Optimal Database Allocation in Finite Time with Efficient Communication and Transmission Stopping over Dynamic Networks

TL;DR

This paper introduces a distributed algorithm for optimal data allocation in dynamic wireless networks that converges in finite time, uses quantized information, and allows nodes to stop transmissions without global network knowledge.

Contribution

The paper presents a novel finite-time, quantized, event-driven distributed algorithm for optimal data sharing over dynamic networks, with no need for global parameters.

Findings

Algorithm converges to optimal data allocation with high probability.

Nodes can cease transmissions after reaching the optimal solution.

Operates effectively over random, dynamic network topologies.

Abstract

In this paper, we focus on the problem of data sharing over a wireless computer network (i.e., a wireless grid). Given a set of available data, we present a distributed algorithm which operates over a dynamically changing network, and allows each node to calculate the optimal allocation of data in a finite number of time steps. We show that our proposed algorithm (i) converges to the optimal solution in finite time with very high probability, and (ii) once the optimal solution is reached, each node is able to cease transmissions without needing knowledge of a global parameter such as the network diameter. Furthermore, our algorithm (i) operates exclusively with quantized values (i.e., each node processes and transmits quantized information), (ii) relies on event-driven updates, and (iii) calculates the optimal solution in the form of a quantized fraction which avoids errors due to quantization. Finally, we demonstrate the operation, performance, and potential advantages of our algorithm over random dynamic networks.