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Resource-Aware Distributed Scheduling Strategies for Large-Scale Computational Cluster/Grid Systems
October 2007 (vol. 18 no. 10)
pp. 1450-1461
ASCII Text
x 
 
Sivakumar Viswanathan, Bharadwaj Veeravalli, Thomas G. Robertazzi, "Resource-Aware Distributed Scheduling Strategies for Large-Scale Computational Cluster/Grid Systems," IEEE Transactions on Parallel and Distributed Systems, vol. 18, no. 10, pp. 1450-1461, October, 2007.
 
 
BibTex
x
 
@article{ 10.1109/TPDS.2007.1073,
author = {Sivakumar Viswanathan and Bharadwaj Veeravalli and Thomas G. Robertazzi},
title = {Resource-Aware Distributed Scheduling Strategies for Large-Scale Computational Cluster/Grid Systems},
journal ={IEEE Transactions on Parallel and Distributed Systems},
volume = {18},
number = {10},
issn = {1045-9219},
year = {2007},
pages = {1450-1461},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPDS.2007.1073},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Parallel and Distributed Systems
TI - Resource-Aware Distributed Scheduling Strategies for Large-Scale Computational Cluster/Grid Systems
IS - 10
SN - 1045-9219
SP1450
EP1461
EPD - 1450-1461
A1 - Sivakumar Viswanathan,
A1 - Bharadwaj Veeravalli,
A1 - Thomas G. Robertazzi,
PY - 2007
KW - Divisible loads
KW - Grid computing
KW - Cluster computing
KW - buffer constraints
KW - processing time
KW - deadlines
VL - 18
JA - IEEE Transactions on Parallel and Distributed Systems
ER -
 
In this paper, we propose distributed algorithms, referred to as Resource Aware Dynamic Incremental Scheduling (RADIS) strategies. Our strategies are specifically designed to handle large volumes of computationally intensive arbitrarily divisible loads submitted for processing at Cluster / Grid systems involving multiple sources and sinks (processing nodes). We consider a reallife scenario wherein buffer space (memory) available at the sinks (required for holding and processing the loads) vary over time and the loads have deadlines, and propose efficient "pull-based" scheduling strategies with admission control policy that ensures that the admitted loads are processed satisfying their deadline requirements. The design of our proposed strategies adopts the divisible load paradigm, referred to as divisible load theory (DLT), which is shown to be efficient in handling large volume loads. We demonstrate detailed workings of the proposed algorithms via a simulation study using real-life parameters obtained from a major physics experiment.

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Index Terms:
Divisible loads, Grid computing, Cluster computing, buffer constraints, processing time, deadlines
Citation:
Sivakumar Viswanathan, Bharadwaj Veeravalli, Thomas G. Robertazzi, "Resource-Aware Distributed Scheduling Strategies for Large-Scale Computational Cluster/Grid Systems," IEEE Transactions on Parallel and Distributed Systems, vol. 18, no. 10, pp. 1450-1461, Oct. 2007, doi:10.1109/TPDS.2007.1073
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