2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)最新文献_第2页

Network Telemetry Anonymization for Cloud Based Security Analysis - Best Practices 基于云的安全分析的网络遥测匿名化-最佳实践

2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2014-10-01 DOI: 10.1109/CCEM.2014.7015493

Sashank Dara

引用次数: 3

Client Requirement Modeling Using Resource Broker Architecture in Cloud Computing Environment 云计算环境下基于资源代理体系结构的客户端需求建模

2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2014-10-01 DOI: 10.1109/CCEM.2014.7015484

Chetan Awasthi, P. Kanungo

引用次数: 3

A Cloud Computing Service Level Agreement Framework with Negotiation and Secure Monitoring 具有协商和安全监控的云计算服务水平协议框架

2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2014-10-01 DOI: 10.1109/CCEM.2014.7015474

V. Binu, N. D. Gangadhar

引用次数: 7

MultiPaaS - PaaS on Multiple Clouds MultiPaaS——多云上的PaaS

2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2014-10-01 DOI: 10.1109/CCEM.2014.7015492

S. Sahni, Vasudeva Varma

引用次数: 5

DBMLE: Distance-Based Multi-Level Elliptic Routing Protocol for Ad Hoc Networks 用于自组织网络的基于距离的多级椭圆路由协议

2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2014-10-01 DOI: 10.1109/CCEM.2014.7015490

K. Dsouza, M. Sujatha

{"title":"DBMLE: Distance-Based Multi-Level Elliptic Routing Protocol for Ad Hoc Networks","authors":"K. Dsouza, M. Sujatha","doi":"10.1109/CCEM.2014.7015490","DOIUrl":"https://doi.org/10.1109/CCEM.2014.7015490","url":null,"abstract":"A critical challenge in the design of Ad Hoc networks is the development of an efficient routing protocol which provides high quality communication. The node's in MANET have limited communication resources such as bandwidth, buffer space, battery power etc. The resource constraints in MANET require the traffic to be properly distributed among the mobile host. The distance based multi-level elliptic routing protocol proposed in this paper is an efficient method of selecting the node as a next hop node, while communicating in a mobile Ad hoc network. The proposed method selects the node's which are orthogonal to the centroid. Here the node uses the position information to identify the nodes which lie in orthogonal direction. The node obtains location information from the GPS location service. The GPS location service fails to give accurate position information in constrained environments such as node not exposed to GPS satellites. In these scenarios, the node fails to get the location information. The error caused leads to locating the node to improper position. Therefore DBMLE protocol used in this paper uses communication signal strength along with the GPS information. The nodes keep track of neighbor node's position, velocity and signal strength information.","PeriodicalId":143177,"journal":{"name":"2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129324854","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: 0

An Enhanced Cloud Computing Model for Patient Record Management in South Africa 南非患者记录管理的增强型云计算模型

2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2014-10-01 DOI: 10.1109/CCEM.2014.7015480

R. Millham

引用次数: 1

Big Data Infrastructure for Aviation Data Analytics 航空数据分析的大数据基础设施

2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2014-10-01 DOI: 10.1109/CCEM.2014.7015483

A. Murugan, D. Mylaraswamy, Brian Xu, P. Dietrich

引用次数: 10

A Cloud-Based Collaborative Platform Supporting Serviced-Enhanced Products for Emerging Markets 基于云的协作平台，支持面向新兴市场的服务增强产品

2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2014-10-01 DOI: 10.1109/CCEM.2014.7015475

Bholanathsingh Surajbali, Adrian Juan-Verdejo, S. Alexakis, H. Bar, M. Bauer

{"title":"A Cloud-Based Collaborative Platform Supporting Serviced-Enhanced Products for Emerging Markets","authors":"Bholanathsingh Surajbali, Adrian Juan-Verdejo, S. Alexakis, H. Bar, M. Bauer","doi":"10.1109/CCEM.2014.7015475","DOIUrl":"https://doi.org/10.1109/CCEM.2014.7015475","url":null,"abstract":"Collaboration through sharing competencies and resources has been a key approach to both creating new competitive environments, as well as achieving the needed agility to rapidly answer to emerging market demands. Establishing proper collaborative networks for service-enhanced products is challenging given the wide diversity of business operations and involved resources. The creation of software solutions to support such collaboration is an effort-intensive task, especially when these solutions are designed to run in the cloud and to be highly customizable to different end-user scenarios. In this paper we describe how a cloud- based platform can support the creation of software solutions for the collaborative development and operation of highly customized and service-enhanced products. The platform has been designed based on numerous key requirements that have been generated from the analysis of different business scenarios from various use cases and domains, as well as general key requirements a cloud-based platform should provide to support collaboration among organizations.","PeriodicalId":143177,"journal":{"name":"2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125006271","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: 5

A Secure Mutual Authentication Protocol for Cloud Computing Using Secret Sharing and Steganography 基于秘密共享和隐写的云计算安全互鉴协议

2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2014-10-01 DOI: 10.1109/CCEM.2014.7015478

C. Vorugunti, M. Sarvabhatla, G. Murugan

{"title":"A Secure Mutual Authentication Protocol for Cloud Computing Using Secret Sharing and Steganography","authors":"C. Vorugunti, M. Sarvabhatla, G. Murugan","doi":"10.1109/CCEM.2014.7015478","DOIUrl":"https://doi.org/10.1109/CCEM.2014.7015478","url":null,"abstract":"Cloud computing is a collection of virtually massive distributed large scale computers to handle enormous enterprise computing, hardware, storage needs. An exponential advancement of communication and information technologies results in substantial traffic for accessing of cloud resources wired and mobile, through various communication devices like desktop, laptop, tabs, etc. via Internet. Significance of enterprise data and increased access rates from low-resource terminal devices demands for reliable and low cost authentication techniques. Lots of researchers have proposed authentication schemes based on password, biometric, steganography etc. with varied efficiencies. In 2014, Nimmy et al proposed a steganography based mutual authentication protocol for cloud computing and claimed that their scheme resists major cryptographic attacks. Unfortunately, in this paper we will show that Nimmy et al is vulnerable to offline password guessing attack and Denial of Service attack. As a part of our contribution, we propose a low cost steganography based authentication scheme which is strongly secure and best suited for asymmetric cloud computing environment.","PeriodicalId":143177,"journal":{"name":"2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134128174","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: 8

Autonomic Characterization of Workloads Using Workload Fingerprinting 利用工作量指纹识别技术自主确定工作量特征

2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) Pub Date : 2014-10-01 DOI: 10.1109/CCEM.2014.7015482

R. Khanna, M. Ganguli, Ananth S. Narayan, R. Abhiram, P. Gupta

{"title":"Autonomic Characterization of Workloads Using Workload Fingerprinting","authors":"R. Khanna, M. Ganguli, Ananth S. Narayan, R. Abhiram, P. Gupta","doi":"10.1109/CCEM.2014.7015482","DOIUrl":"https://doi.org/10.1109/CCEM.2014.7015482","url":null,"abstract":"In a cloud service management environment, service level agreements (SLA) define the expectation of quality (Quality-of-Service) for managing performance loss in a given service-hosting environment comprising of a pool of compute resources. Typically, complexity of resource inter-dependencies in a server system often results to sub-optimal behaviors leading to performance loss. A well behaved model can anticipate the demand patterns and proactively react to the dynamic stresses in a timely and well optimized manner. Dynamic characterization methods can synthesize self-correcting workload fingerprint code-book that facilitates phase prediction to achieve continuous tuning through proactive workload-allocation and load-balancing. In this paper we introduce the methodology that facilitates the coordinated tuning of the system resources through phase-assisted dynamic characterization. We describe the method to develop a multi-variate phase model by learning and classifying the run-time behavior of workloads. We demonstrate the workload phase forecasting method using phase extraction using a combination of machine learning approach. Results show the new model is about 98% accurate in phase identification and 97.15% accurate in forecasting the compute demands.","PeriodicalId":143177,"journal":{"name":"2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127246368","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: 6