Distributed Optimization in an Energy-Constrained Network Using a Digital Communication Scheme
Abstract
We consider a distributed optimization problem where n nodes, S_I,I\in{1,...,n}), wish to minimize a common strongly convex function f(x),x=[x_1,...,x_n]^T, and suppose that node S_I only has control of variable x_I. The nodes locally update their respective variables and periodically exchange their values over noisy channels. Previous studies of this problem have mainly focused on the convergence issue and the analysis of convergence rate. In this work, we focus on the communication energy and study its impact on convergence. In particular, we study the minimum amount of communication energy required for nodes to obtain an \epsilon-minimizer of f(x) in the mean square sense.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 22, 2009
- Accession Number
- ADA500118
Entities
People
- Alireza Razavi
- Zhi-quan Luo
Organizations
- University of Minnesota