7 resultados para blocking algorithm
em DigitalCommons@University of Nebraska - Lincoln
Resumo:
Translucent wavelength-division multiplexing optical networks use sparse placement of regenerators to overcome physical impairments and wavelength contention introduced by fully transparent networks, and achieve a performance close to fully opaque networks at a much less cost. In previous studies, we addressed the placement of regenerators based on static schemes, allowing for only a limited number of regenerators at fixed locations. This paper furthers those studies by proposing a dynamic resource allocation and dynamic routing scheme to operate translucent networks. This scheme is realized through dynamically sharing regeneration resources, including transmitters, receivers, and electronic interfaces, between regeneration and access functions under a multidomain hierarchical translucent network model. An intradomain routing algorithm, which takes into consideration optical-layer constraints as well as dynamic allocation of regeneration resources, is developed to address the problem of translucent dynamic routing in a single routing domain. Network performance in terms of blocking probability, resource utilization, and running times under different resource allocation and routing schemes is measured through simulation experiments.
Resumo:
We investigate waveband switching (WBS) with different grouping strategies in wavelength-division multiplexing (WDM) mesh networks. End-to-end waveband switching (ETEWBS) and same-destination-intermediate waveband switching (SD-IT-WBS) are analyzed and compared in terms of blocking probability and cost savings. First, an analytical model for ETEWBS is proposed to determine the network blocking probability in a mesh network. For SD-IT-WBS, a simple waveband switching algorithm is presented. An analytical model to determine the network blocking probability is proposed for SD-IT-WBS based on the algorithm. The analytical results are validated by comparing with simulation results. Both results match well and show that ETE-WBS slightly outperforms SD-IT-WBS in terms of blocking probability. On the other hand, simulation results show that SD-IT-WBS outperforms ETE-WBS in terms of cost savings.
Resumo:
Waveband switching (WBS) is an important technique to save switching and transmission cost in wavelength -division multiplexed (WDM) optical networks. A cost-efficient WBS scheme would enable network carriers to increase the network throughput (revenue) while achieving significant cost savings. We identify the critical factors that determine the WBS network throughput and switching cost and propose a novel intermediate waveband switching (IT-WBS) algorithm, called the minimizing-weighted-cost (MWC) algorithm. The MWC algorithm defines a cost for each candidate route of a call. By selecting the route with the smallest weighted cost, MWC balances between minimizing the call blocking probability and minimizing the network switching cost. Our simulations show that MWC outperforms other wavelength/waveband switching algorithms and can enhance the network throughput at a reduced cost.
Resumo:
Routing techniques used in wavelength routed optical networks (WRN) do not give an efficient solution with Waveband routed optical networks (WBN) as the objective of routing in WRN is to reduce the blocking probability and that in WBN is to reduce the number of switching ports. Routing in WBN can be divided two parts, finding the route and grouping the wavelength assigned into that route with some existing wavelengths/wavebands. In this paper, we propose a heuristic for waveband routing, which uses a new grouping strategy called discontinuous waveband grouping to group the wavelengths into a waveband. The main objective of our algorithm is to decrease the total number of ports required and reduce the blocking probability of the network. The performance of the heuristic is analyzed using simulation on a WBN with non-uniform wavebands.
Resumo:
As wavelength-division multiplexing (WDM) evolves towards practical applications in optical transport networks, waveband switching (WBS) has been introduced to cut down the operational costs and to reduce the complexities and sizes of network components, e.g., optical cross-connects (OXCs). This paper considers the routing, wavelength assignment and waveband assignment (RWWBA) problem in a WDM network supporting mixed waveband and wavelength switching. First, the techniques supporting waveband switching are studied, where a node architecture enabling mixed waveband and wavelength switching is proposed. Second, to solve the RWWBA problem with reduced switching costs and improved network throughput, the cost savings and call blocking probabilities along intermediate waveband-routes are analyzed. Our analysis reveals some important insights about the cost savings and call blocking probability in relation to the fiber capacity, the candidate path, and the traffic load. Third, based on our analysis, an online integrated intermediate WBS algorithm (IIWBS) is proposed. IIWBS determines the waveband switching route for a call along its candidate path according to the node connectivity, the link utilization, and the path length information. In addition, the IIWBS algorithm is adaptive to real network applications under dynamic traffic requests. Finally, our simulation results show that IIWBS outperforms a previous intermediate WBS algorithm and RWA algorithms in terms of network throughput and cost efficiency.
Resumo:
Sparse traffic grooming is a practical problem to be addressed in heterogeneous multi-vendor optical WDM networks where only some of the optical cross-connects (OXCs) have grooming capabilities. Such a network is called as a sparse grooming network. The sparse grooming problem under dynamic traffic in optical WDM mesh networks is a relatively unexplored problem. In this work, we propose the maximize-lightpath-sharing multi-hop (MLS-MH) grooming algorithm to support dynamic traffic grooming in sparse grooming networks. We also present an analytical model to evaluate the blocking performance of the MLS-MH algorithm. Simulation results show that MLSMH outperforms an existing grooming algorithm, the shortest path single-hop (SPSH) algorithm. The numerical results from analysis show that it matches closely with the simulation. The effect of the number of grooming nodes in the network on the blocking performance is also analyzed.
Resumo:
Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert). Many conventional active learning algorithms focus on refining the decision boundary, at the expense of exploring new regions that the current hypothesis misclassifies. We propose a new active learning algorithm that balances such exploration with refining of the decision boundary by dynamically adjusting the probability to explore at each step. Our experimental results demonstrate improved performance on data sets that require extensive exploration while remaining competitive on data sets that do not. Our algorithm also shows significant tolerance of noise.