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2nd International Conference on Modelling and Simulation

作者： Wang Xiaohong Zhuang Yi Nanjing Univ Aeronaut & Astronaut Coll Sci Nanjing 210016 Peoples R China

ISBN: (纸本)9781846260650

The substructure direct transformation method is a reduced mode synthesis method. This paper proposed several methods which all based on the direct translation method. The new methods work well especially for the case that the scale of the structural eigenvalue problems, after the substructure mode synthesis reduction or condensation of the whole structure to the interface of the structure, is still too big. The proposed distributed parallel algorithms work on the level of substructure. They require neither assembling the stiff and mass matrices of the whole structure, nor solving the system of interface equations. These methods reduce the large-scale structure eigenvalue problems to many smaller scale problems with excellent calculation precision and stability.

关键词： eigenvalue problem substructure method finite element distributed parallel algorithm Subspace iteration algorithm mode synthesis

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Redundant data high-efficiency compression based on distributed parallel algorithm

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SOFT COMPUTING 2021年第20期25卷 13039-13051页

作者： Gong, Jianhu Guangdong Peizheng Coll Sch Data & Comp Sci Guangzhou 510830 Peoples R China

Redundancy occurs when multiple consumers of the network attempt to access the similar content online. Many state-of-the-art studies have been proposed to remove redundancy from the network and to enhance the network efficiency of Internet applications. Still there is a necessity to explore more data redundancy elimination (DRE) techniques, especially for defense-based networks to enhance the data transmission speed and to compress the irrelevant data optimally for reducing the network latency. In order to improve the optimal storage capacity of redundant data over serial hybrid network cascade database, a high-efficiency redundancy elimination method based on the distributed parallel algorithm is proposed in this paper. The distributed storage structure model for handling redundant data of serial mixed network cascade database is designed and tested in simulated environment. The extraction of features of redundant data is performed by using distributed hybrid feature mining technique. The dimensionality reduction of redundant data is also attained by devising the feature transformation method to remove the unwanted features of data. The two benchmarked techniques have been selected for comparative study and to evaluate the performance of the proposed method. The simulation results show that the proposed DRE method can significantly reduce the redundancy from the network traffic. The bandwidth utilization is improved, the duplicate data are also compressed optimally and it is proved that the proposed DRE method is viable for large networks to eliminate the redundant data.

关键词： distributed parallel algorithm Protocol-independent redundancy elimination (PIDE) Data redundancy elimination (DRE) High performance Compression

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A Refined distributed parallel algorithm For The Eigenvalue Problem Of Large-scale Matrix

A Refined Distributed Parallel Algorithm For The Eigenvalue ...

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2010 3rd International Conference on Biomedical Engineering and Informatics (BMEI 2010)

作者： Zhao, Lu Zhuang, Yi Liu, Yi Ni, Tian Quan Nanjing Univ Aeronaut & Astronaut Coll Informat Sci & Technol Nanjing 210016 Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Aerosp Engn Nanjing 210016 Peoples R China Tongji Univ Coll Aerosp Engn & Appl Mech Shanghai 200092 Peoples R China China Shipbldg Ind Corp Inst 723 Yangzhou 225001 Jiangsu Peoples R China

ISBN: (纸本)9781424464968

In view of eigenvalue problems of large-scale matrix, this paper proposes a refined distributed parallel algorithm named RDPC-DTM based on direct transformation method and DPC-DTM algorithm which is a distributed parallel design of direct transformation method. This new method solves the problem that increasing the number of substructure could not effectively enhance the computing efficiency when the scale of matrix is too large. Numerical experiment proves that RDPC-DTM is more efficient than DPC-DTM, especially when calculating eigenvalue of super large-scale matrix. Numerical experiment also demonstrates that RDPC-DTM has higher degree of parallelism and is more suitable for cluster or MPP parallel computer compared to DPC-DTM.

关键词： eigenvalue problem substructure method finite element distributed parallel algorithm Subspace iteration algorithm mode synthesis

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VaR and CVaR Estimate based on distributed parallel algorithm

VaR and CVaR Estimate based on Distributed Parallel Algorith...

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11th International Symposium on distributed Computing and Applications to Business, Engineering and Science (DCABES)

作者： Fu Shu-huan Cao Jia-he Hohai Univ Sch Business Nanjing Jiangsu Peoples R China

ISBN: (纸本)9780769548180

CVaR has more advantages, than the VaR as portfolio risk measurement tool, but with the calculation of VaR, the Monte Carlo simulation method of the CVaR is difficult, and the cost is high. The establishment of the system of distributed parallel algorithm can reduce costs and speed up the calculation, which is conducive to the promotion of the CVaR Monte Carlo algorithm.

关键词： VaR the CVaR distributed parallel algorithm

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VaR and CVaR Estimate based on distributed parallel algorithm

VaR and CVaR Estimate based on Distributed Parallel Algorith...

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第11届分布式计算及其应用国际学术研讨会

作者： FU Shu-huan CAO Jia-he Business School of Hohai University

关键词： VaR the CVaR distributed parallel algorithm

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New Heuristic distributed parallel algorithms for Searching and Planning

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Journal of Computer Science & Technology 1995年第4期10卷 354-374页

作者：帅典勋 Univ of Xi'an Electronics Science and Technology Xi'an China

This paper proposes new heuristic distributed parallel algorithms for search-ing and planning, which are based on the concepts of wave concurrent prop-agations and competitive activation mechanisms. These algorithms are char-acterized by simplicity and clearness of control strategies for searching, anddistinguished abilities in many aspects, such as high speed processing, widesuitability for searching AND/OR implicit graphs, and ease in hardware imple-mentation.

关键词： Heuristic search distributed parallel algorithm implicit AND/OR graph wave concurrent propagation

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distributed parallel algorithms for online virtual network embedding applications

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INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2023年第1期36卷 e4325-e4325页

作者： Lu, Qiao Nguyen, Khoa Huang, Changcheng Carleton Univ Dept Syst & Comp Engn Ottawa ON K1S 5B6 Canada

Network virtualization (NV) has ubiquitously emerged as an indispensable attribute to enable the success of the forthcoming virtualized networks (eg, 5G network and smart Internet of Things [IoT]). Virtual network embedding (VNE) is the major challenge in NV that allows multiple heterogeneous virtual networks (VNs) to simultaneously coexist on a shared substrate infrastructure. A great number of VNE algorithms have been proposed, but over the past decades, most of them are only targeting for VNE node mapping. In this paper, we propose two distributed parallel genetic algorithms, which are based on two versions of crossover and mutation schemes, for online VN link embedding problems with low latency and high efficiency. Furthermore, we conduct a time analysis on the executing time of independently distributed parallel computing machines in details. This comprehensive analysis validates the parallel computing scalability on an identical number of predefined parallel machines. Extensive simulations have shown that our proposed algorithms can achieve better performance than integer linear programming (ILP)-based solutions while meeting the stringent time requirements for online VN embedding applications. Our proposed algorithms yield superior performance in running time with 32.78% up to 1727.8% faster than existing popular VNE algorithms. Additionally, the theoretical analysis indicates that the execution time can be reduced to logarithmic times by applying proposed distributed parallel algorithms.

关键词： 5G network distributed parallel algorithm metaheuristic network virtualization parallel genetic algorithm

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A new generalized particle approach to parallel bandwidth allocation

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COMPUTER COMMUNICATIONS 2006年第18期29卷 3933-3945页

作者： Feng, Xiang Lau, Francis C. M. Shuai, Dianxun Univ Hong Kong Dept Comp Sci Hong Kong Hong Kong Peoples R China E China Univ Sci & Technol Dept Comp Sci & Engn Shanghai 200237 Peoples R China

This paper presents a new generalized particle (GP) approach to dynamical optimization of network bandwidth allocation, which can also be used to optimize other resource assignments in networks. By using the GP model, the complicated network bandwidth allocation problem is transformed into the kinematics and dynamics of numerous particles in two reciprocal dual force-fields. The proposed model and algorithm are featured by the powerful processing ability under a complex environment that involves the various interactions among network entities, the market mechanism between the demands and service, and other phenomena common in networks, such as congestion, metabolism, and breakdown of network entities. The GP approach also has the advantages in terms of the higher parallelism, lower computation complexities, and the easiness for hardware implementation. The properties of the approach, including the correctness, convergency and stability, are discussed in details. Simulation results attest to the effectiveness and suitability of the proposed approach. (C) 2006 Elsevier B.V. All rights reserved.

关键词： bandwidth allocation generalized particle (GP) distributed parallel algorithm computer networks dynamical process

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A high performance implementation of Zolo-SVD algorithm on distributed memory systems

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parallel COMPUTING 2019年第0期86卷 57-65页

作者： Li, Shengguo Liu, Jie Du, Yunfei Natl Univ Def Technol Coll Comp Sci Changsha 410073 Hunan Peoples R China Sun Yat Sen Univ Dept Comp Sci Guangzhou 510006 Guangdong Peoples R China

This paper introduces a high performance implementation of the Zolo-SVD algorithm on distributed memory systems, which is based on the polar decomposition (PD) algorithm via the Zolotarev's function (Zolo-PD), originally proposed by Nakatsukasa and Freund [SIAM Review, 20161. Our implementation highly relies on the routines of ScaLAPACK and therefore it is portable. Compared with the other PD algorithms such as the QR-based dynamically weighted Halley method (QDWH-PD), Zolo-PD is naturally parallelizable and has better scalability though performs more floating-point operations. When using many processors, Zolo-PD is usually 1.20 times faster than the QDWH-PD algorithm, and Zolo-SVD can be about two times faster than the ScaLAPACK routine PDGESVD. These numerical experiments are performed on Tianhe-2A supercomputer, one of the fastest supercomputers in the world, and the tested matrices include some sparse matrices from particular applications and some randomly generated dense matrices with different dimensions. Our QDWH-SVD and Zolo-SVD implementations are freely available at https://***/shengguolsg/Zolo-SVD. (C) 2019 Elsevier B.V. All rights reserved.

关键词： ScaLAPACK Polar decomposition Zolotarev QDWH distributed parallel algorithm

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The parallel optimization of network bandwidth allocation based on generalized particle model

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COMPUTER NETWORKS 2006年第9期50卷 1219-1246页

作者： Shuai, Dianxun Feng, Xiang E China Univ Sci & Technol Dept Comp Sci & Engn Shanghai 200237 Peoples R China Tsinghua Univ State Key Lab Intelligence Technol & Syst Beijing 100080 Peoples R China

This paper presents a new duality approach to optimize the resource assignment and bandwidth allocation in networks. which is based oil the generalized particle model (GPM). By the GPM, the network's optimization problem is transformed into the kinematics and dynamics of numerous particles in two reciprocal dual force-fields. Like the Kelly's duality model and Low's duality model related to Lagrangian multipliers methods (LMM), the GPM-based duality model also contains two distributed algorithms for resource supplies and resource demands, respectively. and can be carried out in parallel. Both the LMM-based and GPM-based duality models may not only embody the market mechanism between the supplies and demands very well, but also may describe the influence of congestion degree of networks on the resource allocation. But the GPM-based duality model is different from other duality models in terms of the basic principle, mathematical formalization, and properties. Features of the GPM-based duality model and the corresponding duality algorithm include a powerful processing ability in a complex environment that involves the priority, personality, autonomy, and interaction of different entities in networks. Furthermore, the GPM-based duality model can realize the optimization of multiple objectives, including the aggregate utility, the personal utility, the minimal personal utility, the resource utilization, and the users' satisfactory degree. The proposed approach also has the advantages in terms of the higher parallelism, lower computation complexity, and the ease for hardware implementation. The properties of the GPM-based duality model, including the correctness, convergency and stability, are discussed in detail. The numerous simulations oil the network bandwidth allocation have shown the effectiveness and suitability of the proposed approach. (c) 2005 Elsevier B.V. All rights reserved.

关键词： bandwidth allocation duality model multi-objective optimization generalized particle model distributed parallel algorithm computer networks

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