Search

This paper considers a challenging problem: to simultaneously optimize the cost and the quality of service in opaque wavelength division multiplexing (WDM) networks. An optimization problem is proposed that takes the information including network topology, traffic between end nodes, and the target level of congestion at each link/node in WDM networks. The outputs of this problem include routing, link channel capacities, and the optimum number of switch ports locally added/dropped at all switch nodes. The total network cost is reduced to maintain a minimum congestion level on all links, which provides an efficient trade‐off solution for the network design problem. The optimal information is utilized for dynamic traffic in WDM networks, which is shown to achieve the desired performance with the guaranteed quality of service in different networks. It was found that for an average link blocking probability equal to 0.015, the proposed model achieves a net channel gain in terms of wavelength channels (γw) equal to 35.72 %, 39.09 %, and 36.93 % compared to shortest path first routing and γw equal to 29.41 %, 37.35 %, and 27.47 % compared to alternate routing in three different networks. [ABSTRACT FROM AUTHOR]

Existing analytical models (EAMs) are used to find the quality of service of optical networks with wavelength division multiplexing (WDM). However, the convergence of EAMs decreases with an increase in traffic load and the numbers of wavelength (w) channels. EAMs are used to compute approximated numerical values of blocking probabilities (BPs) which are based on an iterative approach. There are cases in EAMs when numerical BP values do not converge to a single point after numerous iterations. In this paper, the converge issues of EAMs have been addressed by considering a recursive approximation based on iterative approach with the convergence criteria which is called an advance approximated BP model (AABPM). The accuracy of the AABPM for WDM optical networks is examined by comparing with an EAM as well as simulation results which shows that AABPM converges to give similar approximated numerical values with less convergence time. [ABSTRACT FROM AUTHOR]