How to minimize the number of mirroring resources under a QoS constraint (resource minimization problem) is an important issue in content delivery networks. This paper proposes a novel approach that takes advantage of the parallelism of dynamically reconfigurable processors (DRPs) to solve the resource minimization problem, which is NP-hard. Our proposal obtains the optimal solution by running an exhaustive search algorithm suitable for DRP. Greedy algorithms, which have been widely studied for tackling the resource minimization problem, cannot always obtain the optimal solution. The proposed method is implemented on an actual DRP and in experiments reduces the execution time by a factor of 40 compared to the conventional exhaustive search algorithm on a Pentium 4 (2.8 GHz).
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Sho SHIMIZU, Hiroyuki ISHIKAWA, Yutaka ARAKAWA, Naoaki YAMANAKA, Kosuke SHIBA, "Resource Minimization Method Satisfying Delay Constraint for Replicating Large Contents" in IEICE TRANSACTIONS on Communications,
vol. E92-B, no. 10, pp. 3102-3110, October 2009, doi: 10.1587/transcom.E92.B.3102.
Abstract: How to minimize the number of mirroring resources under a QoS constraint (resource minimization problem) is an important issue in content delivery networks. This paper proposes a novel approach that takes advantage of the parallelism of dynamically reconfigurable processors (DRPs) to solve the resource minimization problem, which is NP-hard. Our proposal obtains the optimal solution by running an exhaustive search algorithm suitable for DRP. Greedy algorithms, which have been widely studied for tackling the resource minimization problem, cannot always obtain the optimal solution. The proposed method is implemented on an actual DRP and in experiments reduces the execution time by a factor of 40 compared to the conventional exhaustive search algorithm on a Pentium 4 (2.8 GHz).
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E92.B.3102/_p
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@ARTICLE{e92-b_10_3102,
author={Sho SHIMIZU, Hiroyuki ISHIKAWA, Yutaka ARAKAWA, Naoaki YAMANAKA, Kosuke SHIBA, },
journal={IEICE TRANSACTIONS on Communications},
title={Resource Minimization Method Satisfying Delay Constraint for Replicating Large Contents},
year={2009},
volume={E92-B},
number={10},
pages={3102-3110},
abstract={How to minimize the number of mirroring resources under a QoS constraint (resource minimization problem) is an important issue in content delivery networks. This paper proposes a novel approach that takes advantage of the parallelism of dynamically reconfigurable processors (DRPs) to solve the resource minimization problem, which is NP-hard. Our proposal obtains the optimal solution by running an exhaustive search algorithm suitable for DRP. Greedy algorithms, which have been widely studied for tackling the resource minimization problem, cannot always obtain the optimal solution. The proposed method is implemented on an actual DRP and in experiments reduces the execution time by a factor of 40 compared to the conventional exhaustive search algorithm on a Pentium 4 (2.8 GHz).},
keywords={},
doi={10.1587/transcom.E92.B.3102},
ISSN={1745-1345},
month={October},}
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TY - JOUR
TI - Resource Minimization Method Satisfying Delay Constraint for Replicating Large Contents
T2 - IEICE TRANSACTIONS on Communications
SP - 3102
EP - 3110
AU - Sho SHIMIZU
AU - Hiroyuki ISHIKAWA
AU - Yutaka ARAKAWA
AU - Naoaki YAMANAKA
AU - Kosuke SHIBA
PY - 2009
DO - 10.1587/transcom.E92.B.3102
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E92-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2009
AB - How to minimize the number of mirroring resources under a QoS constraint (resource minimization problem) is an important issue in content delivery networks. This paper proposes a novel approach that takes advantage of the parallelism of dynamically reconfigurable processors (DRPs) to solve the resource minimization problem, which is NP-hard. Our proposal obtains the optimal solution by running an exhaustive search algorithm suitable for DRP. Greedy algorithms, which have been widely studied for tackling the resource minimization problem, cannot always obtain the optimal solution. The proposed method is implemented on an actual DRP and in experiments reduces the execution time by a factor of 40 compared to the conventional exhaustive search algorithm on a Pentium 4 (2.8 GHz).
ER -