Exploration of Heed Clustering Algorithm for Performance Improvement in Heterogenous WSNs

Nikita Gandotra*
Department of Computer Science & IT, University of Jammu, Jammu and Kashmir, India.
Periodicity:June - August'2019
DOI : https://doi.org/10.26634/jcom.7.2.16142

Abstract

Wireless Sensor Networks are extensively used for monitoring in difficult terrains since these could be easily deployed due to their small size and their ability to work on their own without additional equipment as they communicate in adhoc manner. Each node consists of an individual power source in the form of a battery and remains active in the network till its energy is exhausted. To extend the network lifetime and optimising the use of restricted power supply, clustering algorithms are widely used to group neighbouring nodes and work in small clusters imitating the behaviour of the actual network. Hybrid Energy Efficient Distributed Clustering (HEED) algorithm was proposed to address the limited power supply and the network lifetime in WSNs. HEED selects cluster heads periodically according to their residual energy and node degree. This paper suggests a few improvements in the original HEED algorithm and a new model has been proposed based on these improvements. The algorithms are analysed with both homogeneous and heterogeneous node batteries and it was found that the proposed model improves the average energy of each node and extends the network lifetime.

Keywords

Wireless Sensor Networks, Clustering Algorithm, HEED, residual energy

How to Cite this Article?

Gandotra, N.(2019). Exploration of Heed Clustering Algorithm for Performance Improvement in Heterogenous WSNs, i-manager's Journal on Computer Science, 7(2), 26-35. https://doi.org/10.26634/jcom.7.2.16142

References

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Pdf 35 35 200 20
Online 35 35 200 15
Pdf & Online 35 35 400 25

If you have access to this article please login to view the article or kindly login to purchase the article
Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.