By Topic

Joint routing, scheduling and channel assignment in multi-power multi-radio 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

3 Author(s)
Jinbao Li ; School of Computer Science and Technology, Heilongjiang University, Harbin, Heilongjiang 150080, China ; Xiaohang Guo ; Longjiang Guo

Power control is a complex issue in routing since the increase of transmission power supplies more opportunities to select optimal routes due to the fact that more links are available. However, conversely, it also implies higher interference and hence decreases the performance of routing. Since multi-radio multi-channel schemes can efficiently mitigate interferences through allowing more concurrent transmissions, therefore, it is worth to investigate the routing scheme in Multi-Power Multi-Radio (MPMR) wireless sensor networks (WSNs). In this paper, we study the joint routing, scheduling, channel assignment and power control problem in MPMR WSNs, which is proven a NP-Hard problem. We first formulate the optimal routing problem as a linear programming problem. Subsequently, we develop a distributed routing protocol based on the random walk method which can efficiently decrease the computational complexity in large-scale WSNs by avoiding solving the linear programming problem. Theoretical analysis and simulations show that the routing based on MPMR can improve the data transmission efficiency and the proposed cross-layer routing scheme significantly reduces the energy consumption and the end-to-end transmission delay.

Published in:

30th IEEE International Performance Computing and Communications Conference

Date of Conference:

17-19 Nov. 2011