Papers by Pongsarun Boonyopakorn
The First International Conference on Future Generation Communication Technologies, 2012
Traffic Engineering requires efficient tools to optimize network performance and traffic delivery... more Traffic Engineering requires efficient tools to optimize network performance and traffic delivery. This paper covers the canalization of performance problems found in IP networks called Autonomous System (AS), to maximize the admitted traffic flow transmission without delay violations. The solution approach can be divided into two sub-problems. The first applies the placement algorithms to determine the gateway locations; the second applies the selection algorithms to dynamically route flows via one of the pre-determined gateways in real-time. The results indicate that the placement locations will perform best when the path length to the gateway and the current residual bandwidth are both taken into consideration which has higher priority to the first one.
This paper covers the analyzing performance problems found in IP networks called Autonomous Syste... more This paper covers the analyzing performance problems found in IP networks called Autonomous System (AS), to maximize the admitted traffic flows. We present a hybrid genetic algorithm approach to optimize the summary of admitted traffic where a hybrid GA approach is combined with an order-based Genetic Algorithm and Greedy then apply the Tabu Search Algorithm to find the optimal solution. We then, implement three certain algorithms to compare the results which are GA, Kcenter, and Greedy. In conclusion, the Tabu search algorithm shows the best performance and yielded significant improvements over techniques that only tried to minimize the length of the traffic routes or minimize bandwidth through the gateways.
A Genetic Algorithm (GA) is an approach to design a network, this is the ultimate solution becaus... more A Genetic Algorithm (GA) is an approach to design a network, this is the ultimate solution because traditional heuristics have limited success. This paper covers the analyzing performance problems found in service network gateways (AS), to maximize the admitted traffic flows. We present a hybrid genetic algorithm approach to optimize the summary of admitted traffic where a hybrid GA approach is combined with an order-based genetic algorithm and the greedy algorithm. We then, implement two certain algorithms which are K-center and Greedy to compare the results. In conclusion, the hybrid genetic algorithms show the best performance and yield significant improvements over techniques that only tried to minimize the length of the traffic routes or minimize bandwidth through the gateways.
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Papers by Pongsarun Boonyopakorn