By Topic

A Fast and Effective Multidimensional Scaling Approach for Node Localization in Wireless Sensor Networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Latsoudas, G. ; Tech. Univ. of Crete, Crete ; Sidiropoulos, N.D.

Given a set of pairwise distance estimates between nodes, it is often of interest to generate a map of node locations. This is an old nonlinear estimation problem that has recently drawn interest in the signal processing community, due to the emergence of wireless sensor networks. Sensor maps are useful for estimating the spatial distribution of measured phenomena, and for routing purposes. We propose a two-stage algorithm that combines algebraic initialization and gradient descent. In particular, we borrow an algebraic solution known as Fastmap from the database literature, adapt it to the sensor network context, and motivate the placement of anchor/pivot nodes on the edges of the network. When all nodes can estimate their distance from the anchors, the overall algorithm offers very competitive performance at low complexity (quadratic in the number of nodes).

Published in:

Signal Processing, IEEE Transactions on  (Volume:55 ,  Issue: 10 )