Peer-to-peer Estimation over Wireless Sensor Networks via Lipschitz Optimization
2009 (English)In: 2009 INTERNATIONAL CONFERENCE ON INFORMATION PROCESSING IN SENSOR NETWORKS (IPSN 2009), NEW YORK: IEEE , 2009, 241-252 p.Conference paper (Refereed)
Motivated by a peer-to-peer estimation algorithm in which adaptive weights are optimized to minimize the estimation error variance, we formulate and solve a novel non-convex Lipschitz optimization problem that guarantees global stability of a large class of peer-to-peer consensus-based algorithms for wireless sensor network. Because of packet. losses, the solution of this optimization problem cannot be achieved efficiently with either traditional centralized methods or distributed Lagrangian message passing. The prove that the optimal solution can be obtained by solving a set of nonlinear equations. A fast distributed algorithm, which requires only local computations, is presented for solving these equations. Analysis and computer simulations illustrate the algorithm and its application to various network topologies.
Place, publisher, year, edition, pages
NEW YORK: IEEE , 2009. 241-252 p.
Lipschitz Optimization, Parallel and Distributed Computation, Wireless Sensor Networks, Distributed Estimation
IdentifiersURN: urn:nbn:se:kth:diva-26514ISI: 000275711800021ScopusID: 2-s2.0-71049143081ISBN: 978-142445108-1OAI: oai:DiVA.org:kth-26514DiVA: diva2:385811
8th International Symposium on Information Processing Sensor Networks San Francisco, CA, APR 13-16, 2009
QC 201101122011-01-122010-11-252012-02-02Bibliographically approved