Wavelength-routed optical-networks: linear formulation, resource budgeting tradeoffs, and a reconfiguration study

Abstract

Abstract--We present algorithms for the design of optimal virtual topologies embedded on wide-area wavelength-routed optical networks. The physical network architecture employs wavelength-conversion-enabled wavelength-routing switches (WRS) at the routing nodes, which allow the establishment of circuit-switched all-optical wavelength-division multiplexed (WDM) channels, called lightpaths. We assume packet-based traffic in the network, such that a packet travelling from its source to its destination may have to multihop through one or more such lightpaths.We present an exact integer linear programming (ILP) formulation for the complete virtual topology design, including choice of the constituent lightpaths, routes for these lightpaths, and intensity of packet flows through these lightpaths. By minimizing the average packet hop distance in our objective function and by relaxing the wavelength-continuity constraints (i.e., assuming wavelength converters at all nodes), we demonstrate that the entire optical network design problem can be considerably simplified and made computationally tractable.Although an ILP may take an exponential amount of time to obtain an exact optimal solution, we demonstrate that terminating the optimization within the first few iterations of the branch-and-bound method provides high-quality solutions. We ran experiments using the CPLEX optimization package on the NSFNET topology, a subset of the PACBELL network topology, as well as a third random topology to substantiate this conjecture.Minimizing the average packet hop distance is equivalent to maximizing the total network throughput under balanced flows through the lightpaths. The problem formulation can be used to design a balanced network, such that the utilizations of both transceivers and wavelengths in the network are maximized, thus reducing the cost of the network equipment. We analyze the tradeoffs in budgeting of resources (transceivers and switch sizes) in the optical network, and demonstrate how an improperly designed network may have low utilization of any one of these resources. We also use the problem formulation to provide a reconfiguration methodology in order to adapt the virtual topology to changing traffic conditions.

Scheduling bulk file transfers with start and end times

“…On the other hand, the execution time for the node-arc algorithm is nearly 15 minutes for a network size of 500 nodes. We conclude that the 5 Unless mentioned otherwise, the execution time for the edge-path formulations does not include the path computation time for finding the shortest paths. This is because the shortest paths are computed only once, and the computation can be carried out off-line.…”

“…This common quantity is denoted by y i (j) for job i on time slice j. Condition (5) says that, for each job, the total supply (or, equivalently, total demand), when summed over all time slices, must be equal to Z times the job size, where Z is the variable to be maximized. Condition (6) says that the capacity constraints must be satisfied for all edges on every time slice.…”

LS(Graph): a constraint-based local search for constraint optimization on trees and paths

“…: exact methods based on the ILP formulation [23,46,61,52,55,47,39,65]; heuristic algorithms [31,67,11,12]; and metaheuristics, including tabu search [40,51] and Genetic [4,10,38]. These techniques have been tried on realistic networks of small size (networks up to 27 nodes and 70 edges) but involving a large number of connection requests.…”

“…In the current tree tr (see Figure 3a), the edge (8,10) is a preferred replacing edge, nca tr (s, 8) = 7, nca tr (s, 10) = 12, lownca tr ((8, 10), s) = 7, upnca tr ((8, 10), s) = 12, low tr ((8,-10), s) = 8 and up tr ((8, 10), s) = 10. The edges (7,11) and (11,12) are preferred replaceable edges of (8,10) because these edges belong to path tr (7,12). The path induced by tr is s, 3, 4, 6, 7, 11, 12, t .…”

“…Lines 7-9 remove all impossible wavelengths for P i from W i . If no wavelength already used is possible for P i (line 10), then we have to find a new wavelength w i for P i (lines [11][12]. If the candidate set W i is not null, we select randomly a wavelength from W i and assign it to P i (line 15).…”