Satellite observation schedule is investigated in this paper.A mission planning algorithm of task clustering is proposed to improve the observation efficiency of agile satellite.The newly developed method can make the...Satellite observation schedule is investigated in this paper.A mission planning algorithm of task clustering is proposed to improve the observation efficiency of agile satellite.The newly developed method can make the satellite observe more targets and therefore save observation resources.First,for the densely distributed target points,a preprocessing scheme based on task clustering is proposed.The target points are clustered according to the distance condition.Second,the local observation path is generated by Tabu algorithm in the inner layer of cluster regions.Third,considering the scatter and cluster sets,the global observation path is obtained by adopting Tabu algorithm in the outer layer.Simulation results show that the algorithm can effectively reduce the task planning time of large-scale point targets while ensuring the optimal solution quality.展开更多
Considering the flexible attitude maneuver and the narrow field of view of agile Earth observation satellite(AEOS)together,a comprehensive task clustering(CTC)is proposed to improve the observation scheduling problem ...Considering the flexible attitude maneuver and the narrow field of view of agile Earth observation satellite(AEOS)together,a comprehensive task clustering(CTC)is proposed to improve the observation scheduling problem for AEOS(OSPFAS).Since the observation scheduling problem for AEOS with comprehensive task clustering(OSWCTC)is a dynamic combination optimization problem,two optimization objectives,the loss rate(LR)of the image quality and the energy consumption(EC),are proposed to format OSWCTC as a bi-objective optimization model.Harnessing the power of an adaptive large neighborhood search(ALNS)algorithm with a nondominated sorting genetic algorithm II(NSGA-II),a bi-objective optimization algorithm,ALNS+NSGA-II,is developed to solve OSWCTC.Based on the existing instances,the efficiency of ALNS+NSGA-II is analyzed from several aspects,meanwhile,results of extensive computational experiments are presented which disclose that OSPFAS considering CTC produces superior outcomes.展开更多
Cloud computing has developed as an important information technology paradigm which can provide on-demand services. Meanwhile,its energy consumption problem has attracted a grow-ing attention both from academic and in...Cloud computing has developed as an important information technology paradigm which can provide on-demand services. Meanwhile,its energy consumption problem has attracted a grow-ing attention both from academic and industrial communities. In this paper,from the perspective of cloud tasks,the relationship between cloud tasks and cloud platform energy consumption is established and analyzed on the basis of the multidimensional attributes of cloud tasks. Furthermore,a three-way clustering algorithm of cloud tasks is proposed for saving energy. In the algorithm,f irst,t he cloud tasks are classified into three categories according to the content properties of the cloud tasks and resources respectively. Next,cloud tasks and cloud resources are clustered according to their computation characteristics（ e. g. computation-intensive,data-intensive）. Subsequently,greedy scheduling is performed. The simulation results showthat the proposed algorithm can significantly reduce the energy cost and improve resources utilization,compared with the general greedy scheduling algorithm.展开更多
A new heuristic approach that resembles the evolution of interpersonal relationships in human society is put forward for the problem of scheduling multitasks represented by a directed acyclic graph. The algorithm incl...A new heuristic approach that resembles the evolution of interpersonal relationships in human society is put forward for the problem of scheduling multitasks represented by a directed acyclic graph. The algorithm includes dynamic-group, detachgraph and front-sink components. The priority rules used are new. Relationship number, potentiality, weight and merge degree are defined for cluster＇s priority, and task potentiality for tasks＇ priority. Experiments show the algorithm could get good result in short time. The algorithm produces another optimal solution for the classic MJD benchmark. Its average performance is better than five latter-day representative algorithms, especially six benchmarks of the nines.展开更多
为解决低轨遥感星座协同任务规划面临的计算复杂度高、通信开销大、动态响应能力弱等问题,提出一种基于任务聚类与禁忌搜索的改进合同网算法(improved contract net protocol based on task clustering and tabu search,CN-TCTS).该算...为解决低轨遥感星座协同任务规划面临的计算复杂度高、通信开销大、动态响应能力弱等问题,提出一种基于任务聚类与禁忌搜索的改进合同网算法(improved contract net protocol based on task clustering and tabu search,CN-TCTS).该算法采用“单星调度-全局分配”的分层求解框架.首先,通过任务聚类合并元任务,有效缩减解空间;其次,设计了动态约束禁忌搜索算法(dynamic constraint tabu search,DCTS),通过价值导向的邻域搜索策略实现单星任务序列的快速规划;最后,在全局分配阶段,引入多种策略对传统合同网协议进行改进,实现任务的高效分配与冲突消解.仿真结果表明,本文所提CN-TCTS算法在400个任务的大规模场景下,任务完成率仍保持82.0%,且平均通信轮次仅为6.6轮.此外,在卫星突发失效的动态场景下,该算法表现出更强的鲁棒性,收益损失率更低.此外,局部规划算法仿真中验证了DCTS算法在收敛速度与解质量方面的优势.展开更多
The formation of the manned aerial vehicle/unmanned aerial vehicle(MAV/UAV) task coalition is considered. To reduce the scale of the problem, the formation progress is divided into three phases. For the task clusterin...The formation of the manned aerial vehicle/unmanned aerial vehicle(MAV/UAV) task coalition is considered. To reduce the scale of the problem, the formation progress is divided into three phases. For the task clustering phase, the geographical position of tasks is taken into consideration and a cluster method is proposed. For the UAV allocation phase, the UAV requirement for both constrained and unconstrained resources is introduced, and a multi-objective optimal algorithm is proposed to solve the allocation problem. For the MAV allocation phase, the optimal model is firstly constructed and it is decomposed according to the ideal of greed to reduce the time complexity of the algorithm. Based on the above phases, the MAV/UAV task coalition formation method is proposed and the effectiveness and practicability are demonstrated by simulation examples.展开更多
We propose a content-based parallel image retrieval system to achieve high responding ability. Our system is developed on cluster architectures. It has several retrieval. servers to supply the service of content-based...We propose a content-based parallel image retrieval system to achieve high responding ability. Our system is developed on cluster architectures. It has several retrieval. servers to supply the service of content-based image retrieval. It adopts the Browser/Server (B/S) mode. The users could visit our system though web pages. It uses the symmetrical color-spatial features (SCSF) to represent the content of an image. The SCSF is effective and efficient for image matching because it is independent of image distortion such as rotation and flip as well as it increases the matching accuracy. The SCSF was organized by M-tree, which could speedup the searching procedure. Our experiments show that the image matching is quickly and efficiently with the use of SCSF. And with the support of several retrieval servers, the system could respond to many users at mean time. Key words content-based image retrieval - cluster architecture - color-spatial feature - B/S mode - task parallel - WWW - Internet CLC number TP391 Foundation item: Supported by the National Natural Science Foundation of China (60173058)Biography: ZHOU Bing (1975-), male, Ph. D candidate, reseach direction: data mining, content-based image retrieval.展开更多
The real problem in cluster of workstations is the changes in workstation power or number of workstations or dynmaic changes in the run time behavior of the application hamper the efficient use of resources. Dynamic l...The real problem in cluster of workstations is the changes in workstation power or number of workstations or dynmaic changes in the run time behavior of the application hamper the efficient use of resources. Dynamic load balancing is a technique for the parallel implementation of problems, which generate unpredictable workloads by migration work units from heavily loaded processor to lightly loaded processors at run time. This paper proposed an efficient load balancing method in which parallel tree computations depth first search (DFS) generates unpredictable, highly imbalance workloads and moves through different phases detectable at run time, where dynamic load balancing strategy is applicable in each phase running under the MPI(message passing interface) and Unix operating system on cluster of workstations parallel platform computing.展开更多
基金the National Key Research and Development Program of China(Grant No.2016YFB0500801)sponsored by Qing Lan Project.
文摘Satellite observation schedule is investigated in this paper.A mission planning algorithm of task clustering is proposed to improve the observation efficiency of agile satellite.The newly developed method can make the satellite observe more targets and therefore save observation resources.First,for the densely distributed target points,a preprocessing scheme based on task clustering is proposed.The target points are clustered according to the distance condition.Second,the local observation path is generated by Tabu algorithm in the inner layer of cluster regions.Third,considering the scatter and cluster sets,the global observation path is obtained by adopting Tabu algorithm in the outer layer.Simulation results show that the algorithm can effectively reduce the task planning time of large-scale point targets while ensuring the optimal solution quality.
文摘Considering the flexible attitude maneuver and the narrow field of view of agile Earth observation satellite(AEOS)together,a comprehensive task clustering(CTC)is proposed to improve the observation scheduling problem for AEOS(OSPFAS).Since the observation scheduling problem for AEOS with comprehensive task clustering(OSWCTC)is a dynamic combination optimization problem,two optimization objectives,the loss rate(LR)of the image quality and the energy consumption(EC),are proposed to format OSWCTC as a bi-objective optimization model.Harnessing the power of an adaptive large neighborhood search(ALNS)algorithm with a nondominated sorting genetic algorithm II(NSGA-II),a bi-objective optimization algorithm,ALNS+NSGA-II,is developed to solve OSWCTC.Based on the existing instances,the efficiency of ALNS+NSGA-II is analyzed from several aspects,meanwhile,results of extensive computational experiments are presented which disclose that OSPFAS considering CTC produces superior outcomes.
基金Supported by the Harbin Technology Bureau Youth Talented Project(2014RFQXJ073)China Postdoctoral Fund Projects(2014M561330)
文摘Cloud computing has developed as an important information technology paradigm which can provide on-demand services. Meanwhile,its energy consumption problem has attracted a grow-ing attention both from academic and industrial communities. In this paper,from the perspective of cloud tasks,the relationship between cloud tasks and cloud platform energy consumption is established and analyzed on the basis of the multidimensional attributes of cloud tasks. Furthermore,a three-way clustering algorithm of cloud tasks is proposed for saving energy. In the algorithm,f irst,t he cloud tasks are classified into three categories according to the content properties of the cloud tasks and resources respectively. Next,cloud tasks and cloud resources are clustered according to their computation characteristics（ e. g. computation-intensive,data-intensive）. Subsequently,greedy scheduling is performed. The simulation results showthat the proposed algorithm can significantly reduce the energy cost and improve resources utilization,compared with the general greedy scheduling algorithm.
基金Supported by the National Natural Science Foundation of China (7047107)the Ph.D. Programs Foundation of Ministry of Education of China (20020487046)
文摘A new heuristic approach that resembles the evolution of interpersonal relationships in human society is put forward for the problem of scheduling multitasks represented by a directed acyclic graph. The algorithm includes dynamic-group, detachgraph and front-sink components. The priority rules used are new. Relationship number, potentiality, weight and merge degree are defined for cluster＇s priority, and task potentiality for tasks＇ priority. Experiments show the algorithm could get good result in short time. The algorithm produces another optimal solution for the classic MJD benchmark. Its average performance is better than five latter-day representative algorithms, especially six benchmarks of the nines.
文摘为解决低轨遥感星座协同任务规划面临的计算复杂度高、通信开销大、动态响应能力弱等问题,提出一种基于任务聚类与禁忌搜索的改进合同网算法(improved contract net protocol based on task clustering and tabu search,CN-TCTS).该算法采用“单星调度-全局分配”的分层求解框架.首先,通过任务聚类合并元任务,有效缩减解空间;其次,设计了动态约束禁忌搜索算法(dynamic constraint tabu search,DCTS),通过价值导向的邻域搜索策略实现单星任务序列的快速规划;最后,在全局分配阶段,引入多种策略对传统合同网协议进行改进,实现任务的高效分配与冲突消解.仿真结果表明,本文所提CN-TCTS算法在400个任务的大规模场景下,任务完成率仍保持82.0%,且平均通信轮次仅为6.6轮.此外,在卫星突发失效的动态场景下,该算法表现出更强的鲁棒性,收益损失率更低.此外,局部规划算法仿真中验证了DCTS算法在收敛速度与解质量方面的优势.
基金supported by the National Natural Science Foundation of China(61573017 61703425)the Aeronautical Science Fund(20175796014)
文摘The formation of the manned aerial vehicle/unmanned aerial vehicle(MAV/UAV) task coalition is considered. To reduce the scale of the problem, the formation progress is divided into three phases. For the task clustering phase, the geographical position of tasks is taken into consideration and a cluster method is proposed. For the UAV allocation phase, the UAV requirement for both constrained and unconstrained resources is introduced, and a multi-objective optimal algorithm is proposed to solve the allocation problem. For the MAV allocation phase, the optimal model is firstly constructed and it is decomposed according to the ideal of greed to reduce the time complexity of the algorithm. Based on the above phases, the MAV/UAV task coalition formation method is proposed and the effectiveness and practicability are demonstrated by simulation examples.
文摘We propose a content-based parallel image retrieval system to achieve high responding ability. Our system is developed on cluster architectures. It has several retrieval. servers to supply the service of content-based image retrieval. It adopts the Browser/Server (B/S) mode. The users could visit our system though web pages. It uses the symmetrical color-spatial features (SCSF) to represent the content of an image. The SCSF is effective and efficient for image matching because it is independent of image distortion such as rotation and flip as well as it increases the matching accuracy. The SCSF was organized by M-tree, which could speedup the searching procedure. Our experiments show that the image matching is quickly and efficiently with the use of SCSF. And with the support of several retrieval servers, the system could respond to many users at mean time. Key words content-based image retrieval - cluster architecture - color-spatial feature - B/S mode - task parallel - WWW - Internet CLC number TP391 Foundation item: Supported by the National Natural Science Foundation of China (60173058)Biography: ZHOU Bing (1975-), male, Ph. D candidate, reseach direction: data mining, content-based image retrieval.
基金Natural Science Foundation of China (No.60 173 0 3 1)
文摘The real problem in cluster of workstations is the changes in workstation power or number of workstations or dynmaic changes in the run time behavior of the application hamper the efficient use of resources. Dynamic load balancing is a technique for the parallel implementation of problems, which generate unpredictable workloads by migration work units from heavily loaded processor to lightly loaded processors at run time. This paper proposed an efficient load balancing method in which parallel tree computations depth first search (DFS) generates unpredictable, highly imbalance workloads and moves through different phases detectable at run time, where dynamic load balancing strategy is applicable in each phase running under the MPI(message passing interface) and Unix operating system on cluster of workstations parallel platform computing.
