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检索条件"任意字段=17th International Conference on Parallel and Distributed Computing Systems, PDCS 2004"

共 281 条记录，以下是61-70 订阅

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Detecting Chaff Perturbation on Stepping-Stone Connection

Detecting Chaff Perturbation on Stepping-Stone Connection

引用

17th IEEE international conference on parallel and distributed systems (ICPADS)

作者： Huang, Shou-Hsuan Stephen Kuo, Ying-Wei Univ Houston Dept Comp Sci Houston TX 77204 USA

ISBN: (纸本)9780769545769

Cybercriminals often use a sequence of intermediate "stepping-stone" hosts to attack a target machine in order to maintain anonymity. this type of attack of using a connection chain is called stepping-stone attack. Most existing algorithms to detect such attack is to use timing-based correlation on the connections. However, these timing-based approaches are vulnerable if the intruders add chaff packets to evade the detection. the stepping-stone detection rate decreases as the chaff rate increases. We developed a novel anomaly detection algorithm to detect the presence of chaff in a connection by monitoring the packet inter-arrival times. Our study shows the probability distribution of the inter-arrival time of a chaffed connection differs from that of one without chaff. Our experiments show the detection rate as a function of the chaff rate under a variety of complex circumstances. the new algorithm complements the existing correlation-based stepping-stone detection algorithms in providing a more robust solution to stepping-stone detection.

关键词： Stepping-stone intrusion detection network security chaff evasion technique packet inter-arrival time model distributed computing

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Vertex-centric parallel Algorithms for Identifying Key Vertices in Large-scale Graphs 17

Vertex-centric Parallel Algorithms for Identifying Key Verti...

引用

2015 IEEE 17th international conference on High Performance computing and Communications (HPCC)

作者： Li, Bo Gao, Zhuangliang Niu, Jianwei Lv, YanFei Zhang, Hong Beihang Univ Sch Comp Sci & Engn Beijing Peoples R China CNCERT CC Beijing Peoples R China

ISBN: (纸本)9781479989379

Betweenness centrality is a metric to measure the relative importance of vertices within a graph. the computation of betweenness centrality is based on shortest paths which requires O(n+m) space and O(mn) and O(nm+n(2) log n) time on unweighted and weighted graphs, respectively. It is time-consuming to deal with large-scale graphs, which motivates us resort to distributed computing and parallel algorithms. In this paper, we design a vertex-based parallel algorithm following the shortest path approach (SPBC). Moreover, we propose a distributed algorithm based on message propagation (MPBC) to quantify the importance of vertices. MPBC takes into account the real situation of information diffusion in social networks. We implement our algorithms on Graphlab and evaluate them through comprehensive experiments. the results show that both SPBC and MPBC scale well with the increasing number of machines. SPBC on 2 machines outperforms the classical centralized algorithm by 1.59 times in terms of running time. MPBC can handle graph with ten millions of vertices and edges within an acceptable time where classical algorithms become infeasible.

关键词： key vertices parallel algorithm SPBC MPBC

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A Hybrid Simulation of Large Crowd Evacuation

A Hybrid Simulation of Large Crowd Evacuation

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17th IEEE international conference on parallel and distributed systems (ICPADS)

作者： Wei, Xing Xiong, Muzhou Zhang, Xuguang Chen, Dan China Univ Geosci Sch Comp Sci Wuhan 430074 Peoples R China Yanshan Univ Inst Elect Engn Qinhuangdao 066004 Peoples R China Univ Birmingham Sch Comp Sci Birmingham B15 2TT W Midlands England

ISBN: (纸本)9780769545769

A Grid simulation infrastructure can facilitate a simulation comprising models of different grains and/or models of various types in nature to investigate large and complicated problems. On top of the infrastructure, a simulation of evacuating thousands of pedestrians in a large urban area has been constructed. A number of agent-based and computational models residing at two administrative domains operate together, which successfully presents the dynamics of the complex scenario at scales of both individual and crowd levels. Experimental results indicate that the proposed approach can effectively cope with the size and complexity of a scenario involving a large crowd.

关键词： Crowd Modelling & Simulation Grid computing Complex systems

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K-means parallel acceleration for sparse data dimensions on flink 21

K-means parallel acceleration for sparse data dimensions on ...

引用

21st IEEE international conference on High Performance computing and Communications, 17th IEEE international conference on Smart City and 5th IEEE international conference on Data Science and systems, HPCC/SmartCity/DSS 2019

作者： Zeng, Zihao Li, Kenli Duan, Mingxing Liu, Chubo Liao, Xiangke Dept. College of Computer Science and Electronic Engineering Hunan University Changsha China Dept. College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781728120584

the K-means algorithm is a clustering algorithm which widely used in various applications, and it's running time is dramatically increased as the data size expanded. When the volume of data exceeds the range that can be carried by a single machine, the parallel operation of the algorithm must be implemented by using a distributed computing framework. Generally, during the parallel operation of the task, there are differences among the running time of each task due to the data skew, and the running progress of the entire job is determined by the task with the longest running time. In this paper, we propose an optimal data partitioning method for the application of the k-means algorithm on the sparsely dimensioned dataset to eliminate the data skew problem and further accelerate the parallel execution of the algorithm. Experimental evaluation on large-scale text datasets demonstrate the effectiveness of our partitioning approach on Flink. © 2019 IEEE.

关键词： K-means clustering

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parallel walking tree method for sequence recombination 17

Parallel walking tree method for sequence recombination

引用

17th international conference on parallel and distributed computing systems

作者： Hsu, T Cull, P Northwestern Polytech Univ Dept Comp Sci Fremont CA 94539 USA

ISBN: (纸本)1880843528

Generally, biological string alignment is either "local alignment" [27] or "global alignment"[26]. Both use the edit-distance model [16, 25] which assumes that changes between strings occur locally. But, evidence shows that large scale changes are possible[13]. For instance, meiotic cells' DNA replication is usually followed by homologous chromosomes' DNA recombination in which large pieces of DNA can be moved from one location to another (translocations), or replaced by their reversed complements (inversions). Walking Tree Methods are mathematically modeled for sequence recombination in which "local" and "global" alignments are just our method's two special cases. We demonstrated its use [6,7,8,9,10,11,28,29] in gene verification and discovery, sequence rearrangement phylogeny, and whole genome alignment. Alignments of million base sequences take only a few hours by our parallel methods.

关键词： recombination rearrangement genome alignment

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On termination detection in an asynchronous distributed system 17

On termination detection in an asynchronous distributed syst...

引用

17th international conference on parallel and distributed computing systems

作者： Peri, S Mittal, N Univ Texas Dept Comp Sci Richardson TX 75083 USA

ISBN: (纸本)1880843528

An important problem in distributed systems is to detect termination of a distributed computation. A distributed computation is said to have terminated when all processes have become passive and all channels have become empty. We focus on two attributes of a termination detection algorithm. First, whether the distributed computation starts from a single process or from multiple processes: diffusing computation versus non-diffusing computation. Second, whether the detection algorithm should be initiated along with the computation or can be initiated anytime after the computation has started: simultaneous initiation versus delayed initiation. We show that any termination detection algorithm for a diffusing computation can be transformed into a termination detection algorithm for a non-diffusing computation. We also demonstrate that any termination detection algorithm for simultaneous initiation can be transformed into a termination detection algorithm for delayed initiation. We prove the correctness of our transformations, and show that our transformations have minimal impact on the complexity of the given termination detection algorithm.

关键词： termination detection algorithm transformation diffusing and non-diffusing computations simultaneous and delayed initiations

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Accelerating the Kalman Filter on a GPU

Accelerating the Kalman Filter on a GPU

引用

17th IEEE international conference on parallel and distributed systems (ICPADS)

作者： Huang, Min-Yu Wei, Shih-Chieh Huang, Bormin Chang, Yang-Lang Univ Wisconsin Ctr Space Sci & Engn 1225 W Dayton St Madison WI 53706 USA Natl Taipei Univ Technol Dept Elect Engn Taipei Taiwan Tamkang Univ Dept Info Management New Taipei 25137 Taiwan

ISBN: (纸本)9780769545769

For linear dynamic systems with hidden states, the Kalman filter can estimate the system state and its error covariance considering the uncertainties in transition and observation models. In each iteration of applying the Kalman filter, the two phases of predict and update contain a total of 18 matrix operations which include addition, subtraction, multiplication and inversion. As recent graphic processor units (GPU) have shown to provide high speedup in matrix operations, we implemented a GPU accelerated Kalman filter in this work. For general reference purposes, we tested the filter on typical large-scale over-determined systems with thousands of components in states and measurements. For the various combinations of configurations in our test, the GPU accelerated filter shows a scalable speedup as either the state or the measurement dimension increases. the obtained 2 to 3 orders of magnitude speedup over its single-threaded CPU counterpart shows a promising direction of using the GPU-based Kalman filter in large-scale time-critical applications.

关键词： Kalman filter GPU CUDA parallel computing

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Heterogeneity-aware Peak Power Management for Accelerator-based systems

Heterogeneity-aware Peak Power Management for Accelerator-ba...

引用

17th IEEE international conference on parallel and distributed systems (ICPADS)

作者： Wang, Guibin Lin, Yisong National Laboratory for Parallel and Distributed Processing National University of Defense Technology China

ISBN: (纸本)9780769545769

Power management has become one of the first-order considerations in high performance computing field. Many recent studies focus on optimizing the performance of a computer system within a given power budget. However, most existing solutions adopt fixed period control mechanism and are transparent to the running applications. Although the application-transparent control mechanism has relatively good portability, it exhibits low efficiency in accelerator-based heterogeneous parallel systems. In typical accelerator-based parallel systems, different processing units have largely different processing speeds and power consumption. Under a given power constraint, how to choose the processor to be slowed down and how to schedule a parallel task onto different processors for the maximum performance are different from those in homogeneous systems and have not been well studied. From the motivating example in this paper, we could find that in order to efficiently harness the heterogeneous parallel processing, one should not only perform dynamic voltage/frequency scaling (DVFS) to meet the power budget, but also tune the parallel task scheduling to adapt to the changes. In this paper, we propose a heterogeneity-aware peak power management, which extends existing application-transparent power controller with an application-aware power controller. Firstly, we theoretically analyze the conditions for the maximum performance given a power budget for heterogeneous systems. Based on this result, we provide a power-constrained parallel task partition algorithm, which coordinates parallel task partition and voltage scaling for heterogeneous processing units to achieve the optimal performance given a system power budget. Finally, we evaluate the proposed method on a typical CPU-GPU heterogeneous system, and validate the superiority of application-aware power controller over the existing method.

关键词： Accelerator-based systems Peak Power Management GPU

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Intelligent mailbox with centralized parallel processing 17

Intelligent mailbox with centralized parallel processing

引用

17th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing, SNPD 2016

作者： Muhammad, Adeel Ur Rehman, Nabeel University of Stuttgart Stuttgart Germany University of Heilbronn Heilbronn Germany

ISBN: (纸本)9781509022397

Internet of things (IoT) has a wide range of potential from smart home systems to hospitals or in industry under the title of Industry 4.0. this not only makes our life easier to monitor and manage our tasks but also helps in making a secure and healthy environment around us. this paper describes overall topology and prototype implementation of an intelligent mailbox using concepts of IoT to facilitate monitoring of physical mailbox installed at homes and offices. Successful implementation of prototype also demonstrates how parallel computing power of modern multicore processors and general purpose graphics processing units (GPGPUs) can be exploited in smart buildings to enhance compute intensive tasks. © 2016 IEEE.

关键词： Internet of things

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Fast Snippet Generation Based On CPU-GPU Hybrid System

Fast Snippet Generation Based On CPU-GPU Hybrid System

引用

17th IEEE international conference on parallel and distributed systems (ICPADS)

作者： Liu, Ding Li, Ruixuan Gu, Xiwu Wen, Kunmei He, Heng Gao, Guoqiang Huazhong Univ Sci & Technol Intelligent & Distributed Comp Lab Sch Comp Sci & Technol Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9780769545769

As an important part of searching result presentation, query-biased document snippet generation has become a popular method of search engines that makes the result list more informative to users. Generating a single snippet is a lightweight task. However, it will be a heavy workload to generate multiple snippets of multiple documents as the search engines need to process large amount of queries per second, and each result list usually contains several snippets. To deal with this heavy workload, we propose a new high-performance snippet generation approach based on CPU-GPU hybrid system. Our main contribution of this paper is to present a parallel processing stream for large-scale snippet generation tasks using GPU. We adopt a sliding document segmentation method in our approach which costs more computing resources but can avoid the common defect that the high relevant fragment may be cut off. the experimental results show that our approach gains a speedup of nearly 6 times in average process time compared with the baseline approach-Highlighter.

关键词： query-biased snippet generation graphics processing unit CPU-GPU hybrid system parallel processing stream sliding document segmentation

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