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Overhead Performance Tradeoffs-A Resource Allocation Perspective
Journal article   Open access   Peer reviewed

Overhead Performance Tradeoffs-A Resource Allocation Perspective

Jie Jie Ren, Bradford D Boyle, Gwanmo Gwanmo Ku, Steven Weber and John MacLaren Walsh
IEEE transactions on information theory, v 62(6), pp 3243-3269
Jun 2016
DOI: https://doi.org/10.1109/TIT.2016.2524576
url
http://arxiv.org/abs/1408.3661View
Submitted Open Open Access (License Unspecified)

Abstract

rate distortion scalar quantization Modulation Rate-distortion Receivers Encoding Indexes Resource management Distributed function computation Information rates
A key aspect of many resource allocation problems is the need for the resource controller to compute a function, such as the max or arg max, of the competing users' metrics. Information must be exchanged between the competing users and the resource controller in order for this function to be computed. In many practical resource controllers, the competing users' metrics are communicated to the resource controller, which then computes the desired extremization function. However, in this paper, it is shown that information rate savings can be obtained by recognizing that the controller only needs to determine the result of this extremization function. If the extremization function is to be computed losslessly, the rate savings are shown in most cases to be at most 2 b independent of the number of competing users. Motivated by the small savings in the lossless case, simple achievable schemes for both the lossy and interactive variants of this problem are considered. It is shown that both of these approaches have the potential to realize large rate savings, especially in the case where the number of competing users is large. For the lossy variant, it is shown that the proposed simple achievable schemes are in fact close to the fundamental limit given by the rate distortion function.

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5 citations in Web of Science
8 citations in Scopus

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Web of Science research areas
Computer Science, Information Systems
Computer Science, Theory & Methods
Engineering, Electrical & Electronic
Mathematics, Applied
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