By Topic

Location Service Based on K-Hop Clustering Algorithm for Heterogeneous Ad Hoc 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
$31 $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)
Zhou Jiangwei ; Sch. of Electron. & Inf. Eng., Xi''an Jiaotong Univ., Xi''an, China ; Feng Boqin,

Many works has researched on homogeneous ad hoc networks. This paper is focused on heterogeneous ad hoc networks. In such networks, two types of nodes are discussed. One type is location server which provides location service, and the other type is general node. A location server can be an individual device or be attached to a host which has the capabilities of providing location service. A location server has the characteristic that it is stationary or moves at a very low speed during the whole task. Based on such networks, we combine location service with k-hop clustering algorithm to provide location service for general nodes. Location service messages between location servers and general nodes are all unicast packets, which avoids global broadcast like other location service. Moreover, location update messages are only triggered by the status change of a node. So the control overhead decreases dramatically on the condition that the quality of location service is guaranteed. Moreover, geographical forwarding is modified to appropriate new structure networks, which improves the network¿s performance considerably. The simulation results show that high mobility adaptation and good scalability are achieved.

Published in:

Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on  (Volume:1 )

Date of Conference:

19-20 Dec. 2008