Title
Interactive Scalar Quantization for Distributed Resource Allocation
Abstract
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.
Year
DOI
Venue
2016
10.1109/TSP.2015.2483479
IEEE Transactions on Signal Processing
Keywords
Field
DocType
Quantization (signal),Delays,Computational modeling,Dynamic programming,Rate-distortion,Distortion,Resource management
Scalar quantization,Mathematical optimization,Control theory,Computer science,Pre-determined overhead rate,Resource allocation,Quantization (signal processing),Scaling
Journal
Volume
Issue
ISSN
64
5
1053-587X
Citations 
PageRank 
References 
1
0.35
23
Authors
4
Name
Order
Citations
PageRank
Bradford D. Boyle161.80
Jie Ren292.51
John MacLaren Walsh310717.90
Steven Weber472453.55