By Topic

Multi-objective optimization techniques in topology control of free space optical 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

5 Author(s)
Jifang Zhuang ; Dept. of Civil & Environ. Eng., Maryland Univ., College Park, MD, USA ; Casey, M.J. ; Milner, S.D. ; Gabriel, S.A.
more authors

To mitigate the effects of obscuration and attenuation, free space optical (FSO) wireless networks employ topology control to dynamically reconfigure node connectivity based on changes in link state. Our previous research in topology control has focused primarily on creating heuristics for computing an optimal topology either in the physical layer (minimize bit error rate) or in the network layer (minimize congestion). This research presents a multi-objective optimization formulation of the topology control problem whereby physical network cost and network layer congestion are jointly minimized. Our formulation uses a weighting method for specifying preference in the physical or network layer, based on existing heuristics for each respective layer. Discrete event simulation was used to perform an evaluation of the weighting method in our formulation. By studying scenarios with different normalization factors, number of nodes (N), and weight sampling, we have categorized the conditions in which the multi-objective optimization topology control formulation is inferior, superior or incomparable to using just the respective physical or network layer only formulations. The simulation results show that the combined topology solution is preferable to the individual heuristics in over 80% of cases. Finally, we present possible strategies for assigning preference, and obtaining a Pareto optimal solution.

Published in:

Military Communications Conference, 2004. MILCOM 2004. 2004 IEEE  (Volume:1 )

Date of Conference:

31 Oct.-3 Nov. 2004