A quality of service （QoS） or constraint-based routing selection needs to find a path subject to multiple constraints through a network. The problem of finding such a path is known as the multi-constrained path （MC...A quality of service （QoS） or constraint-based routing selection needs to find a path subject to multiple constraints through a network. The problem of finding such a path is known as the multi-constrained path （MCP） problem, and has been proven to be NP-complete that cannot be exactly solved in a polynomial time. The NPC problem is converted into a multiobjective optimization problem with constraints to be solved with a genetic algorithm. Based on the Pareto optimum, a constrained routing computation method is proposed to generate a set of nondominated optimal routes with the genetic algorithm mechanism. The convergence and time complexity of the novel algorithm is analyzed. Experimental results show that multiobjective evolution is highly responsive and competent for the Pareto optimum-based route selection. When this method is applied to a MPLS and metropolitan-area network, it will be capable of optimizing the transmission performance.展开更多
Multi-constrained Quality-of-Service (QoS) routing is a big challenge for Mobile Ad hoc Networks (MANETs) where the topology may change constantly. In this paper a novel QoS Routing Algorithm based on Simulated Anneal...Multi-constrained Quality-of-Service (QoS) routing is a big challenge for Mobile Ad hoc Networks (MANETs) where the topology may change constantly. In this paper a novel QoS Routing Algorithm based on Simulated Annealing (SA_RA) is proposed. This algorithm first uses an energy function to translate multiple QoS weights into a single mixed metric and then seeks to find a feasible path by simulated annealing. The pa- per outlines simulated annealing algorithm and analyzes the problems met when we apply it to Qos Routing (QoSR) in MANETs. Theoretical analysis and experiment results demonstrate that the proposed method is an effective approximation algorithms showing better performance than the other pertinent algorithm in seeking the (approximate) optimal configuration within a period of polynomial time.展开更多
In order to establish a route supporting multi-constrained quality of service（QoS）, increase network throughput and reduce network energy consumption, an improved ant colony-based multi-constrained QoS energy-saving...In order to establish a route supporting multi-constrained quality of service（QoS）, increase network throughput and reduce network energy consumption, an improved ant colony-based multi-constrained QoS energy-saving routing algorithm（IAMQER） is proposed. The ant colony algorithm, as one of the available heuristic algorithms, is used to find the optimal route from source node to destination node. The proposed IAMQER algorithm, which is based on the analysis of local node information such as node queue length, node forwarding number of data packets and node residual energy, balances the relationship between the network throughput and the energy consumption, thus improving the performance of network in multi-constrained QoS routing. Simulation results show that this IAMQER algorithm can find the QoS route that reduce average energy consumption and improves network packet delivery ratio under the end-to-end delay and packet loss ratio constraints.展开更多
基金the Natural Science Foundation of Anhui Province of China (050420212)the Excellent Youth Science and Technology Foundation of Anhui Province of China (04042069).
文摘A quality of service （QoS） or constraint-based routing selection needs to find a path subject to multiple constraints through a network. The problem of finding such a path is known as the multi-constrained path （MCP） problem, and has been proven to be NP-complete that cannot be exactly solved in a polynomial time. The NPC problem is converted into a multiobjective optimization problem with constraints to be solved with a genetic algorithm. Based on the Pareto optimum, a constrained routing computation method is proposed to generate a set of nondominated optimal routes with the genetic algorithm mechanism. The convergence and time complexity of the novel algorithm is analyzed. Experimental results show that multiobjective evolution is highly responsive and competent for the Pareto optimum-based route selection. When this method is applied to a MPLS and metropolitan-area network, it will be capable of optimizing the transmission performance.
基金Supported by the National Natural Science Foundation of China (No.60472104), the Natural Science Research Program of Jiangsu Province (No.04KJB510094).
文摘Multi-constrained Quality-of-Service (QoS) routing is a big challenge for Mobile Ad hoc Networks (MANETs) where the topology may change constantly. In this paper a novel QoS Routing Algorithm based on Simulated Annealing (SA_RA) is proposed. This algorithm first uses an energy function to translate multiple QoS weights into a single mixed metric and then seeks to find a feasible path by simulated annealing. The pa- per outlines simulated annealing algorithm and analyzes the problems met when we apply it to Qos Routing (QoSR) in MANETs. Theoretical analysis and experiment results demonstrate that the proposed method is an effective approximation algorithms showing better performance than the other pertinent algorithm in seeking the (approximate) optimal configuration within a period of polynomial time.
基金supported by the National Natural Science Foundation of China(61101107)the Beijing Higher Education Young Elite Teacher Project
文摘In order to establish a route supporting multi-constrained quality of service（QoS）, increase network throughput and reduce network energy consumption, an improved ant colony-based multi-constrained QoS energy-saving routing algorithm（IAMQER） is proposed. The ant colony algorithm, as one of the available heuristic algorithms, is used to find the optimal route from source node to destination node. The proposed IAMQER algorithm, which is based on the analysis of local node information such as node queue length, node forwarding number of data packets and node residual energy, balances the relationship between the network throughput and the energy consumption, thus improving the performance of network in multi-constrained QoS routing. Simulation results show that this IAMQER algorithm can find the QoS route that reduce average energy consumption and improves network packet delivery ratio under the end-to-end delay and packet loss ratio constraints.
