Architecture and sparse placement of limited-wavelength converters for optical networks

Abstract

Equipping all nodes of a large optical network with full conversion capability is prohibitively costly. To improve performance at reduced cost, sparse converter placement algorithms are used to select a subset of nodes for full-conversion deployment. Further cost reduction can be obtained by deploying only limited conversion capability in the selected nodes. We present a limited wavelength converter placement algorithm based on the k-minimum dominating set (k-MDS) concept. We propose three different cost-effective optical switch designs using the technologically feasible nontunable optical multiplexers. These three switch designs are flexible node sharing, strict node sharing, and static mapping. Compared to the full search heuristic of O(N 3) complexity based on ranking nodes by blocking percentages, our algorithm not only has a better time complexity O(RN 2), where R is the number of disjoint sets provided by k-MDS, but also avoids the local minimum problem. The performance benefit of our algorithm is demonstrated by network simulation with the U.S Long Haul topology having 28 nodes (R is 5) and the National Science Foundation (NSF) network having 16 nodes (R is 4). Our simulation considers the case when the traffic is not uniformly distributed between node pairs in the network using a weighted placement approach, referred to as k-WMDS. From the optical network management point of view, our results also show that the limited conversion capability can achieve performance very close to that of the full conversion capability, while not only decreasing the optical switch cost but also enhancing its fault tolerance. © 2004 Society of Photo-Optical Instrumentation Engineers.

Routing and Wavelength Assignment in Optical Networks Using Logical Link Representation and Efficient Bitwise Computation

“…The impact of converters on the RWA method proposed in this paper can be evaluated in two steps. First, the converter placement algorithm proposed in [27] can be applied to select the nodes that will be equipped with wavelength converters. Second, the RWA method is modified to take advantage of the presence of converters in some nodes.…”

“…The benefit of wavelength conversion can be obtained even when the converters are deployed in only a small number of nodes. For example, we have recently shown [26][27][28] that the presence of full or limited wavelength conversion capability in a sparse set of nodes selected by a k-minimum dominating set heuristic can lead to significant gains in performance. For the sake of clarity and simplicity, however, we shall illustrate the main idea of our RWA approach using OXCs without wavelength converters.…”

Wavelength converter placement in least-load-routing-based optical networks using genetic algorithms

“…In FAR, LLR-MMM and LLR-MSM, 2 edge-disjoint paths (K = 2) are used. The performance of the GA model for the wavelength converter placement is also discussed, and compared with two popular heuristic algorithms, Total Outgoing Traffic (TOT) [12] and the K Minimum Dominating Set (K-MDS) placement [22].…”

Contention resolution and QoS provisioning using sparse fiber delay lines in WDM networks

“…Our previous work investigated various aspects of WDM and OBS networks either assuming wavelength continuity [28] or using wavelength conversion [22,25,[29][30][31]. In this paper, we focus on FDLs and the sparse placement of FDLs at the core nodes of an OBS network as a solution to burst contention.…”

“…Examples include solutions based on burst segmentation [15], QoS-based burstification [17], classes of traffic isolation by extra offset-time [3], wavelength reservation [19], and burst assembly schemes [20]. Another approach for solving contention is based on deflection: in the time domain using FDLs [6,10,11,18,21]; in the space domain using deflection; routing [8,13,21]; or in the wavelength domain using OWCs [1,[6][7][8][22][23][24][25][26]. The authors in Ref.…”