Dynamic Multi-hop Clustering in a Wireless Sensor Network: Performance Improvement

Dynamic Multi-hop Clustering in a Wireless Sensor Network: Performance Improvement A cluster-based model is preferable in wireless sensor network due to its ability to reduce energy consumption. However, managing the nodes inside the cluster in a dynamic environment is an open challenge. Selecting the cluster heads (CHs) is a cumbersome process that greatly affects the network performance. Although there are several studies that propose CH selection methods, most of them are not appropriate for a dynamic clustering environment. To avoid this problem, several methods were proposed based on intelligent algorithms such as fuzzy logic, genetic algorithm (GA), and neural networks. However, these algorithms work better within a single-hop clustering model framework, and the network lifetime constitutes a big issue in case of multi-hop clustering environments. This paper introduces a new CH selection method based on GA for both single-hop and the multi-hop cluster models. The proposed method is designed to meet the requirements of dynamic environments by electing the CH based on six main features, namely, (1) the remaining energy, (2) the consumed energy, (3) the number of nearby neighbors, (4) the energy aware distance, (5) the node vulnerability, and (6) the degree of mobility. We shall see how the corresponding results show that the proposed algorithm greatly extends the network lifetime. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Wireless Personal Communications Springer Journals

Dynamic Multi-hop Clustering in a Wireless Sensor Network: Performance Improvement

Loading next page...
 
/lp/springer_journal/dynamic-multi-hop-clustering-in-a-wireless-sensor-network-performance-0MVNENQgD7
Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media New York
Subject
Engineering; Communications Engineering, Networks; Signal,Image and Speech Processing; Computer Communication Networks
ISSN
0929-6212
eISSN
1572-834X
D.O.I.
10.1007/s11277-017-4023-8
Publisher site
See Article on Publisher Site

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

Monthly Plan

  • Read unlimited articles
  • Personalized recommendations
  • No expiration
  • Print 20 pages per month
  • 20% off on PDF purchases
  • Organize your research
  • Get updates on your journals and topic searches

$49/month

Start Free Trial

14-day Free Trial

Best Deal — 39% off

Annual Plan

  • All the features of the Professional Plan, but for 39% off!
  • Billed annually
  • No expiration
  • For the normal price of 10 articles elsewhere, you get one full year of unlimited access to articles.

$588

$360/year

billed annually
Start Free Trial

14-day Free Trial