Valentina Radojičić

A heuristic algorithm for lightpath scheduling in next-generation WDM optical networks

We study the routing and wavelength assignment (RWA) problem of scheduled lightpath demands (SLDs) in all-optical wavelength division multiplexing networks with no wavelength conversion capability. We consider the deterministic lightpath scheduling problem in which the whole set of lightpath demands is completely known in advance. The objective is to maximize the number of established lightpaths for a given number of wavelengths. Since this problem has been shown to be NP complete, various heuristic algorithms have been developed to solve it suboptimally. In this paper, we propose a novel heuristic RWA algorithm for SLDs based on the bee colony optimization (BCO) metaheuristic. BCO is a newborn swarm intelligence metaheuristic approach recently proposed to solve complex combinatorial optimization problems. We compare the efficiency of the proposed algorithm with three simple greedy algorithms for the same problem. Numerical results obtained by numerous simulations performed on the widely used realistic European Optical Network topology indicate that the proposed algorithm produces better-quality solutions compared to those obtained by greedy algorithms. In addition, we compare the results of the BCO–RWA–SLD algorithm with four other heuristic/metaheuristic algorithms proposed in literature to solve the RWA problem in the case of permanent (static) traffic demands.

New technology forecasting using the bass model

In this paper a brief review of new technology forecasting methods is given. We described the main influences and decision factors of the adoption of new telecommunications services/technologies. The Bass model in order to forecast the new technology adoption is applied. We demonstrate the procedure of Bass diffusion parameters estimation in a case of HDTV service.

Modelling for Evaluations of Call Center for Public Traffic and Transport Systems

Abstract This paper is dealing with functional organization of a call center based on human operator work. Due to significant fluctuations of user demands during the day and from day to day, the determination of required number of agents appears as actual giving the opportunities for efficient management. The purpose of this paper is to develop a mathematical model for optimal resource allocation in a call center in order to provide a satisfactory quality of service at all times, without having more agents than necessary. The objective is to find the best staffing levels or schedule that minimizes the daily costs while satisfying all constraints. To solve this problem, we propose here a two-level dynamic programming (DP) algorithm that determines the required staffing levels by shifts. The algorithm enables optimal allocation of available human resources such that the operation costs are reduced as much as possible. The practical sample is demonstrated in a case of a call center for public traffic and tra...

Bee colony approach for advance resource reservation in optical based grids

We study the advance resource reservation (ARR) problem in multi-wavelength optical-based grids under the deterministic scheduled traffic demands. The bee colony optimization meta-heuristic is used to solve the complex combinatorial ARR problem in which the objective is to maximize the number of established lightpaths. Simulation studies prove that the proposed bee colony optimization-ARR algorithm is able to produce good approximate solutions within reasonable amount of computation time.Copyright

Network capacity expansion strategies based on link congestion costs

In this paper two capacity expansion strategies are considered. Our focus will be on the congestion costs and maximum link utilisation, because these values best capture the overall network performances as well as the time period which is the best for capacity expansion. Throughout practical example the possible capacity expansion strategies are analyzed.

New diffusion model with variable market potential

Building upon the Bass diffusion model we propose the new forecasting model with variable market potential that depends on the technological availability of telecommunication network infrastructure. This paper presents case study of IPTV service adoption at the Serbian market. The model may be a useful managerial tool for analysing the impact of the network infrastructure investment on diffusion process.

A new method for estimating the real number of callers for call centre staffing optimisation

This paper deals with functional organisation of a call centre by adjusting the amount of human and technical resources such that the quality of service is satisfied while the costs of the resources are significantly reduced. If the call centre is not well designed, a great number of repeated requests occur, particularly in periods of peak traffic intensity. In such circumstances, the recorded data statistics give an unreal number of callers. This paper proposes a new method for estimating the real number of callers and the offered traffic using the general probability theory. Additionally we developed the two-level dynamic programming (DP) method for call centre staffing optimisation. Proposed method enables optimal allocation of available human resources by shifts such that the operation costs are significantly reduced.