WDM optical networks represent the future direction of high capacity wide-area network applications. By creating optical paths between several nodes in the core networks, a logical topology can be created over the physical topology. By reconfiguring the logical topology, network resource utilization can be optimized corresponding to traffic pattern changes. From the viewpoint of network operation, the complexity of reconfiguration should be minimized as well. In this paper we consider the logical topology reconfiguration in arbitrary topology IP over WDM networks with balancing between network performance and operation complexity. The exact formulation of the logical topology reconfiguration problem is usually represented as Mixed Integer Linear Programming, but it grows intractable with increasing network size. Here we propose a simulated annealing approach in order to both determine the target topology with a smaller logical topology change and also satisfy the performance requirement. A threshold on the congestion performance requirement is used to balance the optimal congestion requirement and operation complexity. This is achieved by tuning this threshold to a feasible value. For effective solution discovery, a two-stage SA algorithm is developed for multiple objectives optimization.
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Sugang XU, Kaoru SEZAKI, Yoshiaki TANAKA, "A Two-Stage Simulated Annealing Logical Topology Reconfiguration in IP over WDM Networks" in IEICE TRANSACTIONS on Communications,
vol. E88-B, no. 6, pp. 2483-2494, June 2005, doi: 10.1093/ietcom/e88-b.6.2483.
Abstract: WDM optical networks represent the future direction of high capacity wide-area network applications. By creating optical paths between several nodes in the core networks, a logical topology can be created over the physical topology. By reconfiguring the logical topology, network resource utilization can be optimized corresponding to traffic pattern changes. From the viewpoint of network operation, the complexity of reconfiguration should be minimized as well. In this paper we consider the logical topology reconfiguration in arbitrary topology IP over WDM networks with balancing between network performance and operation complexity. The exact formulation of the logical topology reconfiguration problem is usually represented as Mixed Integer Linear Programming, but it grows intractable with increasing network size. Here we propose a simulated annealing approach in order to both determine the target topology with a smaller logical topology change and also satisfy the performance requirement. A threshold on the congestion performance requirement is used to balance the optimal congestion requirement and operation complexity. This is achieved by tuning this threshold to a feasible value. For effective solution discovery, a two-stage SA algorithm is developed for multiple objectives optimization.
URL: https://globals.ieice.org/en_transactions/communications/10.1093/ietcom/e88-b.6.2483/_p
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@ARTICLE{e88-b_6_2483,
author={Sugang XU, Kaoru SEZAKI, Yoshiaki TANAKA, },
journal={IEICE TRANSACTIONS on Communications},
title={A Two-Stage Simulated Annealing Logical Topology Reconfiguration in IP over WDM Networks},
year={2005},
volume={E88-B},
number={6},
pages={2483-2494},
abstract={WDM optical networks represent the future direction of high capacity wide-area network applications. By creating optical paths between several nodes in the core networks, a logical topology can be created over the physical topology. By reconfiguring the logical topology, network resource utilization can be optimized corresponding to traffic pattern changes. From the viewpoint of network operation, the complexity of reconfiguration should be minimized as well. In this paper we consider the logical topology reconfiguration in arbitrary topology IP over WDM networks with balancing between network performance and operation complexity. The exact formulation of the logical topology reconfiguration problem is usually represented as Mixed Integer Linear Programming, but it grows intractable with increasing network size. Here we propose a simulated annealing approach in order to both determine the target topology with a smaller logical topology change and also satisfy the performance requirement. A threshold on the congestion performance requirement is used to balance the optimal congestion requirement and operation complexity. This is achieved by tuning this threshold to a feasible value. For effective solution discovery, a two-stage SA algorithm is developed for multiple objectives optimization.},
keywords={},
doi={10.1093/ietcom/e88-b.6.2483},
ISSN={},
month={June},}
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TY - JOUR
TI - A Two-Stage Simulated Annealing Logical Topology Reconfiguration in IP over WDM Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 2483
EP - 2494
AU - Sugang XU
AU - Kaoru SEZAKI
AU - Yoshiaki TANAKA
PY - 2005
DO - 10.1093/ietcom/e88-b.6.2483
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E88-B
IS - 6
JA - IEICE TRANSACTIONS on Communications
Y1 - June 2005
AB - WDM optical networks represent the future direction of high capacity wide-area network applications. By creating optical paths between several nodes in the core networks, a logical topology can be created over the physical topology. By reconfiguring the logical topology, network resource utilization can be optimized corresponding to traffic pattern changes. From the viewpoint of network operation, the complexity of reconfiguration should be minimized as well. In this paper we consider the logical topology reconfiguration in arbitrary topology IP over WDM networks with balancing between network performance and operation complexity. The exact formulation of the logical topology reconfiguration problem is usually represented as Mixed Integer Linear Programming, but it grows intractable with increasing network size. Here we propose a simulated annealing approach in order to both determine the target topology with a smaller logical topology change and also satisfy the performance requirement. A threshold on the congestion performance requirement is used to balance the optimal congestion requirement and operation complexity. This is achieved by tuning this threshold to a feasible value. For effective solution discovery, a two-stage SA algorithm is developed for multiple objectives optimization.
ER -