2016 Sixth International Conference on Information Science and Technology (ICIST)最新文献_第4页

A dynamic resource allocation and task scheduling strategy with uncertain task runtime on IaaS clouds IaaS云环境下任务运行时不确定的动态资源分配和任务调度策略

2016 Sixth International Conference on Information Science and Technology (ICIST) Pub Date : 2016-05-06 DOI: 10.1109/ICIST.2016.7483406

Shaowei Liu, Kaijun Ren, Kefeng Deng, Junqiang Song

{"title":"A dynamic resource allocation and task scheduling strategy with uncertain task runtime on IaaS clouds","authors":"Shaowei Liu, Kaijun Ren, Kefeng Deng, Junqiang Song","doi":"10.1109/ICIST.2016.7483406","DOIUrl":"https://doi.org/10.1109/ICIST.2016.7483406","url":null,"abstract":"Performing scientific workflows on IaaS cloud may face the problem of uncertain task runtime, meaning that tasks' real execution time are different from their given or evaluated time. So the pre-determined scheduling scheme can not perform as expected, causing that scientific workflows can not be completed within deadline or the total cost is far beyond users' budget. To address this problem, we proposed a new dynamic resource allocation and task scheduling(DRATS) strategy. At build-time, we use Path cut(PC) algorithm to generate a static task-Virtual Machine(VM) mapping scheme, and use task duplication(TD) algorithm to reduce the affect caused by their potential uncertain task runtime; At running time, when any task's executing time is inaccurate, we use least resource appending(LAR) algorithm to re-organize the mapping relationship between successor tasks and VMs, and add new virtual machine as cheap as possible. Experimental results demonstrate that, DRATS strategy can decrease the impact brought by uncertain task runtime, improve the probability of completing scientific workflows on time, and reduce the execution cost of scientific workflows effectively while satisfying the deadline constraint.","PeriodicalId":159643,"journal":{"name":"2016 Sixth International Conference on Information Science and Technology (ICIST)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128006159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Cooperation incentive mechanism for selfish users based on trust degree 基于信任度的自私用户合作激励机制

2016 Sixth International Conference on Information Science and Technology (ICIST) Pub Date : 2016-05-06 DOI: 10.1109/ICIST.2016.7483411

Wen Wang, Kaizhi Huang, Yi Zou

引用次数: 4

Human body shapes modeling and feature points location based on ASM for virtual fitting 基于ASM的人体形状建模与特征点定位

2016 Sixth International Conference on Information Science and Technology (ICIST) Pub Date : 2016-05-06 DOI: 10.1109/ICIST.2016.7483461

Zhu Xin-juan, Xiong Xiao-ya

引用次数: 8

A new key-aggregate encryption scheme with chosen ciphertext security 一种新的具有选择密文安全性的密钥聚合加密方案

2016 Sixth International Conference on Information Science and Technology (ICIST) Pub Date : 2016-05-06 DOI: 10.1109/ICIST.2016.7483415

Caihui Lan, Haifeng Li, Caifen Wang

引用次数: 2

Network traffic and user behavior analysis of mobile reading applications 移动阅读应用的网络流量与用户行为分析

2016 Sixth International Conference on Information Science and Technology (ICIST) Pub Date : 2016-05-06 DOI: 10.1109/ICIST.2016.7483400

Yue Chang, Fang Liu

引用次数: 4

Evaluation index system of international talents with regional features in hospitality industry 酒店行业具有区域特色的国际人才评价指标体系

2016 Sixth International Conference on Information Science and Technology (ICIST) Pub Date : 2016-05-06 DOI: 10.1109/ICIST.2016.7483402

Yanli Bao, Hefeng Hua

引用次数: 0

Model predictive control for dynamic positioning system of ships with unknown time-varying disturbances and actuator constraint 具有未知时变扰动和作动器约束的船舶动态定位系统模型预测控制

2016 Sixth International Conference on Information Science and Technology (ICIST) Pub Date : 2016-05-06 DOI: 10.1109/ICIST.2016.7483430

Guibing Zhu, Jia-lu Du, Yongchao Liu

引用次数: 1

Robust adaptive neural network control of a class of perturbed uncertain pure-feedback nonlinear systems with dead-zone input 一类具有死区输入的扰动不确定纯反馈非线性系统的鲁棒自适应神经网络控制

2016 Sixth International Conference on Information Science and Technology (ICIST) Pub Date : 2016-05-06 DOI: 10.1109/ICIST.2016.7483423

Gang Sun, Mingxin Wang, Shuangwu Wu

引用次数: 0

Real-time video copy detection based on Hadoop 基于Hadoop的实时视频拷贝检测

2016 Sixth International Conference on Information Science and Technology (ICIST) Pub Date : 2016-05-06 DOI: 10.1109/ICIST.2016.7483464

Jing Li, Xuquan Lian, Qiang Wu, Jiande Sun

{"title":"Real-time video copy detection based on Hadoop","authors":"Jing Li, Xuquan Lian, Qiang Wu, Jiande Sun","doi":"10.1109/ICIST.2016.7483464","DOIUrl":"https://doi.org/10.1109/ICIST.2016.7483464","url":null,"abstract":"With the development of multimedia technology and Internet, the amount of videos in the Internet is increasing quickly. Among the large amount of videos in the Internet, a considerable number of them are copies of original videos, which are simply revised versions of the original ones. The purpose of video copy detection technology is to detect copy videos, which has important applications in video tracking, video content retrieval, video copyright protection and other aspects. The current problem is that real-time video copy detection is often difficult to achieve due to the large amount of video data. Hadoop is a distributed computing platform which is designed for deployment in inexpensive hardware and suitable for those applications with a large data set. All of these characteristics could just meet the requirements of real-time video copy detection technology. In this paper, an attempt is done to develop a real-time video copy detection system based on Hadoop platform, and two video copy detection algorithms are implemented on Hadoop platform, which are the method based on brightness sequence and the method based on TIRI-DCT respectively, and their performances are compared. Experiments show that the use of Hadoop platform can significantly improve the efficiency of video copy detection, which has important practical significance for video tracking and real-time video content retrieval application.","PeriodicalId":159643,"journal":{"name":"2016 Sixth International Conference on Information Science and Technology (ICIST)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124905846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

A fatal drawback of the widely used Granger causality in neuroscience 在神经科学中广泛使用的格兰杰因果关系的一个致命缺陷

2016 Sixth International Conference on Information Science and Technology (ICIST) Pub Date : 2016-05-06 DOI: 10.1109/ICIST.2016.7483386

Xueqing Hu, Sanqing Hu, Jianhai Zhang, Wanzeng Kong, Yu Cao

{"title":"A fatal drawback of the widely used Granger causality in neuroscience","authors":"Xueqing Hu, Sanqing Hu, Jianhai Zhang, Wanzeng Kong, Yu Cao","doi":"10.1109/ICIST.2016.7483386","DOIUrl":"https://doi.org/10.1109/ICIST.2016.7483386","url":null,"abstract":"In 2011 [1] we proposed new causality (NC) method and demonstrated that NC method much better reveals true causality of time-invariant bivariate autoregressive model than the popular Granger causality (GC) method by several examples. In this paper, we provide more evidence that GC cannot reveal true causality, and point out the core difference between GC and NC mathematically. Given a jointly regression model in GC method one has to estimate the autoregressive model. By an illustrative example on one hand we give the exact formula for GC, which is only related to some coefficients and has nothing to do with the other coefficients, and thus GC cannot reveal true causality at all since true causality underlying the joint regression model with different time-invariant coefficients surely be different. On the other hand, we theoretically show a fatal drawback that the estimation of the autoregressive model is equivalent to taking a series of backward recursive operations, which are infeasible however for many irreversible chemical reaction models. Thus, GC method cannot be applied at all. In this case GC value by forcibly estimating the auto regressive model (i.e., taking a series of backward recursive operations) inevitably cannot reveal true causality.","PeriodicalId":159643,"journal":{"name":"2016 Sixth International Conference on Information Science and Technology (ICIST)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121927136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1