Abstract
Designing an excellent original topology not only improves the accuracy of routing, but also improves the restoring rate of failure. In this paper, we propose a new heuristic topology generation algorithm—GA-PODCC (Genetic Algorithm based on the Pareoto Optimality of Delay, Configuration and Consumption), which utilizes a genetic algorithm to optimize the link delay and resource configuration/consumption. The novelty lies in designing the two stages of genetic operation: The first stage is to pick the best population by means of the crossover, mutation, and selection operation; The second stage is to select an excellent individual from the best population. The simulation results show that, using the same number of nodes, GA-PODCC algorithm improves the balance of all the three optimization objectives, maintaining a low level of distortion in topology aggregation.
Highlights
The scale of optical networks is rapidly expanding with the development of optical communication technology [1], the structure of optical networks has changed greatly
We propose a new heuristic topology generation algorithm—GA-PODCC (Genetic Algorithm based on the Pareoto Optimality of Delay, Configuration and Consumption), which utilizes a genetic algorithm to optimize the link delay and resource configuration/consumption
Because the two important indexes of the aggregation algorithm are used to describe the accuracy of the original network topology information, Error Rejected Ratio (ERR) and Crank Back Ratio (CBR) can better reflect the influence of underestimation and overestimation distortions on network performance
Summary
The scale of optical networks is rapidly expanding with the development of optical communication technology [1], the structure of optical networks has changed greatly. The generation of original topology is one of the impetuses to solve the problems of scalability in large-scale multi-domain optical networks [2]. Considering the design of survivable virtual network mapping in multi-domain optical networks, the researchers propose a heuristic algorithm for survivable virtual network mapping using a partition and contraction mechanism (PCM) and based on cut set graph theory with the objective of minimizing the total network link cost [8]. The model of multi-objective optimization is given before designing the topology generation algorithm. Tisj represents the delay required for the business request s passing the link (i, j ). Uisj represents the bandwidth required for the business request s passing the link (i, j ) , Equation (3) represents the situation of resource consumption. Where λmax represents the maximum amount of business requests that a link can carry, so the first constraint represents the sum of business requests of link (i, j ) is less than λmax . bi is the number of optical transmitters owned by node i; The second constraint limits the number of links from node i to other nodes less than bi , representing an out-degree constraint; the third constraint is an in-degree constraint; The last constraint limits the value of xij to 0 or 1
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
