دانلود پایان نامه انگلیسی: Interface development for Eucalyptus based cloud

Nowadays the use of cloud computing is expanding exponentially. With a very short life has become a technology that will. Moving data and applications to Internet and access to them trough services gives some vantages to organizations. Although today there are still some doubts and reservations towards it.
The final thesis work describes and analizes cloud computing world and specially Eucalyptus, a software platform for the implementation of private cloud computing on clusters. As a practical work, it have been release a desktop client for interact with Eucalyptus that allow users to run and connect to virtual machines inside the system.

1. Introduction ...................................................................................................................... - 5 -
a. Short overview of cloud computing .............................................................................. - 5 -
b. Identify the problem ..................................................................................................... - 7 -
c. Objective of the thesis .................................................................................................. - 8 -
d. Tasks of the thesis ......................................................................................................... - 9 -
2. Cloud computing ............................................................................................................. - 10 -
a. Historical view ............................................................................................................. - 10 -
b. Overview of cloud computing in details ...................................................................... - 12 -
I. Definition ................................................................................................................. - 12 -
II. Architechtures ......................................................................................................... - 14 -
III. Types of clouds .................................................................................................... - 15 -
IV. Positions about cloud computing ........................................................................ - 15 -
V. Technologies related ............................................................................................... - 19 -
VI. Implementations, providers ................................................................................ - 24 -
3. Practical part ................................................................................................................... - 29 -
a. Tasks of the thesis ....................................................................................................... - 29 -
b. Application, Eucalyptus ............................................................................................... - 31 -
c. The application ............................................................................................................ - 42 -
d. Requirements for the cloud service ............................................................................ - 48 -
e. Architecture of cloud service (interface to the Scilab), UML diagrams… .................... - 49 -
Conclusions and suggestions for further works ...................................................................... - 68 -
4. References ....................................................................................................................... - 72 -

چارچوبی برای رده بندی سرویس های محاسبه ابری

 *** مقاله انگلیسی با ترجمه فارسی ***

A framework for ranking of cloud computing services

چارچوبی برای رده بندی سرویس های محاسبه ابری

( رشته کامپیوتر )

10 صفحه انگلیسی با فرمت PDF

34 صفحه ترجمه فارسی با فرمت Word 2007

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چکیده

محاسبه ابری انقلابی را در صنعت فناوری اطلاعات با توانمند ساختن ان ها برای عرضه دسترسی به زیرساخت هایشان و خدمات کاربردی بر مبنای اشتراک ایجاد کرده است. بنابراین، چندین شرکت همانند IBM، مایکروسافت، گوگل، و آمازون شروع به عرضه سرویس های ابری مختلف به مشتریانشان کرده اند. به دلیل تنوع زیاد در سرویس های محاسبه ابری موجود، از دیدگاه مشتری، مشکل شده است تا تصمیم بگیریم که آن ها از چه سرویسی می بایست استفاده کرده و مبنای انتخاب آن ها چه می باشد. در حال حاضر چارچوبی وجود ندارد تا بتواند این امکان را به کاربران بدهد تا به ارزیابی عرضه محاسبات ابری پرداخته و آن ها را بر مبنای توانایی شان برای تامین نیازهای کیفیت خدمات (QoS) رده بندی کنند. در این تحقیق، چارچوب و مکانیسمی را مطرح می کنیم که کیفیت را اندازه گیری کرده و سرویس های محاسبه ابری را اولویت بندی می کند. چنین چارچوبی می تواند تاثیر قابل توجهی را ایجاد کرده و رقابت سالمی را در میان ارائه دهندگان محاسبات ابری برای مد نظر قرار دادن توافقنامه سطح خدمات (SLA) و بهبود کیفیت خدمات شان ایجاد کند. ما عملی بودن چارچوب رده بندی را با استفاده از بررسی موردی نشان می دهیم.

Abstract

Cloud computing is revolutionizing the IT industry by enabling them to offer access to their infrastructure
and application services on a subscription basis. As a result, several enterprises including IBM, Microsoft,
Google, and Amazon have started to offer different Cloud services to their customers. Due to the vast
diversity in the available Cloud services, from the customer’s point of view, it has become difficult to
decide whose services they should use and what is the basis for their selection. Currently, there is no
framework that can allow customers to evaluate Cloud offerings and rank them based on their ability
to meet the user’s Quality of Service (QoS) requirements. In this work, we propose a framework and
a mechanism that measure the quality and prioritize Cloud services. Such a framework can make a
significant impact and will create healthy competition among Cloud providers to satisfy their Service Level
Agreement (SLA) and improve their QoS.Wehave shown the applicability of the ranking framework using
a case study.

Intelligent techniques for secure financial management in cloud computing

Intelligent techniques for secure financial management in cloud computing

ژورنال:Electronic Commerce Research and Applications

سال:November 2015

قیمت اصلی:37.95$

Highlights•

A new intelligent technique for cloud computing information management was defined.

•

A new class of CFMSiC systems (Cognitive Financial Management Systems in the Cloud) dedicated to cloud-based semantic management of financial data was described.

Abstract

This publication presents new classes of financial management systems. These systems will serve as examples of systems for the cognitive analysis of financial data with particular emphasis on analysing financial ratios. Semantic analysis will be an innovative component in financial management systems which will enhance the traditional solutions by adding elements of cognitive data interpretation and analysis. The systems thus built will constitute a class of intelligent management systems. Intelligent financial management systems will also be used to conceal data of a confidential and strategic nature. For this type of solutions, advanced information sharing schemes will be proposed to enable splitting the information among a defined group of secret trustees in an either equal or privileged way. In addition, a scheme for sharing financial data between groups of secret trustees who can jointly reconstruct the shared financial (strategic) information will be proposed. In addition, a new class of financial management systems will be defined which will be optimal for financial data management processes. The new solution will consist of CFMSiC systems (Cognitive Financial Management Systems in the Cloud) dedicated to cloud-based semantic management of financial data.

Motivation of the author’s study and this paper is to propose new aspects of the intelligent techniques dedicated for secure financial management in cloud computing. The most important research question is: which secure techniques are the optimal for secure strategic financial data management? To answer to this question it is important to conduct accurate analysis, which shows the efficiency in guaranteeing the secrecy of cognitive data analysis. Also, is necessary to discuss about the advanced techniques dedicated to secure strategic data in financial management processes. As a results of the author’s research, in this paper will be presented a strategic data sharing protocols in advanced threshold schemes, a sharing data schemes with a division into groups using advanced threshold schemes, and presentation of these solutions in a new class of information systems – in a CFMSiC systems (Cognitive Financial Management Systems in the Cloud) dedicated to managing financial data in the cloud.

KeywordsIntelligent techniques, Financial management, Secure management, Cloud computing

دانلود پایان نامه انگلیسی کارشناسی ارشد کامپیوتر:امنیت محاسبات ابری--حفظ حریم خصوصی با پرس و جو روی داده های عددی رمز شده

در این پایان نامه ، نویسنده در مورد حفظ حریم خصوصی کاربران (Privacy) در سیستم های ابری (Cloud Computing) بحث کرده است. جنبه ای از حریم خصوصی که به آن پرداخته شده است، پرس و جوهای محدوده های (range query) روی داده های عددی رمزگذاری شده می باشد.

این پایان نامه در سال 2011 برای دریافت درجه کارشناسی ارشد از دانشگاه Zhejiang ارائه شده است.

تعداد صفحات: 59

فهرست مطالب:

1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5 Thesis Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2 Related Work 8
2.1 Database Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.2 Keyword Based Search . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.3 Others . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3 Problem Formulation 13
3.1 Range Queries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.3 Our Goal and Condentiality Requirements . . . . . . . . . . . . . . . . . . . 16
3.4 Symbol Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
4 A New Encryption Scheme 19
4.1 Building Blocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.2 Encoding Records and Queries . . . . . . . . . . . . . . . . . . . . . . . . . . 20
4.3 Encrypting Records and Queries . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.3.1 Setup Secret Key . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.3.2 Data Encryption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4.3.3 Query Encryption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.4 Computing the Query . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.5 Decryption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.6 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.6.1 Secret Key Privacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.6.2 Frequency Privacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.6.3 Order Privacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
4.6.4 Additional Analysis and Summarization . . . . . . . . . . . . . . . . . 31
5 Indexing Method 33
6 Experiments 38
6.1 Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
6.1.1 General Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
6.1.2 Specic Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
6.2 Results and Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
6.2.1 Ball Tree Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
6.2.2 Encryption Time and Space Overhead for K . . . . . . . . . . . . . . 42
6.2.3 Query Execution Time . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
7 Conclusion 45
7.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

7.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
Bibliography 47

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Smart monitoring and controlling of Pandemic Influenza A (H1N1) using Social Network Analysis and cloud computing

Smart monitoring and controlling of Pandemic Influenza A (H1N1) using Social Network Analysis and cloud computing

ژورنال:Journal of Computational Science

سال: January 2016

قیمت اصلی:35.95$

Highlights•

An effective cloud computing framework is proposed which predicts H1N1 infected patients and provides preventions to control infection rate.

•

Random decision tree is used to initially assess the infection in any patient depending on his/her symptoms.

•

Social Network Analysis (SNA) is used to present the state of outbreak.

•

Proposed framework is tested on synthetic data generated for two million users.

•

System provided 94% accuracy for classification and around 81% of resources utilization on Amazon EC2 cloud.

Abstract

H1N1 is an infectious virus which, when spread affects a large volume of the population. It is an airborne disease that spreads easily and has a high death rate. Development of healthcare support systems using cloud computing is emerging as an effective solution with the benefits of better quality of service, reduced costs and flexibility. In this paper, an effective cloud computing architecture is proposed which predicts H1N1 infected patients and provides preventions to control infection rate. It consists of four processing components along with secure cloud storage medical database. The random decision tree is used to initially assess the infection in any patient depending on his/her symptoms. Social Network Analysis (SNA) is used to present the state of the outbreak. The proposed architecture is tested on synthetic data generated for two million users. The system provided 94% accuracy for the classification and around 81% of the resource utilization on Amazon EC2 cloud. The key point of the paper is the use of SNA graphs to calculate role of an infected user in spreading the outbreak known as Outbreak Role Index (ORI). It will help government agencies and healthcare departments to present, analyze and prevent outbreak effectively.

KeywordsPandemic Influenza A, H1N1, Bioinformatics, Cloud computing, Swine flu,Social Network Analysis