Yong-Sik Shin

Uncapacitated point-to-multipoint network flow problem and its application to multicasting in telecommunication networks

Abstract This paper introduces an uncapacitated point-to-multipoint network flow problem where a convex arc cost and demand splitting is introduced. This problem arises from multicast routing in telecommunication networks such as the Internet Protocol network. Multiple tree routes are used to use the network resources efficiently. The proposed method adds extra tree routes until it satisfies the target conditions. This method splits the multicast traffic demand into the chosen tree routes. In this study, a mathematical model was developed and the conditions for traffic splitting were optimized. The convergence of the algorithm was obtained under monotonically increasing and strictly convex conditions on the arc cost function. A modified algorithm was proposed for a practical multicasting method. Various experiments were carried and the results show that the new multicasting method is fairly effective in improving the quality of service with only two or three multiple tree routes.

Wavelength converter location and optical fiber dimensioning for limited channel convertible optical networks

This paper introduces two efficient methods for the design of multiwavelength optical networks. First, we suggest a wavelength converter location method if converters are located at some nodes. Second, we suggest a decision method about how many optical fibers must be required at each link to satisfy all connection demands. The second method is also for the network with wavelength converters at some nodes. These two methods are based on a new optical path scheme in a network of arbitrary topology. In the new optical path scheme, called the partial wavelength path (PWP) scheme, limited channel converters are located at not all, but some nodes. Limited channel converter allows a limited number of optical paths to share wavelength conversion. Static routing and wavelength assignment is assumed.

Iterative bundle-based decomposition for large-scale nonseparable convex optimization

Abstract There has been considerable research in solving large-scale separable convex optimization problems. In this paper we present an algorithm for large-scale nonseparable smooth convex optimization problems with block-angular linear constraints. The solution of the problem is approximated by solving a sequence of structured separable quadratic programs. The Bundle-based decomposition (BBD) method of Robinson (In: Prekopa, A., Szelezsan, J., Strazicky, B. (Eds.), System Modelling and Optimization, Springer, 1986, pp. 751–756; Annals de Institute Henri Poincare: Analyse Non Lineaire 6 (1989) 435–447) is applied to each separable quadratic program. We implement the algorithm and present computational experience.

Multicast Routing by Multiple Tree Routes

A solution to reduce the cost of multicast paths is presented, where the traffic is split over multiple paths to obtain an overall lower cost. Optimal conditions for this split operation are provided and two different algorithms are presented. The methods were shown to work on problems with many different types of simultaneous multicast traffic. Various experiments were conducted and the results showed that the new multicasting was fairly effective on the end-to-end quality of services.