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Idempotent Task Cache System for Handling Intermediate Data Skew in MapReduce on Cloud Computing 云计算MapReduce中处理中间数据倾斜的幂等任务缓存系统
Pub Date : 2016-12-01 DOI: 10.1109/ICS.2016.0111
Tzu-Chi Huang, Kuo-Chih Chu, Jia-Hui Lin, C. Shieh
A MapReduce system gradually becomes a popular platform for developing cloud applications while MapReduce is the de facto standard programming model of the applications. However, a MapReduce system may suffer intermediate data skew to degrade performances because input data is unpredictable and the Map function of the application may generate different quantities of intermediate data according to the application algorithm. A MapReduce system can use the Idempotent Task Cache System (ITCS) proposed in this paper to handle intermediate data skew. A MapReduce system can avoid negative performance impacts of intermediate data skew with ITCS by using caches to skip the high workload of processing skewed intermediate data in certain Reduce tasks. In experiments, a MapReduce system is tested with several popular applications to prove that ITCS not only alleviates performance penalties when intermediate data skew happens, but also greatly outperforms native MapReduce systems without any help of ITCS.
MapReduce系统逐渐成为开发云应用程序的流行平台,而MapReduce实际上是应用程序的标准编程模型。但是,由于输入数据不可预测,并且应用程序的Map函数可能根据应用程序算法生成不同数量的中间数据,因此MapReduce系统可能会出现中间数据倾斜,从而降低性能。MapReduce系统可以使用本文提出的幂等任务缓存系统(ITCS)来处理中间数据倾斜。MapReduce系统可以通过使用缓存跳过某些Reduce任务中处理倾斜中间数据的高工作量,从而避免ITCS对中间数据倾斜的负面性能影响。在实验中,用几个流行的应用程序对MapReduce系统进行了测试,证明ITCS不仅减轻了中间数据倾斜发生时的性能损失,而且在没有任何ITCS帮助的情况下大大优于原生MapReduce系统。
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引用次数: 2
Constructing ECA Rule for IoT Application through a Novel S2RG Process: The Exemplary ECA Rules for Smarter Energy Applications 通过新型S2RG流程构建物联网应用的ECA规则:智能能源应用的ECA规则示例
Pub Date : 2016-12-01 DOI: 10.1109/ICS.2016.0114
Yu-Tso Chen, Ching-Chung Chen, Hao-Yun Chang, Hsin-Shan Lin, Hsuan-Ting Chang
As the development of Internet of Things (IoT) is increasingly emphasized, how to adopt interconnected sensors and devices in conjunction with situation-awareness based system to smarten living applications has paid great attentions. On a multiple-units connected environment, a scheme of event-condition-action (ECA) is frequently used to serve automatic operation functions in the light of defined rules. According to the previous works, the ECA approach was often adopted in IC designs but less applied in advancing human-centered IoT applications, one of the main problems is the difficulty in directly generating ECA rules from human-centered application scenarios. This paper proposes a scenario-triggered, state-based rule generation (shortly S2RG) process which enables a complete but simplified way to conduct ECA rule for human-centered IoT applications. With the operation of the presented S2RG process, this paper also demonstrates ECA rules for two exemplary power saving scenarios for smarter energy applications.
随着物联网(IoT)的发展日益受到重视,如何将互联的传感器和设备与基于态势感知的系统相结合,实现智能生活应用备受关注。在多单元连接的环境中,事件-条件-动作(ECA)方案经常被用来根据定义的规则服务于自动操作功能。根据以往的工作,ECA方法通常用于IC设计,但很少用于推进以人为中心的物联网应用,主要问题之一是难以直接从以人为中心的应用场景中生成ECA规则。本文提出了一个场景触发的、基于状态的规则生成(简称S2RG)过程,该过程能够以一种完整但简化的方式为以人为中心的物联网应用执行ECA规则。通过所提出的S2RG过程的操作,本文还演示了两种典型节能方案的ECA规则,以实现智能能源应用。
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引用次数: 0
A Framework for Opinion Mining System with Design Pattern 基于设计模式的意见挖掘系统框架
Pub Date : 2016-12-01 DOI: 10.1109/ICS.2016.0128
Nien-Lin Hsueh
Due to the sheer volume of opinion rich web resources such as discussion forum, review sites, blogs, and news corpora available in digital form, much of the current research is focusing on the area of sentiment analysis. People are intended to develop a system that can identify and classify opinion or sentiment as represented in an electronic text. An accurate method for predicting sentiments could enable us, to extract opinions from the internet and predict on-line customer's preferences, which could prove valuable for economic or marketing research. In this paper we present a framework for opinion mining in Traditional Chinese-called FOM (Framework of Opinion Mining) to collect unstructured articles in the popular web site and analyse the opinion and sentiment in the semi-automatic way. The framework is developed by objected oriented design patterns, such as to support the flexibility and maintainability. With the FOM framework, new analysis algorithm can be easily replaced and integrated in a new application. A flood predication application based on facebook text in Taiwan will be demonstrated in this paper.
由于大量的意见丰富的网络资源,如论坛,评论网站,博客和新闻语料库的数字形式,目前的许多研究都集中在情感分析领域。人们打算开发一种系统,可以识别和分类电子文本中所代表的意见或情绪。一种准确的预测情绪的方法可以使我们能够从互联网上提取意见,并预测在线客户的偏好,这对经济或营销研究来说是有价值的。本文提出了一种观点挖掘框架,即FOM (framework of opinion mining),用于在热门网站中收集非结构化文章,并以半自动的方式分析观点和情感。该框架采用面向对象的设计模式开发,以支持灵活性和可维护性等。利用FOM框架,可以方便地替换和集成新的分析算法。本文将演示一个基于facebook文本的台湾洪水预测应用程序。
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引用次数: 3
Inference of Share Stacking Based on Progressive Visual Cryptography 基于渐进式视觉密码的共享叠加推理
Pub Date : 2016-12-01 DOI: 10.1109/ICS.2016.0054
Y. Zeng, Wen-Tsung Chang
The objective of visual cryptography is to hide secret in multiple share images. Then, stacking share images together decrypts hidden secret by human visual system. As the share images are given with different priorities, those share images hide various degrees of secret, which is the objective of progressive visual cryptography. This paper presents a scheme to realize progressive visual cryptography. A 2x2 block is the basic element of share image, and we design block pairs for secret hiding as well as secret encryption. The degrees of hidden secret depend on the priorities of share images. The proposed scheme is capable of decrypting partial secret and inferring the stacked shares. The experiment results will demonstrate that our scheme further achieves applications based on progressive visual cryptography, including self-decryption watermark, and inference of shares stacking.
视觉密码学的目标是在多个共享图像中隐藏秘密。然后,将共享图像叠加在一起,通过人类视觉系统解密隐藏的秘密。由于共享图像被赋予了不同的优先级,这些共享图像隐藏了不同程度的秘密,这是渐进式视觉密码学的目标。提出了一种实现渐进式视觉密码的方案。一个2x2的块是共享图像的基本元素,我们设计了块对用于秘密隐藏和秘密加密。隐藏秘密的程度取决于共享图像的优先级。该方案能够对部分秘密进行解密,并推断出堆叠的共享。实验结果表明,我们的方案进一步实现了基于渐进式视觉密码的应用,包括自解密水印和共享叠加推理。
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引用次数: 2
An Efficient and Secure Public Batch Auditing Protocol for Dynamic Cloud Storage Data 一种高效、安全的云存储动态数据公共批量审计协议
Pub Date : 2016-12-01 DOI: 10.1109/ICS.2016.0138
Liu Yang, Lili Xia
Cloud storage supplies enormous convenience for numerous companies and individuals to manage their data. However, data owners lose ultimately physical control of their data, which introduces many potential safety hazards in the cloud storage environment. Many scholars have made studies on the security problem of cloud storage data. To solve the problem, we propose a secure audit scheme supporting dynamic operation and transparent verification. Utilizing BLS short signature as well as the sequence-enforced B+ Hash Tree structure, the audit scheme is more effective. The scheme introduces an organizer in the auditing process to prevent the TPA from getting any information about the data's location. Thus, the scheme is completely transparent for TPA. Meanwhile, the scheme utilizes random mask and bilinear aggregate signature technology to realize privacy protection and batch audit.
云存储为众多公司和个人管理数据提供了极大的便利。然而,数据所有者最终失去了对其数据的物理控制,这在云存储环境中引入了许多潜在的安全隐患。许多学者对云存储数据的安全问题进行了研究。为了解决这一问题,我们提出了一种支持动态操作和透明验证的安全审计方案。利用BLS短签名和序列强制的B+哈希树结构,审计方案更加有效。该方案在审计过程中引入了一个组织者,以防止TPA获取有关数据位置的任何信息。因此,该方案对TPA是完全透明的。同时,该方案利用随机掩码和双线性聚合签名技术实现隐私保护和批量审计。
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引用次数: 4
A Goal-Driven Attribute Selection Method for Recommendation Systems 推荐系统的目标驱动属性选择方法
Pub Date : 2016-12-01 DOI: 10.1109/ICS.2016.0118
Ching-Jung Lee, Alan Liu, Po-Hsuan Lu, Power Wu
This paper reports a requirements engineering approach to attribute selection for enhancing the results of a recommendation system. A recommendation system suffers the sparsity problem and the cold start problem with collaborative filtering which are caused by the lack of data. Our method is to introduce more timely information of user preferences to enhance the recommendation results that meet the current needs of a user. The proposed method uses a goal-driven approach with the support of the Analytic Hierarchy Process in attribute selection. The experiments show that this method derives promising results.
本文提出了一种需求工程方法来进行属性选择,以提高推荐系统的结果。推荐系统在进行协同过滤时,由于缺乏数据而存在稀疏性问题和冷启动问题。我们的方法是引入更多及时的用户偏好信息,以增强满足用户当前需求的推荐结果。该方法采用目标驱动的方法,并在属性选择中支持层次分析法。实验表明,该方法取得了良好的效果。
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引用次数: 0
New Method for Industry 4.0 Machine Status Prediction - A Case Study with the Machine of a Spring Factory 工业4.0机器状态预测的新方法——以弹簧厂机器为例
Pub Date : 2016-12-01 DOI: 10.1109/ICS.2016.0071
Tzu-Yu Lin, Yo-Ming Chen, Don-Lin Yang, Yi-Chung Chen
In response to the technological development in recent years, many technology giants are making efforts toward Industry 4.0. However, many small-and medium-sized factories cannot even computerize and automate their factories, which is the foundation of Industry 4.0, due to inadequate capital and scale. This is because the majority of these factories are still using conventional machines in which the data cannot be digitized. Consequently, they cannot achieve the goal of Industry 4.0. This work therefore proposes a simple approach that facilitates the transition of these small-and medium-sized factories. The approach uses add-on triaxial sensors to aid in machine monitoring. The data obtained is analyzed for abnormalities using neural networks. Experiment results demonstrate the validity of the proposed approach.
为了应对近年来的技术发展,许多科技巨头都在朝着工业4.0的方向努力。然而,由于资金和规模不足,许多中小型工厂甚至无法实现工厂的计算机化和自动化,而这正是工业4.0的基础。这是因为这些工厂中的大多数仍在使用传统的机器,其中的数据无法数字化。因此,他们无法实现工业4.0的目标。因此,这项工作提出了一种简单的方法,可以促进这些中小型工厂的转型。该方法使用附加的三轴传感器来辅助机器监控。使用神经网络分析获得的数据是否异常。实验结果证明了该方法的有效性。
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引用次数: 9
Task Ranking and Allocation Heuristics for Efficient Workflow Schedules 高效工作流调度的任务排序与分配启发式方法
Pub Date : 2016-12-01 DOI: 10.1109/ICS.2016.0108
Kuo-Chan Huang, Meng-Han Tsai
Task ranking and allocation are two major steps in list-based workflow scheduling. This paper explores various possibilities, evaluates recent approaches in the literature, and proposes several new task ranking and allocation heuristics. A series of simulation experiments have been conducted to evaluate the proposed heuristics. Experimental results indicate that effectiveness of task ranking and allocation heuristics largely depends on the characteristics of workflows to be scheduled, and our new scheduling heuristics can outperform previous methods when dealing with workflows of high CCR (Communication-to-Computation Ratio) values.
任务排序和分配是基于列表的工作流调度的两个主要步骤。本文探讨了各种可能性,评估了文献中的最新方法,并提出了几种新的任务排序和分配启发式方法。我们进行了一系列的仿真实验来评估所提出的启发式算法。实验结果表明,任务排序和分配启发式算法的有效性在很大程度上取决于待调度工作流的特征,在处理高通信计算比的工作流时,我们的新调度启发式算法优于以往的方法。
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引用次数: 4
Abnormal Event Detection Using Microsoft Kinect in a Smart Home 在智能家居中使用微软Kinect进行异常事件检测
Pub Date : 2016-12-01 DOI: 10.1109/ICS.2016.0064
Hsiu-Yu Lin, Yu-Ling Hsueh, W. Lie
In this paper, we present a continuous deep learning model for fall detection using Microsoft Kinect. The input include pre-processed high-resolution RGB images, depth images collected by a Kinect and optical flow images. We combine several deep learning structures including convolutional neural networks and long short-term memory networks for continuous human fallen detection. Finally, we present experimental results to demonstrate the performance and utility of our approach.
在本文中,我们提出了一个使用微软Kinect进行跌倒检测的连续深度学习模型。输入包括预处理的高分辨率RGB图像、Kinect采集的深度图像和光流图像。我们结合了卷积神经网络和长短期记忆网络等几种深度学习结构,用于连续的人体跌倒检测。最后,我们给出了实验结果来证明我们的方法的性能和实用性。
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引用次数: 10
Expressing Requirements of Spot Services in Problem Frames: Design Domains as Physical-Lexical Domains 在问题框架中表达现货服务需求:作为物理-词汇域的设计域
Pub Date : 2016-12-01 DOI: 10.1109/ICS.2016.0117
Chin-Yun Hsieh, Yu Chin Cheng, J. Jwo
An extension to the design domain of problem frames has been proposed. The proposed extension is intended to cope with the inclusion of lexical design domains that have physical counterparts with the equivalent information. An example of the use of such a physical counterpart is illustrated with a spot service application in patient monitoring.
提出了问题框架设计领域的一个扩展。建议的扩展旨在处理包含具有等效信息的物理对应物的词汇设计域。使用这种物理对应物的一个例子是用病人监测中的现场服务应用程序来说明的。
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引用次数: 0
期刊
2016 International Computer Symposium (ICS)
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