In the Internet, a group of replicated servers is commonly used in order to improve the scalability of network service. Anycast service is a new network service that can improve network load distribution and simplify ...In the Internet, a group of replicated servers is commonly used in order to improve the scalability of network service. Anycast service is a new network service that can improve network load distribution and simplify certain applications. In this paper, the authors described a simple anycast service model in the Internet without significant affecting the routing and protocol processing infrastructure that was already in place, and proposed an anycast QoS routing algorithm for this model. The algorithm used randomized method to balance network load and improve its performance. Several new techniques are proposed in the algorithm, first, theminimum hops for each node are used in the algorithm, which are used as metric for computing the probability of possible out links. The metric is pre computed for each node in the network, which can simplify the network complexity and provide the routing process with useful information. Second, randomness is used at the link level and depends dynamically on the routing configuration. This provides great flexibility for the routing process, prevents the routing process from overusing certain fixed routing paths, and adequately balances the delay of the routing path. the authors assess the quality of QoS algorithm in terms of the acceptance ratio on anycast QoS requests, and the simulation results on a variety of network topologies and on various parameters show that the algorithm has good performances and can balance network load effectively.展开更多
Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a ...Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a mathematical model for multi-depot heterogeneous vehicle routing problem with soft time windows （MDHVRPSTW） is established. An improved ant colony optimization （IACO） is proposed for solving this model. First, MDHVRPSTW is transferred into different groups according to the nearest principle, and then the initial route is constructed by the scanning algorithm （SA）. Secondly, genetic operators are introduced, and crossover probability and mutation probability are adaptively adjusted in order to improve the global search ability of the algorithm. Moreover, the smooth mechanism is used to improve the performance of the ant colony optimization （ACO）. Finally, the 3-opt strategy is used to improve the local search ability. The proposed IACO was tested on three new instances that were generated randomly. The experimental results show that IACO is superior to the other three existing algorithms in terms of convergence speed and solution quality. Thus, the proposed method is effective and feasible, and the proposed model is meaningful.展开更多
基金TheNationalScienceFundforOverseasDistinguishedYoungScholars (No .6 992 82 0 1)FoundationforUniversityKeyTeacherbytheMinist
文摘In the Internet, a group of replicated servers is commonly used in order to improve the scalability of network service. Anycast service is a new network service that can improve network load distribution and simplify certain applications. In this paper, the authors described a simple anycast service model in the Internet without significant affecting the routing and protocol processing infrastructure that was already in place, and proposed an anycast QoS routing algorithm for this model. The algorithm used randomized method to balance network load and improve its performance. Several new techniques are proposed in the algorithm, first, theminimum hops for each node are used in the algorithm, which are used as metric for computing the probability of possible out links. The metric is pre computed for each node in the network, which can simplify the network complexity and provide the routing process with useful information. Second, randomness is used at the link level and depends dynamically on the routing configuration. This provides great flexibility for the routing process, prevents the routing process from overusing certain fixed routing paths, and adequately balances the delay of the routing path. the authors assess the quality of QoS algorithm in terms of the acceptance ratio on anycast QoS requests, and the simulation results on a variety of network topologies and on various parameters show that the algorithm has good performances and can balance network load effectively.
基金The National Natural Science Foundation of China(No.61074147)the Natural Science Foundation of Guangdong Province(No.S2011010005059)+2 种基金the Foundation of Enterprise-University-Research Institute Cooperation from Guangdong Province and Ministry of Education of China(No.2012B091000171,2011B090400460)the Science and Technology Program of Guangdong Province(No.2012B050600028)the Science and Technology Program of Huadu District,Guangzhou(No.HD14ZD001)
文摘Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a mathematical model for multi-depot heterogeneous vehicle routing problem with soft time windows （MDHVRPSTW） is established. An improved ant colony optimization （IACO） is proposed for solving this model. First, MDHVRPSTW is transferred into different groups according to the nearest principle, and then the initial route is constructed by the scanning algorithm （SA）. Secondly, genetic operators are introduced, and crossover probability and mutation probability are adaptively adjusted in order to improve the global search ability of the algorithm. Moreover, the smooth mechanism is used to improve the performance of the ant colony optimization （ACO）. Finally, the 3-opt strategy is used to improve the local search ability. The proposed IACO was tested on three new instances that were generated randomly. The experimental results show that IACO is superior to the other three existing algorithms in terms of convergence speed and solution quality. Thus, the proposed method is effective and feasible, and the proposed model is meaningful.
