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共有20条相似文献,以下是第1-20项 搜索用时 406 毫秒

1.  SSTT: Efficient Local Search for GSI Global Routing  被引次数:6
   经彤  洪先龙  鲍海云  许静宇  顾钧《计算机科学技术学报》,2003年第18卷第5期
   In this paper, a novel global routing algorithm is presented for congestion opti-mization based on efficient local search, named SSTT (search space traversing technology). This method manages to traverse the whole search space. A hybrid optimization strategy is adopted,consisting of three optimization sub-strategies: stochastic optimization, deterministic optimiza-tion and local enumeration optimization, to dynamically reconstruct the problem structure. Thus,“transition” can be made from a local minimum point to reach other parts of the search space,traverse the whole search space, and obtain the global (approximate) optimal routing solution.Since any arbitrary initial routing solution can be used as the start point of the search, the initial-ization in SSTT algorithm is greatly simplified. SSTT algorithm has been tested on both MCNC benchmark circuits and industrial circuits, and the experimental results were compared with those of typical existing algorithms. The experimental results show that SSTT algorithm can obtain the global (approximate) optimal routing solution easily and quickly. Moreover, it can meet the needs of practical applications. The SSTT global routing algorithm gives a general-purpose routing solution.    

2.  Spray and forward:Efficient routing based on the Markov location prediction model for DTNs  
   DANG Fei  YANG XiaoLong  & LONG KePing  Research Center for Optical Internet and Mobile Information NetworksCOIMIN  University of Electronic Science and Technology of China  Chengdu  China;《中国科学:信息科学(英文版)》,2012年第2期
   Typical delay tolerant networks(DTNs)often suffer from long and variable delays,frequent connectivity disruptions,and high bit error rates.In DTNs,the design of an efficient routing algorithm is one of the key issues.The existing methods improve the accessibility probability of the data transmission by transmitting many copies of the packet to the network,but they may cause a high network overhead.To address the tradeoff between a successful delivery ratio and the network overhead,we propose a DTN routing algorithm based on the Markov location prediction model,called the spray and forward routing algorithm(SFR).Based on historical information of the nodes,the algorithm uses the second-order Markov forecasting mechanism to predict the location of the destination node,and then forwards the data by greedy routing,which reduces the copies of packets by spraying the packets in a particular direction.In contrast to a fixed mode where a successful-delivery ratio and routing overhead are contradictory,a hybrid strategy with multi-copy forwarding is able to reduce the copies of the packets efficiently and at the same time maintain an acceptable successful-delivery ratio.The simulation results show that the proposed SFR is efficient enough to provide better network performance than the spray and wait routing algorithm,in scenarios with sparse node density and fast mobility of the nodes.    

3.  HierTrack: an energy-efficient cluster-based target tracking system forwireless sensor networks  
   Zhi-bo WANG  Zhi WANG  Hong-long CHEN  Jian-feng LI  Hong-bin LI  Jie SHEN《浙江大学学报:C卷英文版》,2013年第14卷第6期
   Target tracking is a typical and important application of wireless sensor networks(WSNs).Existing target tracking protocols focus mainly on energy efficiency,and little effort has been put into network management and real-time data routing,which are also very important issues for target tracking.In this paper,we propose a scalable cluster-based target tracking framework,namely the hierarchical prediction strategy(HPS),for energyefficient and real-time target tracking in large-scale WSNs.HPS organizes sensor nodes into clusters by using suitable clustering protocols which are beneficial for network management and data routing.As a target moves in the network,cluster heads predict the target trajectory using Kalman filter and selectively activate the next round of sensors in advance to keep on tracking the target.The estimated locations of the target are routed to the base station via the backbone composed of the cluster heads.A soft handoff algorithm is proposed in HPS to guarantee smooth tracking of the target when the target moves from one cluster to another.Under the framework of HPS,we design and implement an energy-efficient target tracking system,HierTrack,which consists of 36 sensor motes,a sink node,and a base station.Both simulation and experimental results show the efficiency of our system.    

4.  A hybrid genetic algorithm to optimize device allocation in industrial Ethernet networks with real-time constraints  
   Mattias LAMPE《浙江大学学报:C卷英文版》,2011年第12期
   With the advance of automation technology,the scale of industrial communication networks at field level is growing.Guaranteeing real-time performance of these networks is therefore becoming an increasingly difficult task.This paper addresses the optimization of device allocation in industrial Ethernet networks with real-time constraints (DAIEN-RC).Considering the inherent diversity of real-time requirements of typical industrial applications,a novel optimization criterion based on relative delay is proposed.A hybrid genetic algorithm incorporating a reduced variable neighborhood search (GA-rVNS) is developed for DAIEN-RC.Experimental results show that the proposed novel scheme achieves a superior performance compared to existing schemes,especially for large scale industrial networks.    

5.  A genetic algorithm for the pareto optimal solution set of multi-objective shortest path problem  
   胡仕成 徐晓飞 战德臣《哈尔滨工业大学学报(英文版)》,2005年第12卷第6期
   Unlike the shortest path problem that has only one optimal solution and can be solved in polynomial time, the muhi-objective shortest path problem ( MSPP ) has a set of pareto optimal solutions and cannot be solved in polynomial time. The present algorithms focused mainly on how to obtain a precisely pareto optimal solution for MSPP resulting in a long time to obtain multiple pareto optimal solutions with them. In order to obtain a set of satisfied solutions for MSPP in reasonable time to meet the demand of a decision maker, a genetic algo- rithm MSPP-GA is presented to solve the MSPP with typically competing objectives, cost and time, in this pa- per. The encoding of the solution and the operators such as crossover, mutation and selection are developed. The algorithm introduced pareto domination tournament and sharing based selection operator, which can not only directly search the pareto optimal frontier but also maintain the diversity of populations in the process of evolutionary computation. Experimental results show that MSPP-GA can obtain most efficient solutions distributed all along the pareto frontier in less time than an exact algorithm. The algorithm proposed in this paper provides a new and effective method of how to obtain the set of pareto optimal solutions for other multiple objective optimization problems in a short time.    

6.  Fast convergence caching replacement algorithm based on dynamic classification for content-centric networks  
   FANG Chao  HUANG Tao  LIU Jiang  CHEN  Jian-ya LIU  Yun-jie《中国邮电高校学报(英文版)》,2013年第5期
   One of the key research fields of content-centric networking (CCN) is to develop more efficient cache replacement policies to improve the hit ratio of CCN in-network caching. However, most of existing cache strategies designed mainly based on the time or frequency of content access, can not properly deal with the problem of the dynamicity of content popularity in the network. In this paper, we propose a fast convergence caching replacement algorithm based on dynamic classification method for CCN, named as FCDC. It develops a dynamic classification method to reduce the time complexity of cache inquiry, which achieves a higher caching hit rate in comparison to random classification method under dynamic change of content popularity. Meanwhile, in order to relieve the influence brought about by dynamic content popularity, it designs a weighting function to speed up cache hit rate convergence in the CCN router. Experimental results show that the proposed scheme outperforms the replacement policies related to least recently used (LRU) and recent usage frequency (RUF) in cache hit rate and resiliency when content popularity in the network varies.    

7.  QoS路由的不确定信息研究:形式化描述与分析  
   桂志波 胡仲海《计算机科学》,2003年第30卷第11期
   In order to guarantee network quality of service(QoS), QoS routing algorithms try to find an optimal path that can provide sufficient resources to accommodate the performance requirements such as delay, jitter, bandwidth, loss rate and so on required by applications. According to unique or multiple metrics, most of the existing routing algorithms take bandwidth and propagation delay as routing metrics and find out the smallest propagation delay path among all widest paths and so on. Realistic networks are a kind of time-varying, dynamic and complex systems, so the network state information required by QoS routing is uncertain inherently. In this paper, formalization description of uncertain information for QoS routing is carried, and its emerging causes are analyzed. Then, the relevant analytical models and optimization algorithms and solutions for QoS routing with uncertain information are discussed based on bandwidth and delay. Moreover, further research on uncertain information for QoS routing is discussed.    

8.  A Learning Automata Based Area Coverage Algorithm for Wireless Sensor Networks  被引次数:1
   Habib Mostafaei  Mohammad Reza Meybodi  Mehdi Esnaashari《中国电子科技》,2010年第8卷第3期
   One way to reduce energy consumption in wireless sensor networks is to reduce the number of active nodes in the network. When sensors are redundantly deployed, a subset of sensors should be selected to actively monitor the field (referred to as a "cover"), whereas the rest of the sensors should be put to sleep to conserve their batteries. In this paper, a learning automata based algorithm for energy-efficient monitoring in wireless sensor networks (EEMLA) is proposed. Each node in EEMLA algorithm is equipped with a learning automaton which decides for the node to be active or not at any time during the operation of the network. Using feedback received from neighboring nodes, each node gradually learns its proper state during the operation of the network. Experimental results have shown that the proposed monitoring algorithm in comparison to other existing methods such as Tian and LUC can better prolong the network lifetime.    

9.  High efficient methods of content-based 3D model retrieval  
   WU Yuanhao  TIAN Ling  LI Chenggang《机械工程学报(英文版)》,2013年第26卷第2期
   Content-based 3D model retrieval is of great help to facilitate the reuse of existing designs and to inspire designers during conceptual design. However, there is still a gap to apply it in industry due to the low time efficiency. This paper presents two new methods with high efficiency to build a Content-based 3D model retrieval system. First, an improvement is made on the "Shape Distribution (D2)" algorithm, and a new algorithm named "Quick D2" is proposed. Four sample 3D mechanical models are used in an experiment to compare the time cost of the two algorithms. The result indicates that the time cost of Quick D2 is much lower than that of D2, while the descriptors extracted by the two algorithms are almost the same. Second, an expandable 3D model repository index method with high performance, namely, RBK index, is presented. On the basis of RBK index, the search space is pruned effectively during the search process, leading to a speed up of the whole system. The factors that influence the values of the key parameters of RBK index are discussed and an experimental method to find the optimal values of the key parameters is given. Finally, "3D Searcher", a content-based 3D model retrieval system is developed. By using the methods proposed, the time cost for the system to respond one query online is reduced by 75% on average. The system has been implemented in a manufacturing enterprise, and practical query examples during a case of the automobile rear axle design are also shown. The research method presented shows a new research perspective and can effectively improve the content-based 3D model retrieval efficiency.    

10.  An Optimal Lifetime Utility Routing for 5G and Energy-Harvesting Wireless Networks  
   Gina Martinez  Shufang Li  Chi Zhou《中兴通讯技术(英文版)》,2015年第1期
   Harvesting energy from environmental sources such as solar and wind can mitigate or solve the limited-energy problem in wireless sensor networks. In this paper, we propose an energy-harvest-aware route-selection method that incorporates harvest availability properties and energy storage capacity limits into the routing decisions. The harvest-aware routing problem is formulated as a linear program with a utility-based objective function that balances the two conflicting routing objectives of maximum total and maximum minimum residual network energy. The simulation results show that doing so achieves a longer network lifetime, defined as the time-to-first-node-death in the network. Additionally, most existing energy-harvesting routing algorithms route each traffic flow independently from each other. The LP formulation allows for a joint optimization of multiple traffic flows. Better residual energy statistics are also achieved by such joint consideration compared to independent optimization of each commodity.    

11.  Top-K Query Framework in Wireless Sensor Networks for Smart Grid  
   WANG Hui  GUAN Zhitao  YANG Tingting  XU Yue《中国通信》,2014年第6期
   The smart grid has caught great attentions in recent years, which is poised to transform a centralized, producer-controlled network to a decentralized, consumer- interactive network that's supported by fine-grained monitoring. Large-scale WSNs (Wireless Sensor Networks) have been considered one of the very promising technologies to support the implementation of smart grid. WSNs are applied in almost every aspect of smart grid, including power generation, power transmission, power distribution, power utilization and power dispatch, and the data query processing of 'WSNs in power grid' become an hotspot issue due to the amount of data of power grid is very large and the requirement of response time is very high. To meet the demands, top-k query processing is a good choice, which performs the cooperative query by aggregating the database objects' degree of match for each different query predicate and returning the best k matching objects. In this paper, a framework that can effectively apply top-k query to wireless sensor network in smart grid is proposed, which is based on the cluster-topology sensor network. In the new method, local indices are used to optimize the necessary query routing and process intermediate results inside the cluster to cut down the data traffic, and the hierarchical join query is executed based on the local results.Besides, top-k query results are verified by the clean-up process, and two schemes are taken to deal with the problem of node's dynamicity, which further reduce communication cost. Case studies and experimental results show that our algorithm has outperformed the current existing one with higher quality results and better efficiently.    

12.  Evolutionary Generation Approach of Test Data for Multiple Paths Coverage of Message-passing Parallel Programs  
   TIAN Tian  GONG Dunwei《电子学报:英文版》,2014年第2期
   Test data generation, the premise of soft- ware testing, has attracted scholars in the software engi- neering community in recent years. Influenced by task par- titioning, process scheduling, and network delays, parallel programs are executed in a non-deterministic way, which makes test data generation of parallel programs different from that of serial programs in essence. This paper inves- tigated the problem of generating test data for multiple paths coverage of message-passing parallel programs. A mathematical model of the above problem was built based on each given path and its equivalent ones. It was solved by using a genetic algorithm to generate all desired data in one run. The proposed method was applied to five bench- mark programs, and compared with the existing methods. The experimental results show that the proposed method greatly shortens the number of iterations and time con- sumption without reducing the coverage rate.    

13.  Peak Power Minimizing Algorithm by Voltage Scheduling  
   SU Yajuan  ;WEI Shaojun  ;YE Tianchun  ;CHEN Lan  ;LUO Jiajun《电子学报:英文版》,2008年第1期
   For complicated electronic systems, to ensure high performance and reliability satisfaction, minimizing peak power consumption becomes one of the most important design goals. This paper addresses the problem of variable voltage scheduling on multlprocessor distributed systems, with the goal of shaping the power profile to minimizing peak power. A low peak power algorithm named LPPA is proposed to optimize power distribution via scaling voltage of the tasks on critical regions, based on the comprehensive analysis of how power consumption varies with latency. Compared with previous low peak power techniques, which simply scale voltage of tasks according to their timing critical degree, LPPA additionally take the power profile into count to further decrease the peak power. Experimental results show that the proposed voltage scheduling technique significantly improves the power characteristics over the existing power profile unaware scheduling technique. Meanwhile, energy consumption reduction is also obtained.    

14.  Timing slack optimization approach using FPGA hybrid routing strategy of rip-up-retry and pathfinder  
   Wei Yu  Haigang Yang  Yang Liu  Juan Huang《电子科学学刊(英文版)》,2014年第31卷第3期
   To improve the path slack of Field Programmable Gate Array (FPGA), this paper proposes a timing slack optimization approach which utilizes the hybrid routing strategy of rip-up-retry and pathfinder. Firstly, effect of process variations on path slack is analyzed, and by constructing a col- location table of delay model that takes into account the multi-corner process, the complex statistical static timing analysis is successfully translated into a simple classical static timing analysis. Then, based on the hybrid routing strategy of rip-up-retry and pathfinder, by adjusting the critical path which detours a long distance, the critical path delay is reduced and the path slack is optimized. Experimental results show that, using the hybrid routing strategy, the number of paths with negative slack can be optimized (reduced) by 85.8% on average compared with the Versatile Place and Route (VPR) tim- ing-driven routing algorithm, while the run-time is only increased by 15.02% on average.    

15.  Mesh网络容错广播路由算法的概率分析  
   王高才 陈建二 王国军 陈松乔《计算机科学》,2003年第30卷第10期
   One-to-all or broadcast communication is one of the most important communication patterns and occurs in many important applications in parallel computing. This paper proposes a fault tolerant, local-irdormation-based, and distributed broadcast routing algorithm based on the concept of k-submesh-cormectivity in all-port mesh networks.The paper analyzes the fault tolerance of the algorithm in terms of node failure probability. Suppose that every nodehas independent failure probability, and deduce the success probability of the broadcast routing, which successfully routes a message from a source node to all non-faulty nodes in the networks. The paper strictly proves that the broadcast routing algorithm with the success probability of 99% to route among all non-faulty nodes on mesh networks with forty thousand nodes, in case that the node failure probability is controlled within 0.12% Simulation results show that the algorithm is practically efficient and effective, and the time steps of the algorithm are very closeto the optimum.    

16.  A Monte Carlo Enhanced PSO Algorithm for Optimal QoM in Multi-Channel Wireless Networks  
   杜华争  夏娜  蒋建国  徐丽娜  郑榕《计算机科学技术学报》,2013年第28卷第3期
   In wireless monitoring networks, wireless sniffers are distributed in a region to monitor the activities of users. It can be used for fault diagnosis, resource management and critical path analysis. Due to hardware limitations, wireless sniffers typically can only collect information on one channel at a time. Therefore, it is a key topic to optimize the channel selection for sniffers to maximize the information collected, so as to maximize the quality of monitoring (QoM) of the network. In this paper, a particle swarm optimization (PSO)-based solution is proposed to achieve the optimal channel selection. A2D mapping particle coding and its moving scheme are devised. Monte Carlo method is incorporated to revise the solution and significantly improve the convergence of the algorithm. The extensive simulations demonstrate that the Monte Carlo enhanced PSO (MC-PSO) algorithm outperforms the related algorithms evidently with higher monitoring quality, lower computation complexity, and faster convergence. The practical experiment also shows the feasibility of this algorithm.    

17.  Speed up Training of the Recurrent Neural Network Based on Constrained optimization Techniques  
   Chen Ke  Bao Weiquan  Chi Huisheng《计算机科学技术学报》,1996年第11卷第6期
   In this paper,the constrained optimization technique for a substantial problem is explored,that is accelerating training the globally recurrent neural network.Unlike most of the previous methods in feedforware neural networks,the authors adopt the constrained optimization technique to improve the gradientbased algorithm of the globally recurrent neural network for the adaptive learning rate during tracining.Using the recurrent network with the improved algorithm,some experiments in two real-world problems,namely,filtering additive noises in acoustic data and classification of temporat signals for speaker identification,have been performed.The experimental results show that the recurrent neural network with the improved learning algorithm yields significantly faster training and achieves the satisfactory performance.    

18.  Emergency Local Searching Approach for Job Shop Scheduling  
   ZHAO Ning  CHEN Siyu  DU Yanhua《机械工程学报(英文版)》,2013年第26卷第5期
   Existing methods of local search mostly focus on how to reach optimal solution.However,in some emergency situations,search time is the hard constraint for job shop scheduling problem while optimal solution is not necessary.In this situation,the existing method of local search is not fast enough.This paper presents an emergency local search(ELS) approach which can reach feasible and nearly optimal solution in limited search time.The ELS approach is desirable for the aforementioned emergency situations where search time is limited and a nearly optimal solution is sufficient,which consists of three phases.Firstly,in order to reach a feasible and nearly optimal solution,infeasible solutions are repaired and a repair technique named group repair is proposed.Secondly,in order to save time,the amount of local search moves need to be reduced and this is achieved by a quickly search method named critical path search(CPS).Finally,CPS sometimes stops at a solution far from the optimal one.In order to jump out the search dilemma of CPS,a jump technique based on critical part is used to improve CPS.Furthermore,the schedule system based on ELS has been developed and experiments based on this system completed on the computer of Intel Pentium(R) 2.93 GHz.The experimental result shows that the optimal solutions of small scale instances are reached in 2 s,and the nearly optimal solutions of large scale instances are reached in 4 s.The proposed ELS approach can stably reach nearly optimal solutions with manageable search time,and can be applied on some emergency situations.    

19.  Energy-aware routing for delay-sensitive underwater wireless sensor networks  
   ZHANG SenLin  WANG ZiXiang  LIU MeiQin  QIU MeiKang《中国科学:信息科学(英文版)》,2014年第10期
   The energy reduction is a challenging problem in the applications of underwater wireless sensor networks (UWSNs). The embedded battery is difficult to be replaced and it has an upper bound on its lifetime. Multihop relay is a popular method to reduce energy consumption in data transmission. The energy minimum path from source to destination in the sensor networks can be obtained through the shortest path algorithm. However, because of the node mobility, the global path planning approach is not suitable for the routing in UWSNs. It calls for an energy-efficient routing protocol for the high dynamic UWSNs. In this paper, we propose the modified energy weight routing (MEWR) protocol to deal with the energy-efficient routing of delay- sensitive UWSNs. MEWR is a low flooding routing protocol. It can tolerate the node mobility in UWSNs and achieve a low end-to-end packet delay. MEWR can provide lower energy consumption than the existing low delay routing protocols through the dynamic sending power adjustment. The simulation results demonstrate the effectiveness of MEWR.    

20.  Stability analysis for recurrent neural networks with time-varying delay  
   Yuan-Yuan Wu  Yu-Qiang Wu《国际自动化与计算杂志》,2009年第6卷第3期
   This paper is concerned with the stability analysis for static recurrent neural networks (RNNs) with time-varying delay. By Lyapunov functional method and linear matrix inequality technique, some new delay-dependent conditions are established to ensure the asymptotic stability of the neural network. Expressed in linear matrix inequalities (LMIs), the proposed delay-dependent stability conditions can be checked using the recently developed algorithms. A numerical example is given to show that the obtained conditions can provide less conservative results than some existing ones.    

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