The Experts below are selected from a list of 18756 Experts worldwide ranked by ideXlab platform
Xiaofan Wang - One of the best experts on this subject based on the ideXlab platform.
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Effects of network structure and Routing Strategy on network capacity.
Physical Review E, 2006Co-Authors: Zhenyi Chen, Xiaofan WangAbstract:The capacity of maximum end-to-end traffic flow the network is able to handle without overloading is an important index for network performance in real communication systems. In this paper, we estimate the variations of network capacity under different Routing strategies for three different topologies. Simulation results reveal that the capacity depends on the underlying network structure and the capacity increases as the network becomes more homogeneous. It is also observed that the network capacity is greatly enhanced when the new traffic awareness Routing Strategy is adopted in each network structure.
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Effects of Network Capacity under Variations of Network Structure and Routing Strategy
2006 IEEE International Conference on Networking, Sensing and Control, 2006Co-Authors: Zhenyi Chen, Xiaofan WangAbstract:Network capacity, characterized by the maximum end-to-end traffic flow the network is able to handle without overloading, is an important index for network performance of real communication systems. In this paper, we estimate the effects of variations of network structure and Routing Strategy on network capacity. Simulation results reveal that the capacity depends on the underlying network structure and the capacity increases as the network becomes more homogeneous. It is also observed that the network capacity is greatly enhanced when the new traffic awareness Routing Strategy is adopted in each network structure
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A congestion awareness Routing Strategy for scale-free networks with tunable clustering
Physica A: Statistical Mechanics and its Applications, 2006Co-Authors: Zhenyi Chen, Xiaofan WangAbstract:Abstract By incorporating local traffic information into the basic shortest path Routing policy, we propose a congestion awareness Routing Strategy with a tunable parameter. We investigate the effectiveness of the proposed Routing Strategy for scale-free networks with different clustering coefficients and in different congestion phases. We find that there exists an optimal value for the tunable parameter in the congestion awareness Strategy. Though the optimal value increases slowly as the traffic in the network becomes heavier, it is almost independent of the clustering property of the scale-free network. Furthermore, the performance upgradation of the new Routing Strategy compared with the basic shortest path Routing policy becomes more significant as the network becomes more clustered.
Venson Shaw - One of the best experts on this subject based on the ideXlab platform.
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A genetic-based fault-tolerant Routing Strategy for multiprocessor networks
Future Generation Computer Systems, 2001Co-Authors: Peter K. K. Loh, Venson ShawAbstract:Abstract AI-based search techniques have been adapted as viable, topology-independent fault-tolerant Routing strategies on multiprocessor networks [P.K.K. Loh, Artificial intelligence search techniques as fault-tolerant Routing strategies, Parallel Computing 22 (8) (1996) 1127–1147]. These fault-tolerant Routing strategies are viable with the exception that the routes obtained were non-minimal. This meant that a large number of redundant node traversals were made in reaching the destination, increasing the likelihood of encountering further faulty network components. Here, we investigate the adaptation of a genetic-heuristic algorithm combination as a fault-tolerant Routing Strategy. Our results show that this hybrid fault-tolerant Routing Strategy produces minimal or near-minimal routes. Under certain fault conditions, this new Strategy outperforms the heuristic AI-based ones with a significant reduction in the number of redundant traversals.
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IPPS/SPDP Workshops - A Genetic-Based Fault-Tolerant Routing Strategy for Multiprocessor Networks
Lecture Notes in Computer Science, 1999Co-Authors: Peter K. K. Loh, Venson ShawAbstract:We have investigated the adaptation of AI-based search techniques as topology-independent fault-tolerant Routing strategies on multiprocessor networks [9]. The results showed that these search techniques are suitable for adaptation, as fault-tolerant Routing strategies with the exception that the routes obtained were non-minimal. In this research, we investigate the adaptation of a genetic-heuristic algorithm combination as a fault-tolerant Routing Strategy. Our results show that such a hybrid Strategy results in a viable fault-tolerant Routing Strategy, which produces minimal or near-minimal routes with a corresponding significant reduction in the number of redundant node traversals. Under certain fault conditions, this new hybrid Routing Strategy outperforms the purely heuristic ones.
Peter K. K. Loh - One of the best experts on this subject based on the ideXlab platform.
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ISPA - Design of a viable fault-tolerant Routing Strategy for optical-based grids
Parallel and Distributed Processing and Applications, 2003Co-Authors: Peter K. K. Loh, Wen-jing HsuAbstract:This paper proposes and analyses a cost-effective fault-tolerant Routing Strategy for optical-based grid networks. We present the design of a fully adaptive, fault-tolerant Routing Strategy for multi-hop grid networks based on wavelength-division multiplexing. The Routing Strategy is both deadlock-free and livelock-free. Regardless of the number and type of faults and size of the grid network, only three buffer sets and two Routing tables of size O(d) are required at each node, where d is the grid dimension. In the absence of faults, minimal paths with the least congestion are chosen to minimise latency. In the presence of faults or congestion, misRouting is selectively constrained to prevent livelock. The Routing Strategy requires only local fault information at each node, and does not require component redundancy or the isolation of healthy nodes and channels.
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A genetic-based fault-tolerant Routing Strategy for multiprocessor networks
Future Generation Computer Systems, 2001Co-Authors: Peter K. K. Loh, Venson ShawAbstract:Abstract AI-based search techniques have been adapted as viable, topology-independent fault-tolerant Routing strategies on multiprocessor networks [P.K.K. Loh, Artificial intelligence search techniques as fault-tolerant Routing strategies, Parallel Computing 22 (8) (1996) 1127–1147]. These fault-tolerant Routing strategies are viable with the exception that the routes obtained were non-minimal. This meant that a large number of redundant node traversals were made in reaching the destination, increasing the likelihood of encountering further faulty network components. Here, we investigate the adaptation of a genetic-heuristic algorithm combination as a fault-tolerant Routing Strategy. Our results show that this hybrid fault-tolerant Routing Strategy produces minimal or near-minimal routes. Under certain fault conditions, this new Strategy outperforms the heuristic AI-based ones with a significant reduction in the number of redundant traversals.
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IPPS/SPDP Workshops - A Genetic-Based Fault-Tolerant Routing Strategy for Multiprocessor Networks
Lecture Notes in Computer Science, 1999Co-Authors: Peter K. K. Loh, Venson ShawAbstract:We have investigated the adaptation of AI-based search techniques as topology-independent fault-tolerant Routing strategies on multiprocessor networks [9]. The results showed that these search techniques are suitable for adaptation, as fault-tolerant Routing strategies with the exception that the routes obtained were non-minimal. In this research, we investigate the adaptation of a genetic-heuristic algorithm combination as a fault-tolerant Routing Strategy. Our results show that such a hybrid Strategy results in a viable fault-tolerant Routing Strategy, which produces minimal or near-minimal routes with a corresponding significant reduction in the number of redundant node traversals. Under certain fault conditions, this new hybrid Routing Strategy outperforms the purely heuristic ones.
Zhenyi Chen - One of the best experts on this subject based on the ideXlab platform.
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Effects of network structure and Routing Strategy on network capacity.
Physical Review E, 2006Co-Authors: Zhenyi Chen, Xiaofan WangAbstract:The capacity of maximum end-to-end traffic flow the network is able to handle without overloading is an important index for network performance in real communication systems. In this paper, we estimate the variations of network capacity under different Routing strategies for three different topologies. Simulation results reveal that the capacity depends on the underlying network structure and the capacity increases as the network becomes more homogeneous. It is also observed that the network capacity is greatly enhanced when the new traffic awareness Routing Strategy is adopted in each network structure.
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Effects of Network Capacity under Variations of Network Structure and Routing Strategy
2006 IEEE International Conference on Networking, Sensing and Control, 2006Co-Authors: Zhenyi Chen, Xiaofan WangAbstract:Network capacity, characterized by the maximum end-to-end traffic flow the network is able to handle without overloading, is an important index for network performance of real communication systems. In this paper, we estimate the effects of variations of network structure and Routing Strategy on network capacity. Simulation results reveal that the capacity depends on the underlying network structure and the capacity increases as the network becomes more homogeneous. It is also observed that the network capacity is greatly enhanced when the new traffic awareness Routing Strategy is adopted in each network structure
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A congestion awareness Routing Strategy for scale-free networks with tunable clustering
Physica A: Statistical Mechanics and its Applications, 2006Co-Authors: Zhenyi Chen, Xiaofan WangAbstract:Abstract By incorporating local traffic information into the basic shortest path Routing policy, we propose a congestion awareness Routing Strategy with a tunable parameter. We investigate the effectiveness of the proposed Routing Strategy for scale-free networks with different clustering coefficients and in different congestion phases. We find that there exists an optimal value for the tunable parameter in the congestion awareness Strategy. Though the optimal value increases slowly as the traffic in the network becomes heavier, it is almost independent of the clustering property of the scale-free network. Furthermore, the performance upgradation of the new Routing Strategy compared with the basic shortest path Routing policy becomes more significant as the network becomes more clustered.
Dan Wang - One of the best experts on this subject based on the ideXlab platform.
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Mixed Routing Strategy in scale-free networks
2013 25th Chinese Control and Decision Conference (CCDC), 2013Co-Authors: Dan WangAbstract:In order to improve the network transportation efficiency, we propose a new Routing method called mixed Routing Strategy by considering packet generation rate is varied with time. The mixed Routing Strategy consists of two parts. When the packet generation rate is small, the shortest paths are used to deliver the packets, while the packet generation rate is large, we use the local Routing Strategy. Numerical results shown that with proper design on the shifting instances between the two Routing methods according to the traffic dynamic behavior, the mixed Routing has better network performance than the shortest path Routing and the local Routing Strategy.
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Routing Strategy based on static and dynamic information
2011 Chinese Control and Decision Conference (CCDC), 2011Co-Authors: Dan Wang, Xiaolong Qian, Yuanwei JingAbstract:Two kinds of Routing strategies are proposed respectively based on local topological and dynamic information for enhancing the efficiency of traffic delivery on scale-free networks. The two strategies are governed separately by a single parameter. Simulation results show that the capacity of maximum traffic flow is greatly enhanced by the optimal controlled parameter of new Routing Strategy. Moreover, a simulation is performed in a model of scale-free network with different clustering coefficient by adopting the local topological Routing Strategy with the optimal parameter, and the results revealed that the more clustered network, the less efficient the packet delivery process. Finally, it would be worth noticing at this point that, the proposed strategies are easily implemented, since local topological and dynamic information can be both straightly obtained.
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traffic dynamics based on a traffic awareness Routing Strategy on scale free networks
Physica A-statistical Mechanics and Its Applications, 2008Co-Authors: Dan Wang, Yuanwei Jing, Siying ZhangAbstract:Abstract By incorporating local traffic information into the shortest path Routing Strategy, we numerically investigate the effectiveness of the traffic awareness Routing Strategy for scale-free networks with different clustering. In order to characterize the efficiency of the packet-delivery process, we introduce an order parameter and an average transmission time that allow us to measure the network capacity by the critical value of phase transition from free flow to congestion. Compared with the shortest path Routing protocol, the network capacity is greatly enhanced by the traffic awareness Routing Strategy. We also find that there exists an optimum value for the tunable parameter in the congestion awareness Strategy. Moreover, simulation results show that the more clustered the network, the less efficient the packet-delivery process.
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APWeb - An ant algorithm based dynamic Routing Strategy for mobile agents
Web Technologies and Applications, 2003Co-Authors: Dan Wang, Baoyan Song, Derong Shen, Guoren WangAbstract:Routing Strategy is one of the most important aspects in a mobile agent system, which is a complex combinatorial problem. Most of current mobile agent systems adopt static Routing strategies, which don't consider dynamic network status and host status. This is a hinder to the performance and autonomy of mobile agents. Ant Algorithm is good at solving such kind of problems. After analyzing existing Routing strategies of typical mobile agent systems, this paper summarizes factors that may affect Routing Strategy of mobile agents, proposes an Ant Algorithm based dynamic Routing Strategy by using both experience and network environment such as resource information, network traffic, host workload, presents an acquiring and storing method of Routing parameters and decision rules according to the major characteristics of mobile agent migration. The simulation experiment is implemented and the results show our dynamic Routing Strategy can effectively improve the performance and autonomy of mobile agents.
