scholarly journals Trunk Decomposition Based Global Routing Optimization

Author(s):  
Devang Jariwala ◽  
John Lillis
2013 ◽  
Vol 756-759 ◽  
pp. 2147-2151
Author(s):  
Dan Zhao ◽  
Xiao Feng Hu ◽  
Chun Qing Wu

Hot-potato routing is commonly used to break tie among multiple equally-good exit points associating with inter-domain BGP routes. However, hot-potato routing only takes the network control plane into consideration, where it provides the routers the possibility of enabling early exit of traffic using barely protocol-related information of IGP distance. In this paper, we argue that egress selection of inter-domain routing should pay more attention to traffic forwarding, because the large traffic migration caused by egress change, although not quite often, can degrade the network performance or even make the network crash. We propose Egress Selection based on Traffic Migration Prediction (ES-TMP). We use traffic demand to predict the traffic migration, which is used as important criteria for egress selection. If the volume of traffic migration is large, ES-TMP keeps the egress unchanged. Otherwise, the small traffic migration enables the routers use the closest egress without apparent influence on network performance. ES-TMP can either be implemented with standard BGP protocol or by dedicated servers to perform global routing optimization.


Author(s):  
Subhrapratim Nath ◽  
Rabiraj Bandyopadhyay ◽  
Saptarshi Biswas ◽  
Jamuna Kanta Sing ◽  
Subir Kumar Sarkar

2021 ◽  
Author(s):  
Tiago Augusto Fontana ◽  
Erfan Aghaeekiasaraee ◽  
Renan Netto ◽  
Sheiny Fabre Almeida ◽  
Upma Gandh ◽  
...  

Author(s):  
Jaya Pratha Sebastiyar ◽  
Martin Sahayaraj Joseph

Distributed joint congestion control and routing optimization has received a significant amount of attention recently. To date, however, most of the existing schemes follow a key idea called the back-pressure algorithm. Despite having many salient features, the first-order sub gradient nature of the back-pressure based schemes results in slow convergence and poor delay performance. To overcome these limitations, the present study was made as first attempt at developing a second-order joint congestion control and routing optimization framework that offers utility-optimality, queue-stability, fast convergence, and low delay.  Contributions in this project are three-fold. The present study propose a new second-order joint congestion control and routing framework based on a primal-dual interior-point approach and established utility-optimality and queue-stability of the proposed second-order method. The results of present study showed that how to implement the proposed second-order method in a distributed fashion.


Author(s):  
Kaixian Gao ◽  
Guohua Yang ◽  
Xiaobo Sun

With the rapid development of the logistics industry, the demand of customer become higher and higher. The timeliness of distribution becomes one of the important factors that directly affect the profit and customer satisfaction of the enterprise. If the distribution route is planned rationally, the cost can be greatly reduced and the customer satisfaction can be improved. Aiming at the routing problem of A company’s vehicle distribution link, we establish mathematical models based on theory and practice. According to the characteristics of the model, genetic algorithm is selected as the algorithm of path optimization. At the same time, we simulate the actual situation of a company, and use genetic algorithm to plan the calculus. By contrast, the genetic algorithm suitable for solving complex optimization problems, the practicability of genetic algorithm in this design is highlighted. It solves the problem of unreasonable transportation of A company, so as to get faster efficiency and lower cost.


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