We develop a protocol for optimizing dynamic behavior of a network of simple electronic components, such as a sensor network, an ad hoc network of mobile devices, or a network of communication switches. This protocol requires only local communication and simple computations which are distributed among devices. The protocol is scalable to large networks. As a motivating example, we discuss a problem involving optimization of power consumption, delay, and buffer overflow in a sensor network. Our approach builds on policy gradient methods for optimization of Markov decision processes. The protocol can be viewed as an extension of policy gradient methods to a context involving a team of agents optimizing aggregate performance through asynchronous distributed communication and computation. We establish that the dynamics of the protocol approximate the solution to an ordinary differential equation that follows the gradient of the performance objective.

Ciamac Moallemi and Benjamin Van Roy
Publication Date
Advances in Neural Information Processing Systems 16

Full Citation

Moallemi, Ciamac and Benjamin Van Roy
. “Distributed optimization in adaptive networks.” In
Advances in Neural Information Processing Systems 16
, edited by
Sebastian Thrun, Lawrence K. Saul, and Bernhard Scholkopf
Cambridge, MA
MIT Press
, 2004.