This paper considers multicasting on wavelength-routing mesh optical networks. Although multicasting has been studied extensively in different network environments, multicasting in this environment is different, and more involved. The paper discusses the challenges of multicast support in optical wavelength routing networks, and reports on the advances made so far in this venue. The paper introduces a classification and a comparison of such techniques, and a study of their advantages and disadvantages.
Multicast communication in single -hop broadcast-and-select Wavelength Division Multiplexing (WDM) networks has received considerable attention from researchers. This paper presents a comprehensive survey of the multicast scheduling techniques in this environment. It considers different challenges that are faced in the design of multicasting techniques, and presents a classification of such schemes. A survey of the specific techniques is then presented, and a comparison is drawn between such techniques.
In this paper, we study the Routing and Wavelength Assignment (RWA) problem of a set of multicast sessions on already dimensioned wavelength routed network, while taking optical power impairments into consideration. Our main objective is to minimize the session blocking probability. We formulate the problem as a Mixed-Integer Linear Program (MILP). A greedy algorithm is also introduced, which provides fast, yet efficient, solutions for large problem sizes. The CPLEX linear optimization package is used to solve the MILP formulation, while simulation was used to experiment with the greedy algorithm.
Abstract-The problem of placing the optical amplifiers (OAs) in wavelength-routing mesh networks has been studied in the literature in two contexts: network provisioning [1] and connections provisioning [2]. In this paper, we introduce optimal and heuristic solutions for the network provisioning problem. The solution is based on constructing a multicast forest for each multicast connection with the goal of minimizing the total number of OAs needed in the network, hence reducing its cost. The optimal solution is formulated as a Mixed Integer Linear Program (MILP). On the other hand, the heuristic solution is obtained by dividing the problem into subproblems and solving them separately while taking the interdependency between these subproblems into consideration. The results obtained from both solutions are compared and they are found to be in good match.
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