10,968 research outputs found
A Novel Solution to the Dynamic Routing and Wavelength Assignment Problem in Transparent Optical Networks
We present an evolutionary programming algorithm for solving the dynamic
routing and wavelength assignment (DRWA) problem in optical wavelength-division
multiplexing (WDM) networks under wavelength continuity constraint. We assume
an ideal physical channel and therefore neglect the blocking of connection
requests due to the physical impairments. The problem formulation includes
suitable constraints that enable the algorithm to balance the load among the
individuals and thus results in a lower blocking probability and lower mean
execution time than the existing bio-inspired algorithms available in the
literature for the DRWA problems. Three types of wavelength assignment
techniques, such as First fit, Random, and Round Robin wavelength assignment
techniques have been investigated here. The ability to guarantee both low
blocking probability without any wavelength converters and small delay makes
the improved algorithm very attractive for current optical switching networks.Comment: 12 Pages, IJCNC Journal 201
QoS multicast tree construction in IP/DWDM optical internet by bio-inspired algorithms
Copyright @ Elsevier Ltd. All rights reserved.In this paper, two bio-inspired Quality of Service (QoS) multicast algorithms are proposed in IP over dense wavelength division multiplexing (DWDM) optical Internet. Given a QoS multicast request and the delay interval required by the application, both algorithms are able to find a flexible QoS-based cost suboptimal routing tree. They first construct the multicast trees based on ant colony optimization and artificial immune algorithm, respectively. Then a dedicated wavelength assignment algorithm is proposed to assign wavelengths to the trees aiming to minimize the delay of the wavelength conversion. In both algorithms, multicast routing and wavelength assignment are integrated into a single process. Therefore, they can find the multicast trees on which the least wavelength conversion delay is achieved. Load balance is also considered in both algorithms. Simulation results show that these two bio-inspired algorithms can construct high performance QoS routing trees for multicast applications in IP/DWDM optical Internet.This work was supported in part ny the Program for New Century Excellent Talents in University, the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1, the National Natural Science Foundation of China under Grant no. 60673159 and 70671020, the National High-Tech Reasearch and Development Plan of China under Grant no. 2007AA041201, and the Specialized Research Fund for the Doctoral Program of Higher Education under Grant no. 20070145017
A multipopulation parallel genetic simulated annealing based QoS routing and wavelength assignment integration algorithm for multicast in optical networks
Copyright @ 2008 Elsevier B.V. All rights reserved.In this paper, we propose an integrated Quality of Service (QoS) routing algorithm for optical networks. Given a QoS multicast request and the delay interval specified by users, the proposed algorithm can find a flexible-QoS-based cost suboptimal routing tree. The algorithm first constructs the multicast tree based on the multipopulation parallel genetic simulated annealing algorithm, and then assigns wavelengths to the tree based on the wavelength graph. In the algorithm, routing and wavelength assignment are integrated into a single process. For routing, the objective is to find a cost suboptimal multicast tree. For wavelength assignment, the objective is to minimize the delay of the multicast tree, which is achieved by minimizing the number of wavelength conversion. Thus both the cost of multicast tree and the user QoS satisfaction degree can approach the optimal. Our algorithm also considers load balance. Simulation results show that the proposed algorithm is feasible and effective. We also discuss the practical realization mechanisms of the algorithm.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1, the National Natural Science Foundation of China under Grant nos. 60673159 and 70671020, the National High-Tech Research and Development Plan of China under Grant no. 2006AA01Z214, Program for New Century Excellent Talents in University, and the Key Project of Chinese Ministry of Education under Grant no. 108040
The edge-disjoint path problem on random graphs by message-passing
We present a message-passing algorithm to solve the edge disjoint path
problem (EDP) on graphs incorporating under a unique framework both traffic
optimization and path length minimization. The min-sum equations for this
problem present an exponential computational cost in the number of paths. To
overcome this obstacle we propose an efficient implementation by mapping the
equations onto a weighted combinatorial matching problem over an auxiliary
graph. We perform extensive numerical simulations on random graphs of various
types to test the performance both in terms of path length minimization and
maximization of the number of accommodated paths. In addition, we test the
performance on benchmark instances on various graphs by comparison with
state-of-the-art algorithms and results found in the literature. Our
message-passing algorithm always outperforms the others in terms of the number
of accommodated paths when considering non trivial instances (otherwise it
gives the same trivial results). Remarkably, the largest improvement in
performance with respect to the other methods employed is found in the case of
benchmarks with meshes, where the validity hypothesis behind message-passing is
expected to worsen. In these cases, even though the exact message-passing
equations do not converge, by introducing a reinforcement parameter to force
convergence towards a sub optimal solution, we were able to always outperform
the other algorithms with a peak of 27% performance improvement in terms of
accommodated paths. On random graphs, we numerically observe two separated
regimes: one in which all paths can be accommodated and one in which this is
not possible. We also investigate the behaviour of both the number of paths to
be accommodated and their minimum total length.Comment: 14 pages, 8 figure
Throughput Maximization in Multi-Band Optical Networks with Column Generation
Multi-band transmission is a promising technical direction for spectrum and
capacity expansion of existing optical networks. Due to the increase in the
number of usable wavelengths in multi-band optical networks, the complexity of
resource allocation problems becomes a major concern. Moreover, the
transmission performance, spectrum width, and cost constraint across optical
bands may be heterogeneous. Assuming a worst-case transmission margin in U, L,
and C-bands, this paper investigates the problem of throughput maximization in
multi-band optical networks, including the optimization of route, wavelength,
and band assignment. We propose a low-complexity decomposition approach based
on Column Generation (CG) to address the scalability issue faced by traditional
methodologies. We numerically compare the results obtained by our CG-based
approach to an integer linear programming model, confirming the near-optimal
network throughput. Our results also demonstrate the scalability of the
CG-based approach when the number of wavelengths increases, with the
computation time in the magnitude order of 10 s for cases varying from 75 to
1200 wavelength channels per link in a 14-node network.Comment: 6 pages, 4 figures, submitted to IEEE International Conference on
Communications 2024 (ICC2024). (Note on arXiv: for beginners in the area of
column generation, please refer to the example computation in the file
. I have uploaded it to this arXiv
project along with other source files.
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