2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)最新文献

XHAMI -- Extended HDFS and MapReduce Interface for Image Processing Applications XHAMI——用于图像处理应用的扩展HDFS和MapReduce接口

2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2015-11-01 DOI: 10.1109/CCEM.2015.30

Raghavendra Kune, P. Konugurthi, A. Agarwal, Raghavendra Rao Chillarige, R. Buyya

{"title":"XHAMI -- Extended HDFS and MapReduce Interface for Image Processing Applications","authors":"Raghavendra Kune, P. Konugurthi, A. Agarwal, Raghavendra Rao Chillarige, R. Buyya","doi":"10.1109/CCEM.2015.30","DOIUrl":"https://doi.org/10.1109/CCEM.2015.30","url":null,"abstract":"Hadoop Distributed File System (HDFS) and MapReduce model have become de facto standard for large scale data organization and analysis. Existing model of data organization and processing in Hadoop using HDFS and MapReduce are ideally tailored for search and data parallel applications, for which there is no data dependency with neighboring/adjacent data. Many scientific applications such as image mining, data mining, knowledge data mining, satellite image processing etc., are dependent on adjacent data for processing and analysis. In this paper, we discuss the requirements of the overlapped data organization and propose XHAMI as a two phase extensions to HDFS and MapReduce programming model to address such requirements. We present the APIs and discuss their implementation specific to Image Processing (IP) domain in detail, followed by sample case studies of image processing functions along with the results. XHAMI though has little overheads in data storage and input/output operations, but greatly improves the system performance and simplifies the application development process. The proposed system works without any changes for the existing MapReduce models with zero overheads, and can be used for many domain specific applications where there is a requirement of overlapped data.","PeriodicalId":339923,"journal":{"name":"2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)","volume":"38 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123670781","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: 7

Ensuring Privacy and Data Freshness for Public Auditing of Shared Data in Cloud 云共享数据公共审计保障隐私和数据新鲜度

2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2015-11-01 DOI: 10.1109/CCEM.2015.36

T. Trueman, P. Narayanasamy

{"title":"Ensuring Privacy and Data Freshness for Public Auditing of Shared Data in Cloud","authors":"T. Trueman, P. Narayanasamy","doi":"10.1109/CCEM.2015.36","DOIUrl":"https://doi.org/10.1109/CCEM.2015.36","url":null,"abstract":"The cloud offers storage services where users can store a huge amount of data. Users are given flexible amounts of storage space along with the certain number of processors and primary memory where they can perform the required operations. Users can also share their data with other users whom they trust. This sharing of data is usually done by forming groups of users who share a common interest. Data shared by any user (known as the data owner) can be accessed by other users in the group, in which the data owner is a part of. The data which is stored in the cloud needs to be protected from theft, misuse, eavesdropping, etc. Since the user may store critical and sensitive data in the cloud, it is the responsibility of the cloud service provider (CSP) to ensure that the data is secure and also to preserve the identity (Privacy) of the users who share the data in the group. Users in a group can also make changes to the data which is shared in the group. Moreover when a user accesses the data, most up-to-date (fresh) data should be made available so that valid inferences and operation can be done. For this purpose in this paper, we propose a novel method for ensuring privacy and data freshness of shared data in cloud using Homomorphic authenticable ring signature (HARS) scheme to preserve the user privacy and Overlay tree algorithm is used for ensuring that users the data with required level of freshness. Also Third Party Auditor (TPA) audits the data stored in the cloud. He should be able to verify the trustworthiness of the CSP without disclosing the identity of the users in the group.","PeriodicalId":339923,"journal":{"name":"2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)","volume":"165 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129862648","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: 4

A Novel Data Mining Approach for Multi Variant Text Classification 一种新的多变体文本分类数据挖掘方法

2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2015-11-01 DOI: 10.1109/CCEM.2015.11

K. Dsouza, Zaheed Ahmed Ansari

引用次数: 5

In-Memory Database Optimization Using Statistical Estimation 使用统计估计的内存数据库优化

2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2015-11-01 DOI: 10.1109/CCEM.2015.19

Sudhir Verma, Vidur S. Bhatnagar

引用次数: 0

Standards Based Integration of Advanced Key Management Capabilities with Openstack 基于标准的高级密钥管理功能与Openstack的集成

2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2015-11-01 DOI: 10.1109/CCEM.2015.27

D. Sitaram, Sudheendra Harwalkar, Utkarsh Simha, Sreekanth Iyer, S. Jha

引用次数: 6

Energy Efficient Data Center in Cloud Computing 云计算中的节能数据中心

2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2015-11-01 DOI: 10.1109/CCEM.2015.14

V. Yadav, Pooja Malik, Adarsh Kumar, G. Sahoo

{"title":"Energy Efficient Data Center in Cloud Computing","authors":"V. Yadav, Pooja Malik, Adarsh Kumar, G. Sahoo","doi":"10.1109/CCEM.2015.14","DOIUrl":"https://doi.org/10.1109/CCEM.2015.14","url":null,"abstract":"In fact, Gartner projected global revenue for cloud computing to reach almost $150 billion by 2014. However, the 2011 market is already approximately $68 billion globally. With increase in web technologies and internet, a proportional increase in cloud computing technologies has been cited. Cloud computing has been emerging as a flexible and powerful computational architecture to offer ubiquitous services to users. A variety of hardware and software resources are integrated together as a resource pool, the software is no longer resided in a single hardware environment, it is utilized according to the schedule of the resource pool for optimized resource utilization. The optimization of energy consumption in the cloud computing environment is the question how to use various energy conservation strategies to efficiently allocate resources. The need of different resources in cloud environment is unpredictable. It is observed that load management in cloud is utmost needed in order to provide QoS (Quality of Service). The jobs on over-loaded physical machine are shifted to under-loaded physical machine and turning the idle machine off, in order to provide green cloud. For energy optimization, DVFS and Power-Nap are good strategies. As good amount of this energy is wasted in idle systems: in typical deployments, server utilization is below 30%, but idle servers still consume 60% of their peak power. In this paper, we have proposed an algorithm for energy optimization having the constraint QoS and SLA.","PeriodicalId":339923,"journal":{"name":"2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129736049","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: 4

Towards Cloud-Based Decentralized Storage for Internet of Things Data 面向物联网数据的云分散存储

2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2015-11-01 DOI: 10.1109/CCEM.2015.9

N. Narendra, Koundinya Koorapati, Vijayalakshmi Ujja

{"title":"Towards Cloud-Based Decentralized Storage for Internet of Things Data","authors":"N. Narendra, Koundinya Koorapati, Vijayalakshmi Ujja","doi":"10.1109/CCEM.2015.9","DOIUrl":"https://doi.org/10.1109/CCEM.2015.9","url":null,"abstract":"The Internet of Things (IoT) phenomenon is creating a world of billions of connected devices generating enormous amounts of data. That data needs to be stored efficiently so that it can be retrieved easily on demand and acted upon. Current cloud-based solutions, focusing on centralized data collection and storage, would not be adequate for this task, given the sheer volume of data expected to be generated by IoT devices. Despite this, however, very little work has been reported on cloud-based storage tailored for IoT data. To that end, in this paper, we present a decentralized cloud-based storage solution specifically tailored for IoT data. The salient features of our solution are: usage of object storage (such as Ceph) for software-defined storage, and optimal distribution of data among distributed mini-Clouds, which are mini-data centers. We present approaches for the following: optimal mini-Cloud placement to minimize latency of data collection from IoT devices, and data migration among mini-Clouds with a view towards addressing storage capacity issues while minimizing access latency. Throughout our paper, we illustrate our ideas via a realistic running example in the Smart Cities domain, and present experimental results via a proof of concept prototype.","PeriodicalId":339923,"journal":{"name":"2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116615472","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: 15

End to End Automation on Cloud with Build Pipeline: The Case for DevOps in Insurance Industry, Continuous Integration, Continuous Testing, and Continuous Delivery 基于构建管道的云上端到端自动化:保险行业DevOps案例、持续集成、持续测试和持续交付

2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2015-11-01 DOI: 10.1109/CCEM.2015.29

M. Soni

{"title":"End to End Automation on Cloud with Build Pipeline: The Case for DevOps in Insurance Industry, Continuous Integration, Continuous Testing, and Continuous Delivery","authors":"M. Soni","doi":"10.1109/CCEM.2015.29","DOIUrl":"https://doi.org/10.1109/CCEM.2015.29","url":null,"abstract":"In modern environment, delivering innovative idea in a fast and reliable manner is extremely significant for any organizations. In the existing scenario, Insurance industry need to better respond to dynamic market requirements, faster time to market for new initiatives and services, and support innovative ways of customer interaction. In past few years, the transition to cloud platforms has given benefits such as agility, scalability, and lower capital costs but the application lifecycle management practices are slow with this disruptive change. DevOps culture extends the agile methodology to rapidly create applications and deliver them across environment in automated manner to improve performance and quality assurance. Continuous Integration (CI) and Continuous delivery (CD) has emerged as a boon for traditional application development and release management practices to provide the capability to release quality artifacts continuously to customers with continuously integrated feedback. The objective of the paper is to create a proof of concept for designing an effective framework for continuous integration, continuous testing, and continuous delivery to automate the source code compilation, code analysis, test execution, packaging, infrastructure provisioning, deployment, and notifications using build pipeline concept.","PeriodicalId":339923,"journal":{"name":"2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115758612","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: 77

High Resolution Satellite Image Processing Using Hadoop Framework 基于Hadoop框架的高分辨率卫星图像处理

2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2015-11-01 DOI: 10.1109/CCEM.2015.16

Roshan Rajak, Deepu Raveendran, Maruthi Chandrasekhar Bh, S. Medasani

引用次数: 16

Feasibility Study of Port Scan Detection on Encrypted Data 加密数据端口扫描检测的可行性研究

2015 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2015-11-01 DOI: 10.1109/CCEM.2015.18

P. Chandrashekar, Sashank Dara, V. Muralidhara

引用次数: 1