Optimisation of energy efficient cellular learning automata algorithm for heterogeneous wireless sensor networks

C.P. Subha and S. Malarkkan

International Journal of Networking and Virtual Organisations, 2017, vol. 17, issue 2/3, 170-183

Abstract: Wireless sensor networks is an effective sensing network consisting of a large number of small sensors and small embedded devices each with sensing, computation and communication capabilities for gathering data in various environments. Energy consumption is considered to be an important issue in the design of wireless sensor networks. To overcome the above limitation, efficient method like cellular learning automata (CLA) and heterogeneous-hybrid energy efficient distributed (H-HEED) technique have been used in distributed dynamic clustering networks. The existing method will be the cellular learning automata in which cluster heads will be selected through several stages by considering various parameters with homogeneous nodes. The proposed method selects the cluster head in a similar way and based on the residual energy of the nodes with heterogenous nodes. Their performance is observed using NS2 simulator and comparison has been made to find the best efficient method.

Keywords: cellular automata; learning automata; heterogeneous-hybrid energy efficient distributed; H-HEED; clustering; wireless sensor networks; WSNs; dynamic; irregular cellular learning automata; distributed dynamic clustering; residual energy. (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=85526 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijnvor:v:17:y:2017:i:2/3:p:170-183

Access Statistics for this article

More articles in International Journal of Networking and Virtual Organisations from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().