Overlapping Multi-hop Clustering for Wireless Sensor Networks

Computer Science – Networking and Internet Architecture

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

Clustering is a standard approach for achieving efficient and scalable performance in wireless sensor networks. Traditionally, clustering algorithms aim at generating a number of disjoint clusters that satisfy some criteria. In this paper, we formulate a novel clustering problem that aims at generating overlapping multi-hop clusters. Overlapping clusters are useful in many sensor network applications, including inter-cluster routing, node localization, and time synchronization protocols. We also propose a randomized, distributed multi-hop clustering algorithm (KOCA) for solving the overlapping clustering problem. KOCA aims at generating connected overlapping clusters that cover the entire sensor network with a specific average overlapping degree. Through analysis and simulation experiments we show how to select the different values of the parameters to achieve the clustering process objectives. Moreover, the results show that KOCA produces approximately equal-sized clusters, which allows distributing the load evenly over different clusters. In addition, KOCA is scalable; the clustering formation terminates in a constant time regardless of the network size.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Overlapping Multi-hop Clustering for Wireless Sensor Networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Overlapping Multi-hop Clustering for Wireless Sensor Networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Overlapping Multi-hop Clustering for Wireless Sensor Networks will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-623683

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.