By Topic

Distributed algorithm for minimizing delay in multi-hop 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)
M. Farukh Munir ; EURECOM, Department of Mobile Communications, Sophia Antipolis, France ; Arzad A. Kherani ; F. Filali

We consider a wireless sensor network with n sensor nodes. The sensed data needs to be transferred in a multi-hop fashion to a common processing center. We consider the standard data sampling/sensing scheme where the sensor nodes have a sampling process independent of the transmission scheme. In this paper, we study the problem of optimizing the end-to-end delay in a multi-hop single-sink wireless sensor network. We prove that the delay-minimization objective function is strictly convex for the entire network. We then provide a distributed optimization framework to achieve the required objective. The approach is based on distributed convex optimization and deterministic distributed algorithm without feedback control. Only local knowledge is used to update the algorithmic steps. Specifically, we formulate the objective as a network level delay minimization function where the constraints are the reception-capacity and service-rate probabilities. Using the Lagrangian dual composition method, we derive a distributed primal-dual algorithm to minimize the delay in the network.We further develop a stochastic delay control primal-dual algorithm in the presence of noisy conditions. We also present its convergence and rate of convergence. The proposal is extensively evaluated by analysis and simulations.

Published in:

Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, 2009. WiOPT 2009. 7th International Symposium on

Date of Conference:

23-27 June 2009