Large Data Migration within cloud Enviornment using Compression and Encryption Technique

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Volume 2, Issue 2, 2015

89 Available online at www.ijiere.com

International Journal of Innovative and Emerging

Research in Engineering

e-ISSN: 2394 - 3343 p-ISSN: 2394 - 5494

Large Data migration within Cloud Environments using

Compression and Encryption Technique

Rajeshri Vaidya

a

_{, and Prof. Sumedh Pundkar}

b

a _{Mtech Student, UMIT SNDT College, Mumbai ,India} b_{Assistant Professor, UMIT SNDT College, Mumbai, India}

ABSTRACT:

Cloud computing is rapidly growing computation paradigm. Cloud Computing combines all the IT capabilities which can be used together, easily implemented and managed with minimum efforts. Lots of organizations are taking advantages of cloud capabilities such as online services, dynamic resource allocation etc. Basically, multinational organizations have huge amount of data, so migration on commercial cloud platforms will charge high by their respective cloud service providers. So for such organizations it’s better to use open source cloud platforms. The main aim of this work is to improve performance by reducing the time complexity, which will move data from one cloud storage to other cloud storage with minimum time. Therefore, this paper, propose migration strategy using compression of efficient data movement within different cloud storage environments with encryption for security & also this paper deals with comparative study on different open source cloud platform, which will help to analyze and suggest one of their cost effective solution.

Keywords: Amazon Web Services (AWS), Compression, Migration, open source cloud platforms, private cloud.

I. INTRODUCTION

Cloud computing is a software platform that provides computing services with the help of internet. It allows users to make use of the software and hardware which is managed by the parties at remote locations like online store, social networking, webmail, e-commerce applications etc. With the help of a cloud computing model it provides access to information and computer resources from anywhere in the world with network and internet connection. It provides shared pool of resources that includes data storage space, networking facilities, computing processing power of specialized and user applications.

There are three cloud computing models are Software as a Service (SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS).There are three main characteristics of cloud computing service which differs it from traditional hosting service are:-

1) On demand availability

2) Rapid elasticity (pay per use) for users 3) Resource pooling.

Cloud computing has three categories under which they can be deployed: private, public or Hybrid.

1) Private cloud: In such cloud infrastructure the cloud computing platform is operated solely for a specific organization under the control of IT department and is managed by the organization behind the organizational firewall. Private cloud offers the same features as public cloud and eliminates the issues related to control, data, security etc. 2) Public cloud: In such cloud infrastructure the cloud service provider charges for their services from the organization. Amazon Web Services (AWS) are the largest public cloud provider.

3) Hybrid cloud: It is a cloud infrastructure which combines both private and public cloud infrastructures together.[7] In this paper section 2 discusses existing study on data migration in cloud. Section3 discusses about the emerging of open source cloud platforms and comparative study on them. Section 5 is about proposed design for data migration in cloud and last concludes the discussion.

II. LITERATURE REVIEW

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90 migration which includes cleaning and optimizing code, handling errors in stored procedures. Farah et. al.[4] propose another cloud service called Database as a Service (DaaS) and Requirements for DaaS are divide into two domains. The first is user centric requirements which require less governance and management and hence it can provide high performance in terms of throughput, scalability, latency availability and reliability. The second one is provider centric which focuses on workload handling, effective resource allocation, data security and cost benefit analysis. The paper also discusses about a cloud system which stored data on multiple machines which introduce redundancy using relational cloud architecture.

There are two types of migration can be carried out on large amount of data in one shot or continuously. The first is applicable when only the schema is migrated to new DBMS and also relatively small amount of simple of data can be transfer. However, the one shot approach with large system leads to unacceptable long downtime. Vijay el [1] proposed the seven step iterative model of migration strategy for migrating large amount data into the cloud. Model suggests migrating data and application into parts. First a little amount of data will be migrated along with the applications; it is then tested and if satisfactory results were found more data will be migrated. This approach is iterative and continuous till the data is migrated. Gopi et. al. [2] discuss about the Auto script generation for mapping data elements to cloud entities for on demand bulk data transfer. The system can host an application on Microsoft cloud Azure platform and can be used to enable bulk data transfer on cloud. The paper also discusses advanced distributed query processing engine that utilizes elastic grid infrastructure to provide scalable on-demand data aggregation. Almost all cloud storage provides facility to migrate the data between similar cloud storage. For example, to transfer the data from one SQL Azure database to another SQL Azure database, you can use SQL Azure database copy and SQL Azure Data Sync Commands [6]. Nasuni takes the three clouds Amazon S3, Microsoft Windows Azure and Rackspace and transfer the data between them. It estimates that 40 hours needed to move the 12TB data from S3 to Azure, but takes four hours to move 12 TB of data from one Amazon S3 to another. Reason behind this is data format [3]. Many organizations provide theses data migration facility in own same cloud storage For example, to migrate data from one SQL Azure database to another SQL Azure database, you can use SQL Azure database copy and SQL Azure Data Sync Commands. Still cloud interoperability is a big issue as no one; neither Microsoft nor Amazon supports the Unified Cloud Interface (UCI) Project proposed by the Cloud Computing Interoperability Forum (CCIF) [6].

There are many applications such as search engine clusters, video-on-demand servers, sensor networks and grid computing whose data stored on storage server. A storage server typically consists of set of storage devices, which typically connected using a dedicated high-speed network. It is critical to migrate data to their target disks as quickly as possible to obtain the optimal performance of the system. Many organizations used external hardware to transfer the data which have many side effects like data security, its integrity etc. So online system needed to migrate the data. Hence organizations are migrating their data to cloud to reap cloud benefits. As most of commercial/proprietary cloud providers like Amazon (AWS) etc follows the policy of leveraging the cloud services to the users on the pay-as-you-go basis.

Companies keep on growing services and their data is also goes on increasing, migrating this data on to the proprietary cloud platforms will charge lot of money. Thus a cost will became issue for ever growing large companies that are providing their applications, data as a service on cloud. For such large companies with increasing data Open-source cloud platforms becomes an cost effective solutions. Instead of paying lot of cost to the proprietary cloud platforms, it is better to divert and have their private cloud using open source cloud platforms.

III. COMPARATIVE STUDY ON OPEN SOURCE CLOUD PLATFORMS

As name suggest, Open source Cloud Platform are open, freely available cloud platforms. They can be configured and codes can be customized as per the user needs. As they are open source the level of security is high which is under the control of users and much more trust worthy. Companies with open source cloud platforms have their data always available and can be accessible from anywhere at any time. Adding it, the company will use all the cloud capabilities and benefits within minimum cost with more security and trust. In this section comparative survey study on different Open source cloud platforms is made based on their different architecture and their characteristics.

Table1. Comparison between different open source cloud platform

Parameters Open Nebula Eucalyptus Cloud Stack OpenStack

Architecture wise

Follows classical cluster like architecture with a front end and a set of cluster nodes to run the virtual machines (VMs).

Consist of 5 components Cloud Controller, walrus, cluster controller, storage controller, VM Broker, Node Controller

Has monolithic architecture designed for centralized

management and massively

scalability

Fragmented and distributed architecture have 3 core software projects are:-OpenStack Compute, OpenStack object storage, OpenStack image service

Written in C++,Ruby ,Java Eucalyptus has 5 components where Cluster and Node written in C, while cloud,

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91 storage and VMware are

written in Java Relation with

Amazon

have Amazon Web service API Ecosystem

have native OpenStack Restful APIs or OpenStack APIs Cloud

Implementatio n

Used for develop to develop private, public and hybrid cloud

Used for developing private cloud

Used for

developing private as well as public cloud

Used for developing private as well as public cloud

Hypervisor on which VMs run

Xen, VMware and KVM

Xen and KVM Citrix XenServer, Oracle,

VM,Vmware,KVM ,vSphere

KVM, Xen ,LXC, QEMU,UML,Hyper-V

Databases they support

Supports SQLite in some version while now it uses MySQL as a backend.

PostgreSQL to sote their metadata and information

Supports mainly MySQL

Supports

SQLite3,MYSQL and PostgreSQL

VM migration from one resource to another resource

Supports VM migration

They do not support VM migration

Supports VM migration

Supports VM

migration

Source code licensed under

Fully open source under

Apache v2.0

Fully open source under GPL v3.0 supports.

Apache v2.0

IV. PROBLEM STATEMENT

From the above studied papers, we identified some of the problems such as system works on small amount of data such (KB or MB) but when the data varies with the volume (Gigabytes) the system fails to meet the quality and the performance suffers with downtime.

Most of the systems do the migration. But while transferring the data, security strives and hence data loses its integrity and consistency. Most of the systems are costlier because they are provided by paid services. Thus there is a need of designing a system to migrate large amount of data with integrity, consistency and security also the solution must be cost effective so that it is easily adaptable by small and medium scale organizations.

V. PROPOSED SOLUTION

For the reason as presented in above paragraph, we are proposing the solution of large data migration strategy with divide and squeeze method for better performance and also it achieving security, by performing re- encryption on data blocks so that the data will be more secured while transmitting on network.

In the proposed solution, I have observed the two different cloud storages environment. Firstly, where time is consumed less when data is transferred from one cloud to another with the same service provider whereas in the second process, time taken for data to transfer from one cloud to another with different service providers is more. This happens due to their different data transfer mechanisms and formats.

Data transfer between same cloud storage may be small or large in size. But transferring it between different cloud storages requires a lot of efforts. So, it needs standard format or middleware or application for data migration that can universally accepted while migrating between different cloud providers.

Fig1. Shows the conceptual overview of our Data Migration proposed system. It illustrates user migrates his data from one cloud storage system to another user of other cloud storage system. The storages are located within different clouds and they are connected through transmission link in network on which migration takes place.

Figure 1. Conceptual overview of data migration system

Cloud 1 _{Cloud 2}

User 1 User 2

Data Migration

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92 Fig 2 shows the flow of proposed system, here we setup private cloud in that we consider two cloud storages server acting as different cloud storage environments; users are able to input their large size files to the storage. Once inputted, the file get splits into small blocks and encrypted using AES encryption algorithm and then RSA after calculating message digest of the original message .The file is squeezed using compression algorithm then the file is send for transmission to cloud storage. After the transmission, the file is received at the other end and the reversed procedure of uploading is performed and file is downloaded by another user. Calculating the message digest and comparing it with original at the other end providing the validation to the received message which ultimately checking integrity and consistency of data. Instead of migrating this bulk data in one stroke, we divided it into fixed size blocks and squeezed them using compression technique so that the latency it takes for transferring large data gets optimized and migrated quickly and efficiently with security. The tight integration of encryption and forwarding makes the system to work efficiently.

Data transmission

Figure 2. Shows block diagram of the data migration system

VI. CONCLUSIONS

In this paper, we analyze the existing data migration an approach made by different authors and addresses the various problems for data migration between different cloud storages is a challenging task. Considering this problem, tried to proposed efficient way by using divide and squeeze method to improve the performance and security. According to short comparative study above made, for large data migration it is best to migrate it though the use of open source cloud platforms and among them OpenStack can be the best cost effective solution rather than spending huge amount on paid cloud providers like Amazon (AWS).

ACKNOWLEDGMENT

Author is very grateful to UMIT College, SNDT University Mumbai, Maharashtra, and Mr. Sumedh Pundkar Assistant Professor (UMIT College, SNDT University) for providing resources and environment to carry out this research.

REFERENCES

[1] Vijay Aggarwal, Mohit Mathur, Nitin Saraswat Dept. of IT, Jagan Institute of Management Studies, Delhi, India “Comprehensive Cloud Incremental Data-Application Migration – A Proposed Model for Cloud Migration” International Journal of Computer Applications in Engineering Sciences [vol III,issue I,March 2013].

[2] B. Gopi Krishna, E.Vengal Reddy, K.Jagadamba,Srikumar Krishnamurthy, P. Radha Krishn*a, “A Unified and Scalable Data Migration Service for the Cloud Environments”, 15th International Conference on Management of Data,Mysore, India,December 9-12, 2009.

[3] “Bulk Data Migration in the Cloud, White Paper,” Nasuni.

[4] Farah Habib Chanchary, Samiul Islam, “Data Migration: Connecting Databases in the Cloud”,ICCIT 2012. [5] Prashant Pant, Sanjeev Thakur, ” Data Migration Across The Clouds”, International Journal of Soft Computing

and Engineering (IJSCE), May 2013, ISSN: 2231-2307.

User2 Data Upload

Data Merging Data Splitting

Decryption Encryption

Data Decompression

User1

Storage 1 _{Storage 2}

Data Compression

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93 [6] Parvinder Kaur ,Manish Mahajan “ Connecting Heterogeneous Cloud Storages through Windows

Communication Foundation” International Journal of Modern Computer Science (IJMCS) ISSN: 2320-7868 (Online) Volume 2, Issue 5, October, 2014

[7] Sidharth Sachdev , Amit Mahajan “ Deployment of Private Cloud using Open Stack: An pen Source Cloud Computing Solution for Small and Mid-sized Organizations” International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 10, October 2013 ISSN: 2277 128X

[8] Rakesh Kumar1, Neha Gupta2, Shilpi Charu3, Kanishk Jain4, Sunil Kumar Jangir5 “ Open Source Solution for Cloud Computing Platform Using OpenStack” International Journal of Computer Science and Mobile Computing Vol.3 Issue.5.

[9] Oracles, “Successful Data Migration”, White Paper,October 2011.