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Interactive Scalar Quantization for Distributed Resource Allocation
Journal article   Open access   Peer reviewed

Interactive Scalar Quantization for Distributed Resource Allocation

Bradford D Boyle, Jie Jie Ren, John MacLaren Walsh and Steven Weber
IEEE transactions on signal processing, v 64(5), pp 1243-1256
01 Mar 2016
url
https://doi.org/10.1109/TSP.2015.2483479View
Published, Version of Record (VoR) Open

Abstract

Quantization (signal) resource allocation Computational modeling Rate-distortion Distortion interactive communication Delays Dynamic programming Resource management quantization
In many resource allocation problems, a centralized controller needs to award some resource to a user selected from a collection of distributed users with the goal of maximizing the utility the user would receive from the resource. This can be modeled as the controller computing an extremum of the distributed users' utilities. The overhead rate necessary to enable the controller to reproduce the users' local state can be prohibitively high. An approach to reduce this overhead is interactive communication wherein rate savings are achieved by tolerating an increase in delay. In this paper, we consider the design of a simple achievable scheme based on successive refinements of scalar quantization at each user. The optimal quantization policy is computed via a dynamic program and we demonstrate that tolerating a small increase in delay can yield significant rate savings. We then consider two simpler quantization policies to investigate the scaling properties of the rate-delay tradeoffs. Using a combination of these simpler policies, the performance of the optimal policy can be closely approximated with lower computational costs.

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Web of Science research areas
Engineering, Electrical & Electronic
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