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检索条件"任意字段=3rd International Conference on Soft Computing in Data Science, SCDS 2017"

共 696 条记录，以下是321-330 订阅

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Cost-Efficient Big Intermediate data Placement in a Collaborative Cloud Storage Environment 19

Cost-Efficient Big Intermediate Data Placement in a Collabor...

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19th IEEE international conference on High Performance computing and Communications (HPCC) / 15th IEEE international conference on Smart City (SmartCity) / 3rd IEEE international conference on data science and Systems (DSS)

作者： Ikken, Sonia Renault, Eric Barkat, Amine Tari, Abdelkamel Kechadi, Tahar Univ Paris Saclay CNRS Samovar UMR 5157 Telecom SudParis Paris France UCD Sch Comp Sci & Informat Dublin Ireland Politecn Di Milano Milan Italy Univ Bejaia Fac Exact Sci Bejaia 06000 Algeria

ISBN: (纸本)9781538625880

Collaborative cloud storage environment, which share resources of multiple geographically distributed datacenters owned by different providers enable scientific workflow from different locations to process large scale big intermediate data through the Internet. Distributed datacenters are federated and each member can collaborate with each other to efficiently share and process the intermediate data from distributed workflow instances. This paper focuses on the storage cost minimization of intermediate data placement in federated cloud datacenters. Through collaborative and federation mechanisms, we propose an exact federation data placement algorithm based on integer linear programming model (ILP) to assist multiple datacenters hosting intermediate data files generated from a scientific workflow. Under the constraints of the problem, the proposed algorithm finds an optimal intermediate data placement with a cost saving over the federated cloud datacenters, taking into account scientific user requirements, data dependency and size. Experimental results show the cost-efficiency of the proposed cloud storage federation algorithm.

关键词： Collaborative Cloud Storage Environment Big data Scheduling Storage Cost Saving Intermediate data Dependency

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Model-based Scheduling for Stream Processing Systems 19

Model-based Scheduling for Stream Processing Systems

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作者： Wang, Yidan Tari, Zahir HoseinyFarahabady, M. Reza Zomaya, Albert Y. RMIT Univ Sch Sci Melbourne Vic Australia Univ Sydney Sch IT Ctr Distributed & High Performance Comp Sydney NSW Australia

ISBN: (纸本)9781538625880

Stream processing is emerging to react to the changing business situations of real-time processing. The main aim of this paradigm is to deal with the huge volume of data in the format of information flows originating from distributed devices. This consequently poses challenges to the scheduling problem in cloud data centers regarding the time-varying velocity of data ingesting and processing. In response to the uncertainties and complexities of streaming data, we propose a model-based scheduling scheme for stream processing systems, capturing the system behavior and providing an optimal allocation strategy to adapt to the changing work conditions. The proposed scheduling policy is implemented in Apache Storm, and micro-benchmarks with various shapes (e.g line, star, and diamond) were used in the evaluation. A topology that tracks trending topics on Twitter is also used, where the input is feeding with tweets in realtime. Experimental results show that the proposed solution can perform estimations that are well aligned with the system performance. The proposed scheduling policy achieves an improved performance with regards throughput and latency under varying ingesting rates.

关键词： Streaming data Processing Resource Allocation/Scheduling Apache Storm

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FatCBST: Concurrent Binary Search Tree with Fatnodes 19

FatCBST: Concurrent Binary Search Tree with Fatnodes

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作者： Alapati, Praveen Tavva, Venkata Kalyan Mutyam, Madhu Indian Inst Technol Madras Dept Comp Sci & Engn Madras 600036 Tamil Nadu India IBM India Pvt Ltd STG Labs Bengaluru India

ISBN: (纸本)9781538625880

Effective design of concurrent tree implementation plays a major role in improving the scalability of applications in a multicore environment. We introduce a concurrent binary search tree with fatnodes (FatCBST) and present algorithms to perform basic operations on it. Unlike a simple node with single value, a fatnode consists of a set of values. FatCBST concept allows a thread to perform update operations on an existing fatnode without changing the tree structure, making it less disruptive to other threads' operations. Fatnodes help to take advantage of the spatial locality in the cache hierarchy and also reduce the height of the concurrent binary search tree. Our FatCBST implementation allows multiple threads to perform update operations on the same existing fatnode at the same time. Experimental results show that the FatCBST implementations that have small fatnode sizes provide better throughput for high and medium contention workloads;and large fatnode sizes provide better throughput for low contention workloads, as compared to the current state-of-the-art implementations.

关键词： concurrent data structures trees concurrent binary search trees

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data Loss and Reconstruction for Wireless Environmental Sensor Networks 3

Data Loss and Reconstruction for Wireless Environmental Sens...

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IEEE 3rd international conference on Big data Security on Cloud (BigdataSecurity) / 3rd IEEE international conference on High Performance and Smart computing (HPSC) / 2nd IEEE international conference on Intelligent data and Security (IDS)

作者： Bao, Ting Huang, Zhangqin Li, Da Beijing Univ Technol Beijing Adv Innovat Ctr Future Internet Technol Beijing Peoples R China Beijing Univ Technol Beijing Engn Res Ctr IoT Software & Syst Beijing Peoples R China

ISBN: (纸本)9781509062966

Environmental Sensor Networks (ESNs) in forests facilitate the study of fundamental processes, and the development of wireless communication makes ESNs into 'intelligent' sensor network, named as Wireless Environmental Sensor Networks (WESNs). However, data loss is prevalent in wireless transmission, which may result in incompletion of sensory datasets. Thus, if we want to achieve a satisfactory accuracy in a WESNs system, the task of recovering data from achieved sensory datasets is unavoidable. Previous works provide many approaches to solve the data missing problem. Compared with other methods, Compressing Sensing (CS) is powerful technique for estimating data, which can utilize a small fraction of data to reconstruct the entire dataset. In real forests, because of the complicated geographic conditions and deployment of sensors, sensory data will largely loss during the wireless transmission. Despite CS technique is a better choice, it cannot be directly applied for the data missing problem. In this paper, we will present a reliable WESNs system and a better approach based on CS to reconstruct sensory datasets.

关键词： Wireless Environmental Sensor Networks forests data loss Compressing Sensing

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Fuzzy arithmetical modeling of pressurizer in a nuclear power plant 3rd

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3rd international conference on soft computing in data science, scds 2017

作者： Mohamad, Wan Munirah Wan Ahmad, Tahir Rahman, Niki Anis Ab Ashaari, Azmirul Department of Mathematical Science Faculty of Science Universiti Teknologi Malaysia UTM SkudaiJohor81310 Malaysia Centre for Sustainable Nanomaterials Ibnu Sina Institute for Scientific and Industrial Research Universiti Teknologi Malaysia UTM SkudaiJohor81310 Malaysia

ISBN: (纸本)9789811072413

A pressurizer is to control pressure and temperature in a nuclear power plant. In this paper, a model using fuzzy arithmetic which is based on the Transformation Method (TM) is presented. The analytical solution is used to evaluate the state space model. The TM is then used to quantify the influence of each parameter, and the estimation of relative and absolute measures of uncertainty. To ensure the operating system is maintained and efficient, the method is applied to a pressurizer for simulation and analysis. Simulation and analysis of TM’s efficiency are presented in this paper. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Nuclear power plants

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Leveraging Mobile Signaling data for Monitoring Vehicles on Highways in Real Time 3

Leveraging Mobile Signaling Data for Monitoring Vehicles on ...

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3rd international conference on Big data computing and Communications (BIGCOM)

作者： Cui, Yanling Ji, Qiang Zhang, Fusang Jin, Beihong Chinese Acad Sci Inst Software State Key Lab Comp Sci Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781538633496

To satisfy the real time and full coverage vehicle monitoring requirements from traffic administrative departments, we present an approach named Dipper by exploring signaling data in the mobile communication networks. In particular, by treating mobile phones as roving sensors, Dipper estimates whole traffic conditions on highways in terms of vehicle speeds, traffic volumes and vehicle types. In this way, the vehicles can be continuously monitored in real time with full region coverage. To evaluate our approach, extensive experiments are conducted by taking the large-scale real-world signaling data from a major mobile operator in China as input. The experimental results show that the Dipper approach can well capture the vehicle speeds, traffic volumes, and vehicle types on highways.

关键词： signaling data traffic conditions data mining intelligent transportation system

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Homomorphic Cloud computing Scheme Based on Hybrid Homomorphic Encryption 3

Homomorphic Cloud Computing Scheme Based on Hybrid Homomorph...

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3rd IEEE international conference on Computer and Communications (ICCC)

作者： Song, Xidan Wang, Yulin Wuhan Univ Int Sch Software Wuhan Hubei Peoples R China

ISBN: (纸本)9781509063529

At present, the fully homomorphic encryption method has disadvantages of large key size and low calculation efficiency, and it is not practical for the secure cloud computing. We develop a hybrid cloud computing scheme based on the Paillier algorithm which is additively homomorphic, and RSA encryption algorithm which is multiplicative homomorphic. Customer's calculation requests can be described as the combination of simple add and multiplicative operation and the operands. An Encryption Decryption Machine which running in the private cloud processes the encryption according to the type of the operation and upload the cipher texts to the public cloud. The public cloud process calculation without knowing the exact data. Then we run simulations and analyze the results, and the results show that the scheme is practical and efficient.

关键词： cloud computing homomorphic encryption data security the private cloud Paillier RSA

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Exploring Home and Work Locations in a City from Mobile Phone data 19

Exploring Home and Work Locations in a City from Mobile Phon...

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作者： Tongsinoot, Lumpsum Muangsin, Veera Chulalongkorn Univ Dept Comp Engn Fac Engn Bangkok Thailand Chulalongkorn Univ CU Big Data Analyt & IoT Ctr CUBIC Dept Comp Engn Fac Engn Bangkok Thailand

ISBN: (纸本)9781538625880

Recently, mobile phone call detail records (CDR) have been used to study mobility patterns in cities. Since home and workplace are the most important places in people's lives and define the structure and activity patterns of the city, identifying home and work locations and home-work commuting patterns are of much interest. However, due to decreasing usage of voice calls and SMS, and low usage while people staying at home, identifying home and work locations are getting more difficult. In this paper, we develop a method to exploit daily-aggregated internet usage data (G-CDR) in addition to CDR for identifying work locations. We also develop a method for identifying home locations based on detecting sleeping time. This method can significantly increase home detection success rate and accuracy. From the identified home and work locations, we have explored the population distribution and commuting patterns of people in Bangkok.

关键词： Location data Call Detail Records

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Quantifying and Mitigating Computational Inefficiency of Genomics data Analysis 19

Quantifying and Mitigating Computational Inefficiency of Gen...

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作者： Li, Xueqi Tan, Guangming Zhang, Chunming Li, Xu Zhang, Zhonghai Sun, Ninghui Chinese Acad Sci Inst Comp Technol State Key Lab Comp Architecture Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781538625880

In this paper, we performed a comprehensive study of quantifying and mitigating computational inefficiency of current genomic analysis approaches. First, we found current parallelization approaches that have limited scalability due to either unexploited parallelism or low utilization of system resource. Thus, we proposed Spark-Gene, which is on the basis of Spark in-memory programming model. To test the performance of our Spark-Gene, we used WGS in the GATK as the test case. We show that Spark-Gene reduces the execution time of WGS analysis from 19 hours to 30 minutes with a speedup in excess of 37-fold at 256 CPU cores. Furthermore, we identified that garbage collection is the major scalable bottleneck of better parallel efficiency for native in-memory computing model. Second, we quantified microarchitectural inefficiency for typical genomic applications and uncovered opportunities for microarchitectural optimizations for the design of genomic domain-specific accelerator, especially on specializing concurrency, computation and memory hierarchy. This paper is to leverage state-of-art big-data technologies to improve parallelization for genomics analysis and motivate the integration of accelerators into the genomic analysis computing system.

关键词： Genomics Bioinformatics Pipelines Sequential analysis Microarchitecture Cancer Tools

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A survey of offline handwritten Hindi character recognition 3

A survey of offline handwritten Hindi character recognition

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3rd international conference on Advances in computing, Communication and Automation (Fall), ICACCA 2017

作者： Indian, Ajay Bhatia, Karamjit Invertis University Bareilly India Department of Computer Science Gurukula Knagri Vishvidyalaya Haridwar India

ISBN: (纸本)9781509064038

The problem of character recognition may be categorized into two categories-recognition of printed characters and recognition of handwritten characters. Further, the problem of handwritten character recognition is categorized into two categories-recognition of offline handwritten characters and recognition of online characters. This paper presents an extensive overview of research work, which have been done for recognizing the offline handwritten characters using the various approaches like-ANNs, Fuzzy Logic, Genetic algorithms, SVM, KNN Hidden Markov Model (HMM), Bacterial Foraging, Clonal Selection Algorithm etc. and discuss their performance in terms of accuracy of recognizing the characters. © 2017 IEEE.

关键词： soft computing

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