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检索条件"任意字段=International Symposium Distributed Computing and Applications Business Engineering and Science"

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Pattern Learning Based Parallel Ant Colony Optimization

Pattern Learning Based Parallel Ant Colony Optimization

引用

IEEE international symposium on Parallel and distributed Processing with applications and IEEE international Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Xiaotian Jin Wenbo Zheng Shaocong Mo Yili Qu Xin Jin Jiangwei Zhou Pengfei Duan Tao Zheng School of Computer Science and Technology Wuhan University of Technology Wuhan China School of Software Engineering Xi'an Jiaotong University Xi'an China School of Data and Computer Science Sun Yat-sen University Guangzhou China School of Management Huazhong University of Science and Technology Wuhan China School Of Computer Science and Technology Huazhong University of Science and Technology Wuhan China Wuhan University of Technology Wuhan Hubei CN School of Computer Science and Technology Wuhan University of of Technology Wuhan China

ISBN: (纸本)9781538637913

Ant colony optimization (ACO) can be used to solve complex optimization problems in engineering, economic management and military strategy. Most of these are NP hard problems, which are difficult to solve with traditional methods. An improved parallel ACO algorithm based on pattern learning is proposed in this paper. It extracts parameters automatically to reduce solution space and enhance calculation efficiency. Various parameters in the algorithm are analyzed, and a refining strategy is formed according to ACO's characteristics. The parallel ACO algorithm is carried out under the MIC/CPU architecture, and it can significantly enhance performance.

关键词： Microwave integrated circuits Urban areas Parallel processing Layout Computer architecture Computer science Support vector machines

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Symmetric Key Based Secure Resource Sharing 1

引用

5th international symposium on Security in computing and Communications, SSCC 2017

作者： Bezawada, Bruhadeshwar Kothapalli, Kishore Raman, Dugyala Li, Rui Mahindra Ecole Centrale Hyderabad India International Institute of Information Technology Hyderabad India Vardhaman College of Engineering Hyderabad India College of Computer Science and Networking Security Dongguan University of Technology of Science and Technology Dongguan China

ISBN: (数字)9789811068980

ISBN: (纸本)9789811068973

We focus on the problem of symmetric key distribution for securing shared resources among large groups of users in distributed applications like cloud storage, shared databases, and collaborative editing, among others. In such applications, resources such as data, are sensitive in nature and it is necessary that only authorized users are allowed access without the presence of on-line monitoring system. The de-facto approach is to encrypt a shared resource and deploy a key distribution mechanism, which enables only authorized users to generate the respective decryption key for the resource. The key distribution approach has two major challenges: first, the applications are dynamic i.e., users might join and leave arbitrarily, and second, for a large number of users, it is required that the cryptographic technique be scalable and efficient. In this work, we describe an approach that overcomes these challenges by using two key techniques: first, flattening the access structure and applying efficient symmetric key distribution techniques. By flattening the access structure, we reduce the problem to that of key distribution of a resource among all the users sharing that resource. We consider this smaller flattened access structure and devise a unified key distribution technique that is sufficient for key distribution across all such structures. Our key distribution techniques have an important feature of a public secret and a private secret, which allows the group controller to publish updates to the keying material using the public secret and therefore, does not necessitate the users to be in constant communication with the group controller. Using this model we describe two efficient key distribution techniques that scale logarithmically with the group size and also handle group additions and removals. Furthermore, a user can be off-line for any amount of time and need not be aware of the dynamics of the system, which is important as it overcomes the problems posed by l

关键词： Cloud storage

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TDAG: A Tunable distributed Data Processing Model for Data Stream

TDAG: A Tunable Distributed Data Processing Model for Data S...

引用

IEEE international symposium on Parallel and distributed Processing with applications and IEEE international Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Jintao Tang Xuelian Lin Yang Shen Tianyu Wo The Institute of Advanced Computing Technology School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9781538637913

As the Internet of Vehicles (IoV) becomes flourishing and the data generated by sensors be ubiquitous, there exist various kinds of IoV applications with different performance requirements. Hence, different distributed data processing systems (DDPS) clusters will coexist, e.g., a stream processing system cluster for real-time tasks and a batch one for statistics based data mining tasks, to meet the requirements of such IoV applications. However, it is not an economical or convenient way to maintain varied systems clusters, as the developers and/or administrators have to be familiar with all of these DDPSs, and of course, the deployment of multiple DDPS means a waste of resources compared to the deployment of one DDPS. Based on these observations, this paper proposes the TDAG as a solution. TDAG allows users to adjust the data processing from the streaming style to the batch style by encapsulating the input data with specific packing strategies. We have implemented TDAG in a prototype called TStream. The experimental tests show that our TStream is both effective and efficient.

关键词： Computational modeling Task analysis Sparks Throughput Data encapsulation Fasteners Storms

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Target Coverage-Aware Clustering for Directional Sensor Networks

Target Coverage-Aware Clustering for Directional Sensor Netw...

引用

IEEE international symposium on Parallel and distributed Processing with applications and IEEE international Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Selina Sharmin Fernaz Narin Nur Md. Abdur Razzaque Md. Mustafizur Rahman Department of Computer Science and Engineering University of Dhaka Dhaka Bangladesh Dhaka University Dhaka Dhaka District BD

ISBN: (纸本)9781538637913

In this work, we develop a target coverage-aware clustering algorithm for directional sensor networks, namely,,,, TRACE, that enhances the network lifetime. The TRACE nodes exploit single-hop neighborhood information only to elect cluster heads (CHs) and gateways. Thus, the TRACE is a fully distributed and light-weight clustering algorithm. The TRACE CHs greedily maximize the number of targets covered by as minimum number of sensor nodes as possible. The performances of the proposed TRACE system are studied on Network Simulator version 3 (ns- 3), and the results show that, it outperforms a state-of-the-art- work.

关键词： Logic gates Clustering algorithms Sensors Energy states Monitoring Smart cities Clustering methods

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A Fast distributed Principal Component Analysis with Variance Reduction

A Fast Distributed Principal Component Analysis with Varianc...

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2017 16th international symposium on distributed computing and applications to business,engineering and science（DCABES 2017）

作者： Shiyuan Shang-Guan Jianping Yin Department of Computer Science and Technology National University of Defense Technology

Principal Component Analysis(PCA) and Singular Value Decomposition(SVD) are widely used in dimension reduction,feature extraction,low-rank matrix approximation and so *** large-scale applications,a common alternative is to use cluster which have multiple nodes and multiple cores to accelerate the time of solving *** of the existing distributed PCA algorithm focus on reducing the communication,and there is little attention to the frequent waiting phenomenon caused by the synchronization ***,most of these works are based on either the distributed memory of the processeslevel parallelism or the shared memory of threads-level *** this paper,we propose a fast distributed PCA algorithm with variance reduced,which based on stochastic sampling and Stale Synchronous *** algorithm contains the processes-level and threads-level *** on the "Tianhe-2" super computer demonstrate that our algorithm has a good performance,speedup,and scalability.

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Parallel Skyline Computation for Partially Ordered Domains

Parallel Skyline Computation for Partially Ordered Domains

引用

IEEE international symposium on Parallel and distributed Processing with applications and IEEE international Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Bo Yin Ke Gu School of Computer and Communication Engineering Changsha University of Science and technology Changsha China

ISBN: (纸本)9781538637913

The skyline queries help users handle the huge amount of available data by finding a set of interesting points. As the dataset sizes are constantly increasing and skyline queries are computationally expensive, it is critical to compute such queries by utilizing parallelism. Existing works deal exclusively with the totally ordered attribute domains. In this paper, we present a framework, named PSLP, for parallel skyline evaluation for data with both totally and partially ordered *** introduce a new partial-to-order mapping scheme that guarantees the correctness of the mapping by preserving incomparability and preference with low mapping cost. We also propose a novel logical partitioning for parallel processing where data space are partitioned according to their incomparability and preference relationships by using a pivot point. The logical partitioning can prune away partitions that do not contain any skyline point at the partitioning processing. An extensive performance evaluation confirms the efficiency and effectiveness of the proposed approach.

关键词： Parallel processing Automobiles Merging Data analysis distributed processing Conferences Ubiquitous computing

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The Design Model of Freeway Toll Collection

The Design Model of Freeway Toll Collection

引用

2017 16th international symposium on distributed computing and applications to business,engineering and science（DCABES 2017）

作者： Jinwei Chang Kuntao Lai Baizhen Wang School of Automotive Engineering Wuhan University of Technology School of Transportation Wuhan University of Technology School of Science Wuhan University of Technology

The congestion of toll plaza is an urgent problem in *** to the theory of cellular automata with the consideration of the factors,such as safety precaution and design cost,an asymmetric design model of toll plaza confluence is established,and this model simulates the running of the vehicle at the toll station as well as analyzes the relationships between the vehicle flow,vehicle velocity and traffic *** result demonstrates that the model can effectively improve the vehicle congestion at the toll station.

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Cooperative Game Approach for Energy-Aware Load Balancing in Clouds

Cooperative Game Approach for Energy-Aware Load Balancing in...

引用

IEEE international symposium on Parallel and distributed Processing with applications and IEEE international Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Bo Yang Zhiyong Li Shilong Jiang PKU-HKUST Shenzhen-HongKong Institution Shenzhen China The college of computer science and electronic engineering Hunan University Changsha China

ISBN: (纸本)9781538637913

In cloud environments, failure to fully consider the tradeoff between the energy saving and performance would lead to a sub-optimal scenario. In this paper we model the load balancing problem as a cooperative game among the multiserver systems and present the structure of the Nash bargaining solution (NBS). The objective of the proposed algorithm is to minimize the energy consumption of cloud data centers while promising an acceptable average response time for their customers, in which the computing resources are provided in a greedy manner, and then the users' tasks are allocated along with the concept of the Nash bargain solution. We compared the performance of the proposed approach with the existing approaches. Simulated results demonstrate that the proposed technique has immense potential to balance the tradeoff between the energy saving and performance for the cloud data centers.

关键词： Cloud computing Games Servers Load management NIST Energy consumption Task analysis

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Efficient and Customizable Top-k Query on Named Data Networking

Efficient and Customizable Top-k Query on Named Data Network...

引用

IEEE international symposium on Parallel and distributed Processing with applications and IEEE international Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Zhuhua Liao Zengde Teng Jian Zhang Yizhi Liu Jianxun Liu College of Computer Science and Engineering Hunan University of Science and Technology Xiangtan China

ISBN: (纸本)9781538637913

Offering a flexible paradigm for efficient data discovery is a crucial requirement in large information-centric networks. However, a major hindrance to query data in multicast networks is the uncertain sources and crowds of answering, which causes heavy network traffic and unduly long response time. In this paper, we present an efficient and customizable top-k query processing architecture, called NDN-Qk, by leveraging the emerging named data networking (NDN). NDN-Qk provides a completely ad-hoc and flexible query paradigm and enables the forwarders that distributed on NDN to cooperatively discover and aggregate the relevant top-k data. Specifically, we present adaptive types and strategies of data aggregation, and response completeness discerning algorithm for efficiently aggregating multiple top-k answers in NDN. Moreover, we further introduce a customizable query solution for adjusting the scale, score and range of response data in NDN-Qk. Finally, our comprehensive experimental evaluations demonstrates the effectiveness of our top-k query processing solutions and the performance of our proposed algorithms.

关键词： distributed databases Telecommunication traffic Query processing Protocols Time factors distributed processing Data models

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Hidden Markov Model Based Spot Price Prediction for Cloud computing

Hidden Markov Model Based Spot Price Prediction for Cloud Co...

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IEEE international symposium on Parallel and distributed Processing with applications and IEEE international Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Duan Liu Zhicheng Cai Xiaoping Li School of Computer Science and Engineering Nanjing University of Science and Technology China Ministry of Education Key Laboratory of Computer Network and Information Integration (Southeast University)

ISBN: (纸本)9781538637913

Cloud computing accelerates the processing of big data applications by providing elastic virtual machines. Spot instances are virtual machines sold by auctions which offer lower prices (called Spot prices) than the same virtual machines with fixed prices. Spot prices change stochastically according to the real-time user demands and supplies. Accurate Spot price prediction helps users choose appropriate resources and set optimal bids to reduce resource rental cost. However, great fluctuations of recent Spot prices decrease the prediction accuracy of existing autoregression based prediction methods. Therefore, in this paper, a Hidden Markov Model and Expectation based prediction method (HMM-E) is proposed which uses Markov processes to describe the different demand markets of Cloud computing (hidden states) and the fluctuation degrees of Spot prices (observations) separately. Experimental results demonstrate that HMM-E predicts Spot prices more accurately than the existing autoregression based forecasting methods when the forecast period is shorter than about five hours.

关键词： Hidden Markov models Predictive models Cloud computing Computational modeling Markov processes Prediction algorithms Biological system modeling

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