Leader selection for minimizing convergence error in leader-follower systems: A supermodular optimization approach

  • Andrew Clark
  • , Linda Bushnell
  • , Radha Poovendran

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

In leader-follower systems, follower nodes receive inputs from a set of leader nodes, exchange information, and update their states according to an iterative algorithm. In such algorithms, the node states may deviate from their desired values before the algorithm converges, leading to disruptions in network performance. In this paper, we study the problem of choosing leader nodes in order to minimize convergence errors. We first develop a connection between a class of weighted averaging algorithms and random walks on graphs, and then show that the convergence error is a supermodular function of the set of leader nodes. Based on the supermodularity of the convergence error, we derive efficient algorithms for selecting leader nodes that are within a provable bound of the optimum. Our approach is demonstrated through a simulation study.

Original languageEnglish
Title of host publication2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2012
Pages111-115
Number of pages5
StatePublished - 2012
Event2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2012 - Paderborn, Germany
Duration: May 14 2012May 18 2012

Publication series

Name2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2012

Conference

Conference2012 10th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, WiOpt 2012
Country/TerritoryGermany
CityPaderborn
Period05/14/1205/18/12

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