jiit00:v:7:y:2011:i:2:p:63-83. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.