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Design and Implementation of Distributed Resource Management for Time Sensitive Applications

Chasparis, Georgios; Maggio, Martina LU ; Bini, Enrico and Årzén, Karl-Erik LU (2016) In Automatica 64. p.44-53
Abstract
In this paper, we address distributed convergence to fair allocations of CPU resources for time-sensitive applications. We propose a novel resource management framework where a centralized objective for fair allocations is decomposed into a pair of performance-driven recursive processes for updating: (a) the allocation of computing bandwidth to the applications (resource adaptation), executed by the resource manager, and (b) the computational demand of each application (service-level adaptation), executed by each application independently. We provide conditions under which the distributed recursive scheme exhibits convergence to solutions of the centralized objective (i.e., fair allocations). Contrary to prior work on centralized... (More)
In this paper, we address distributed convergence to fair allocations of CPU resources for time-sensitive applications. We propose a novel resource management framework where a centralized objective for fair allocations is decomposed into a pair of performance-driven recursive processes for updating: (a) the allocation of computing bandwidth to the applications (resource adaptation), executed by the resource manager, and (b) the computational demand of each application (service-level adaptation), executed by each application independently. We provide conditions under which the distributed recursive scheme exhibits convergence to solutions of the centralized objective (i.e., fair allocations). Contrary to prior work on centralized optimization schemes, the proposed framework exhibits adaptivity and robustness to changes both in the number and nature of applications, while it assumes minimum information available to both applications and the resource manager. We finally validate our framework with simulations using the TrueTime toolbox in MATLAB/Simulink. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Automatica
volume
64
pages
44 - 53
publisher
Pergamon
external identifiers
  • wos:000368967000006
  • scopus:84951811717
ISSN
0005-1098
DOI
10.1016/j.automatica.2015.09.015
language
English
LU publication?
yes
id
67190b29-12ee-483b-a0ef-38a41003d65a (old id 5471479)
date added to LUP
2015-06-29 11:07:19
date last changed
2017-01-01 05:33:12
@article{67190b29-12ee-483b-a0ef-38a41003d65a,
  abstract     = {In this paper, we address distributed convergence to fair allocations of CPU resources for time-sensitive applications. We propose a novel resource management framework where a centralized objective for fair allocations is decomposed into a pair of performance-driven recursive processes for updating: (a) the allocation of computing bandwidth to the applications (resource adaptation), executed by the resource manager, and (b) the computational demand of each application (service-level adaptation), executed by each application independently. We provide conditions under which the distributed recursive scheme exhibits convergence to solutions of the centralized objective (i.e., fair allocations). Contrary to prior work on centralized optimization schemes, the proposed framework exhibits adaptivity and robustness to changes both in the number and nature of applications, while it assumes minimum information available to both applications and the resource manager. We finally validate our framework with simulations using the TrueTime toolbox in MATLAB/Simulink.},
  author       = {Chasparis, Georgios and Maggio, Martina and Bini, Enrico and Årzén, Karl-Erik},
  issn         = {0005-1098},
  language     = {eng},
  pages        = {44--53},
  publisher    = {Pergamon},
  series       = {Automatica},
  title        = {Design and Implementation of Distributed Resource Management for Time Sensitive Applications},
  url          = {http://dx.doi.org/10.1016/j.automatica.2015.09.015},
  volume       = {64},
  year         = {2016},
}