在分层图模型的基础上,本文提出一种以最小化全网光路总代价为优化目标的 IP over WDM 光网络动态路由优化模型,设计了一种针对该模型的在线综合路由算法—MCTLP(Minimizing the Cost of Total Lightpaths),MCTLP 通过综合考虑 IP 逻辑...在分层图模型的基础上,本文提出一种以最小化全网光路总代价为优化目标的 IP over WDM 光网络动态路由优化模型,设计了一种针对该模型的在线综合路由算法—MCTLP(Minimizing the Cost of Total Lightpaths),MCTLP 通过综合考虑 IP 逻辑层带宽资源分配和 WDM 光物理层波长链路资源的占用以优化网络资源。与两种有代表性的 IP over WDM 光网络路由算法的性能仿真对比表明:MCTLP 能够在 IP 逻辑层和 WDM 光物理层都使用较少的链路以承载 IP 业务流,接纳更多的 IP 业务连接请求,有效地降低网络阻塞率。展开更多
Capacitated vehicle routing problem (CVRP) is an NP-hard problem. For large-scale problems, it is quite difficult to achieve an optimal solution with traditional optimization methods due to the high computational comp...Capacitated vehicle routing problem (CVRP) is an NP-hard problem. For large-scale problems, it is quite difficult to achieve an optimal solution with traditional optimization methods due to the high computational complexity. A new hybrid ap- proximation algorithm is developed in this work to solve the problem. In the hybrid algorithm, discrete particle swarm optimiza- tion (DPSO) combines global search and local search to search for the optimal results and simulated annealing (SA) uses certain probability to avoid being trapped in a local optimum. The computational study showed that the proposed algorithm is a feasible and effective approach for capacitated vehicle routing problem, especially for large scale problems.展开更多
描述优化链路状态路由算法OLSR(Optimized Link State Routing)协议的特点,分析自组网中OLSR路由协议脆弱性以及它可能遭受的各种攻击,并基于身份的签名机制,提出一种基于身份的签名认证的安全OLSR路由协议的解决方案,并对该新路由算法...描述优化链路状态路由算法OLSR(Optimized Link State Routing)协议的特点,分析自组网中OLSR路由协议脆弱性以及它可能遭受的各种攻击,并基于身份的签名机制,提出一种基于身份的签名认证的安全OLSR路由协议的解决方案,并对该新路由算法的性能进行仿真比较分析。展开更多
Genetic Algorithm (GA) is a biologically inspired technique and widely used to solve numerous combinational optimization problems. It works on a population of individuals, not just one single solution. As a result, it...Genetic Algorithm (GA) is a biologically inspired technique and widely used to solve numerous combinational optimization problems. It works on a population of individuals, not just one single solution. As a result, it avoids converging to the local optimum. However, it takes too much CPU time in the late process of GA. On the other hand, in the late process Simulated Annealing (SA) converges faster than GA but it is easily trapped to local optimum. In this letter, a useful method that unifies GA and SA is introduced, which utilizes the advantage of the global search ability of GA and fast convergence of SA. The experimental results show that the proposed algorithm outperforms GA in terms of CPU time without degradation of performance. It also achieves highly comparable placement cost compared to the state-of-the-art results obtained by Versatile Place and Route (VPR) Tool.展开更多
A supervised genetic algorithm (SGA) is proposed to solve the quality of service (QoS) routing problems in computer networks. The supervised rules of intelligent concept are introduced into genetic algorithms (GAs) to...A supervised genetic algorithm (SGA) is proposed to solve the quality of service (QoS) routing problems in computer networks. The supervised rules of intelligent concept are introduced into genetic algorithms (GAs) to solve the constraint optimization problem. One of the main characteristics of SGA is its searching space can be limited in feasible regions rather than infeasible regions. The superiority of SGA to other GAs lies in that some supervised search rules in which the information comes from the problems are incorporated into SGA. The simulation results show that SGA improves the ability of searching an optimum solution and accelerates the convergent process up to 20 times.展开更多
Opportunistic networks are random networks and do not communicate with each other among respective communication areas.This situation leads to great difficulty in message transfer.This paper proposes a reducing energy...Opportunistic networks are random networks and do not communicate with each other among respective communication areas.This situation leads to great difficulty in message transfer.This paper proposes a reducing energy consumption optimal selection of path transmission(OSPT) routing algorithm in opportunistic networks.This algorithm designs a dynamic random network topology,creates a dynamic link,and realizes an optimized selected path.This algorithm solves a problem that nodes are unable to deliver messages for a long time in opportunistic networks.According to the simulation experiment,OSPT improves deliver ratio,and reduces energy consumption,cache time and transmission delay compared with the Epidemic Algorithm and Spray and Wait Algorithm in opportunistic networks.展开更多
To improve the robustness of the Low Earth Orbit(LEO) satellites networks and realise load balancing, a Cross-layer design and Ant-colony optimization based Load-balancing routing algorithm for LEO Satellite Networks(...To improve the robustness of the Low Earth Orbit(LEO) satellites networks and realise load balancing, a Cross-layer design and Ant-colony optimization based Load-balancing routing algorithm for LEO Satellite Networks(CAL-LSN) is proposed in this paper. In CALLSN, mobile agents are used to gather routing information actively. CAL-LSN can utilise the information of the physical layer to make routing decision during the route construction phase. In order to achieve load balancing, CALLSN makes use of a multi-objective optimization model. Meanwhile, how to take the value of some key parameters is discussed while designing the algorithm so as to improve the reliability. The performance is measured by the packet delivery rate, the end-to-end delay, the link utilization and delay jitter. Simulation results show that CAL-LSN performs well in balancing traffic load and increasing the packet delivery rate. Meanwhile, the end-to-end delay and delay jitter performance can meet the requirement of video transmission.展开更多
文摘在分层图模型的基础上,本文提出一种以最小化全网光路总代价为优化目标的 IP over WDM 光网络动态路由优化模型,设计了一种针对该模型的在线综合路由算法—MCTLP(Minimizing the Cost of Total Lightpaths),MCTLP 通过综合考虑 IP 逻辑层带宽资源分配和 WDM 光物理层波长链路资源的占用以优化网络资源。与两种有代表性的 IP over WDM 光网络路由算法的性能仿真对比表明:MCTLP 能够在 IP 逻辑层和 WDM 光物理层都使用较少的链路以承载 IP 业务流,接纳更多的 IP 业务连接请求,有效地降低网络阻塞率。
基金Project (No. 60174009) supported by the National Natural ScienceFoundation of China
文摘Capacitated vehicle routing problem (CVRP) is an NP-hard problem. For large-scale problems, it is quite difficult to achieve an optimal solution with traditional optimization methods due to the high computational complexity. A new hybrid ap- proximation algorithm is developed in this work to solve the problem. In the hybrid algorithm, discrete particle swarm optimiza- tion (DPSO) combines global search and local search to search for the optimal results and simulated annealing (SA) uses certain probability to avoid being trapped in a local optimum. The computational study showed that the proposed algorithm is a feasible and effective approach for capacitated vehicle routing problem, especially for large scale problems.
基金Supported by School of Engineering, Napier University, United Kingdom, and partially supported by the National Natural Science Foundation of China (No.60273093).
文摘Genetic Algorithm (GA) is a biologically inspired technique and widely used to solve numerous combinational optimization problems. It works on a population of individuals, not just one single solution. As a result, it avoids converging to the local optimum. However, it takes too much CPU time in the late process of GA. On the other hand, in the late process Simulated Annealing (SA) converges faster than GA but it is easily trapped to local optimum. In this letter, a useful method that unifies GA and SA is introduced, which utilizes the advantage of the global search ability of GA and fast convergence of SA. The experimental results show that the proposed algorithm outperforms GA in terms of CPU time without degradation of performance. It also achieves highly comparable placement cost compared to the state-of-the-art results obtained by Versatile Place and Route (VPR) Tool.
基金China Postdoctoral Foundation (No2005037529)Doctoral Foundation of Education Ministry of China (No2003005607)Tianjin High Education Science Development Foundation (No20041325)
文摘A supervised genetic algorithm (SGA) is proposed to solve the quality of service (QoS) routing problems in computer networks. The supervised rules of intelligent concept are introduced into genetic algorithms (GAs) to solve the constraint optimization problem. One of the main characteristics of SGA is its searching space can be limited in feasible regions rather than infeasible regions. The superiority of SGA to other GAs lies in that some supervised search rules in which the information comes from the problems are incorporated into SGA. The simulation results show that SGA improves the ability of searching an optimum solution and accelerates the convergent process up to 20 times.
基金Supported by the National Natural Science Foundation of China(No.61379057,61073186,61309001,61379110,61103202)Doctoral Fund of Ministry of Education of China(No.20120162130008)the National Basic Research Program of China(973 Program)(No.2014CB046305)
文摘Opportunistic networks are random networks and do not communicate with each other among respective communication areas.This situation leads to great difficulty in message transfer.This paper proposes a reducing energy consumption optimal selection of path transmission(OSPT) routing algorithm in opportunistic networks.This algorithm designs a dynamic random network topology,creates a dynamic link,and realizes an optimized selected path.This algorithm solves a problem that nodes are unable to deliver messages for a long time in opportunistic networks.According to the simulation experiment,OSPT improves deliver ratio,and reduces energy consumption,cache time and transmission delay compared with the Epidemic Algorithm and Spray and Wait Algorithm in opportunistic networks.
基金supported by the National Natural Science Foundation of China under Grant No.61271281the National High Technology Research and Development Program of China (863 Program) under Grant No.SS2013AA010503
文摘To improve the robustness of the Low Earth Orbit(LEO) satellites networks and realise load balancing, a Cross-layer design and Ant-colony optimization based Load-balancing routing algorithm for LEO Satellite Networks(CAL-LSN) is proposed in this paper. In CALLSN, mobile agents are used to gather routing information actively. CAL-LSN can utilise the information of the physical layer to make routing decision during the route construction phase. In order to achieve load balancing, CALLSN makes use of a multi-objective optimization model. Meanwhile, how to take the value of some key parameters is discussed while designing the algorithm so as to improve the reliability. The performance is measured by the packet delivery rate, the end-to-end delay, the link utilization and delay jitter. Simulation results show that CAL-LSN performs well in balancing traffic load and increasing the packet delivery rate. Meanwhile, the end-to-end delay and delay jitter performance can meet the requirement of video transmission.
