The algorithm lends itself for processing in a massively distributed environment. A synchronous relaxation method (SRM) is proposed, based on the k-coloring ...

Abstract. We design and analyze a fully distributed algorithm for convex constrained optimization in networks without any consistent naming infrastructure.

This paper studies a class of network optimization problems where the objective function is the summation of individual agents' convex functions and their ...

We propose two approaches to design efficient distributed algorithms to solve the network optimization problem. Our first approach consists of trans- forming ...

The algorithm lends itself for processing in a massively distributed environment. A synchronous relaxation method (SRM) is proposed, based on the k-coloring ...

Abstract. We describe a distributed algorithm for convex constrained optimization in networks without any consistent naming infrastructure.

This paper describes the implementation of a distributed relaxation algorithm for strictly convex network problems on a massively parallel computer and ...

We design and analyze a fully distributed algorithm for convex constrained optimization in networks without any consistent naming infrastructure.

This thesis is concerned with the design of distributed algorithms for solving optimization problems. The particular scenario we consider is a network with P ...

We describe a distributed algorithm for convex constrained optimization in networks without any consistent naming infrastructure. The algorithm produces an ...