Gossip-based density estimation in dynamic heterogeneous wireless sensor networks
by Hadi Tabatabaee Malazi; Kamran Zamanifar; Andrei Pruteanu; Stefan Dulman
International Journal of Autonomous and Adaptive Communications Systems (IJAACS), Vol. 7, No. 1/2, 2014

Abstract: The density estimation of diverse sensor types in a heterogeneous sensor network is an important service that can be used in clustering schemes, node redeployment and sleep scheduling strategies. Similar to any wireless sensor network service, energy efficiency is one of the main requirements. The service has to provide an updated estimation at each node. Network dynamics, especially node mobility, introduce new challenges. Moreover, churn makes the problem even more complicated. In this paper we introduce a new approach called Gossip based Density Estimation (GDE) for heterogeneous dynamic networks. The devised method is able to cope with node mobility and churn, as well as redeployment of new nodes. It is fully distributed and adaptive to network dynamics. We analyse the effect of mobility as well as increased scale in the number of clusters and the quantity of nodes. The simulation results support the idea that our algorithm has a fast convergence speed and provides more accurate estimation compared to similar approaches.

Online publication date: Tue, 21-Oct-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Autonomous and Adaptive Communications Systems (IJAACS):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com