An Algorithm to synchronize the local database with cloud Database

International Journal of Innovative Research in Advanced Engineering (IJIRAE) ISSN: 2349-2163
Issue 04, Volume 4 (April 2017) www.ijirae.com
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An Algorithm to synchronize the local database with cloud
Database
1
Saurav kumar Jha, 2
Shoney Sebastian.
1
Department of Computer Science, Christ University Bangalore,
2
Department of Computer Science, Christ University, Bangalore,
Manuscript History
Number: IJIRAE/RS/Vol.04/Issue04/APAE10091
Received: 25, March 2017
Final Correction: 11, April 2017
Final Accepted: 11, April 2017
Published: April 2017
Abstract - Since the cloud computing [1] platform is widely accepted by the industry, variety of applications are designed
targeting to a cloud platform. Database as a Service (DaaS) is one of the powerful platform of cloud computing. There
are many research issues in DaaS platform and one among them is the data synchronization issue. There are many
approaches suggested in the literature to synchronise a local database by being in cloud environment. Unfortunately,
very few work only available in the literature to synchronise a cloud database by being in the local database. The aim of
this paper is to provide an algorithm to solve the problem of data synchronization from local database to cloud database.
Keywords: Cloud computing, distributed system, database synchronization, Platform as a Service
I. INTRODUCTION
Cloud computing [14] is getting popular and IT giants such as Google, Amazon, Microsoft, IBM have started their cloud
computing infrastructure. Data synchronization [1, 19] is the technique to maintain consistency among the data from source
located at one place to a target located at another place and vice versa. Window Azure [8] is cloud based services which
offers various platform independent services. With cloud environment you can quickly create database solutions that are
built on the SQL Server (RDBMS) database engine. You can create a new SQL database then configure it later. You can
decide whether to use an existing SQL database server or create a new one when you create your new database you can also
import a saved database from Binary Large Object (BLOB) storage into SQL Database. Once you’ve created your new
database, create new tables, import data, create and stored. Your data is safe on cloud server because it’s stored in one
primary data centre and two replica data centres.
In distributed system design [11],data synchronization is one of the major striking aspect of the distributed system users as
the overall system consist multiple clients and a single server and whatever changes are made in client/server side database
or vice versa should properly synchronized over time in order to maintain data integrity. Synchronization techniques are
applied to synchronize the data between the two systems. In computer science field, synchronization generally refers to the
idea of maintaining data integrity or keeping multiple copies of a data set in coherence with one another. Data
synchronization is usually implemented using process synchronization primitives. Few research works has carried out in
this area and very few algorithms have been developed to synchronize data from local database to cloud based database. In
the proposed work we have suggested an algorithm to synchronize a local data base with a cloud copy and incase the server
is unavailable, the suggested algorithm ensure the synchronization whenever the server reconnect, without any data loss.
Traditional data storage techniques [4, 13] like client-server architecture has many drawbacks such as more infrastructure
cost, high possibility of data loss, less availability and Congestion in network. All these problems are overcome with cloud
storage approach. In this case, data will be stored in the cloud providers space which can be accessed from anywhere in the
world with adequate security provide a kind of comfort to the data users.
A HIERARCHICAL VIEW OF CLOUD COMPUTING
Cloud computing employs a service-driven business model. In other words, hardware and platform-level resources are
provided as services on an on-demand basis. However, in practice, cloud services can be grouped into three categories:
infrastructure as a service (IaaS). Platform as a service (PaaS) and Software as a Service (SaaS).

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Infrastructure as a Service: Built on top of data centers layer, IaaS layer virtualizes computing power, storage and network
connectivity of the data centers, and offers it as provisioned services to consumers. Users can scale up and down these
computing resources on demand dynamically. Typically, multiple tenants coexist on the same infrastructure resources.
Examples of this layer include Amazon EC2, Microsoft Azure Platform. Platform as a Service: PaaS [7, 14], often referred
as cloudware, provides a development platform with a set of services to assist application design, development, testing,
deployment, monitoring, hosting on the cloud. It usually requires no software download or installation, and supports
geographically distributed teams to work on projects collaboratively. Google App Engine, Microsoft Azure, Amazon Map
Reduce/Simple Storage Service are among examples of this layer. Software as a Service: In SaaS [7, 14], Software is
presented to the end users as services on demand, usually in a browser. It saves the users from the troubles of software
deployment and maintenance. The software is often shared by multiple tenants, automatically updated from the clouds, and
no additional license needs to be purchased. Features can be requested on demand, and are rolled out more frequently.
Because of its service characteristics, SaaS can often be easily integrated with othermashup applications. An example of
SaaS is Google Maps, and supports multi-tenancy feature by utilizing single application instance model. The isolation
among tenants is taken care by the underline design. Other services include subscription management, federated ID
management, application firewall, etc.
II. LITERATURE REVIEW
There are some research work found related to my selected area of study. Followings are under here.
In paper [11] C.Dutta et al.; describes synchronization algorithms of mobile database in cloud environment. This paper
suggests SAMD (Synchronization Algorithms based on Message Digest) in order to resolve the problem described in paper
[11]. SAMD resolves synchronization problems using only standard SQL queries as certified by the ISO (International
Organization for Standardization). This is followed by a possible synchronization of any data combination regardless of the
kind of database of server side or mobile database. The SAMD algorithm[11],[21] makes the images at the server-side
database and the mobile database uses message digest tables to compare two images in order to select the rows needed for
synchronization. If the two images are different, the synchronization progresses according to synchronization policy. In
conclusion, the SAMD is effective solution for mobile database synchronization in cloud environment.
In paper [2] S. V. Krishna proposed an algorithm to synchronize the file between user devices and cloud storage when they
are connected to internet. In this project, the user can upload file from mobile or PC to the cloud storage. These uploaded
file will be automatically synchronized to the user’s devices when they are connected to internet. So, user files can be
viewed from anywhere by any device. In the existing system, we need to download files manually. This paradigm provides
the user to synchronize data automatically between devices. As a test case they have implemented this algorithm for
windows platform.
In this paper [15] I. Shabani et al.; presented an algorithm for data synchronization based on Web Services (WS). This
algorithm allows software applications to work well on both configurations "Online" and “Offline”, in the absence of the
network. This algorithm are suitable in a scenario of uncertain supply of electricity, disconnecting the network and for other
reasons which are not under the control of professional staff that manages the performance of running application, has
interruption to the online work. In order to continue working in such conditions, are founded adequate solutions to work in
offline mode and later data synchronization in normal conditions.
In this paper [18] authors (S. G. Zucker and S.Wang,) had explained that Data synchronization is required for supply chain
management in the B2B e-commerce environment. This case study examined the impact of the adoption of data
synchronization on three large consumer product goods organizations. The study identified process and structural
inadequacies that developed as the result of the implementation, as well as how these organizations recognized benefits and
future opportunities after data synchronization adoption. The findings revealed the significance of internal alignment
around data cleansing and accuracy, as well as opportunities for improved external alignment from a systems perspective.
The synergy created between product item management, data synchronization, and internal champions existed at all three
companies. The workflow re-design, process improvements and standards development imposed on these organizations by
the clean data requirement of data synchronization provided the greatest benefits from the data synchronization process.
This paper [20] K.Donkena and S. Gannamani attempt a method to evaluate performance of cloud database and traditional
database in term of response time while retrieving the data. There has been an exponential growth in the size of the
databases in the recent times and the same amount of growth is expected in the future. There has been a firm drop in the
storage cost followed by a rapid increase in the storage capacity. The entry of Cloud in the recent times has changed the
equations. The Performance of the Database plays a vital role in the competition. In this research, an attempt has been made
toevaluate and compares the performance of the traditional database and the Cloud Database.
III. PROPOSED TO WORK
Microsoft window azure cloud platform is based on a unique, unified, and integrated approach, which is used as cloud data
storage. In order to address the problem of data synchronization from local database to cloud database we have used
Microsoft Window Azure as cloud service provider.

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ALGORITHM STEPS ARE UNDER HERE.
A. CONNECT TO SERVER
1. Check the availability of server
2. If not available then
{
Create a server
}
3. Check the availability of database and operational table.
4.If not available then
{
Create database and operational table as well as one temporary table with two column (ID, Timestamp)
}
B. CREATION OF STORED PROCEDURE ()
1. Setup linked server to link between local database server and clod database server.
2. Create a stored procedure using SQL
3. Fetch the latest data from the operational table by joining with temporary table ID and timestamp column.
4. Return the latest un-matched record.
5.Insert latest record to cloud database table.
C. CREATE SQL AGENT
1. Create the SQL server agent.
2. Create a new job set the stored procedure to the job.
3. Schedule the job to run.
IV. EXPERIMENT AND RESULTS
For performing test cases and getting results we have considered Microsoft window azure as cloud service provider and
SQL server as relational database.
Following steps are essential in order to perform test cases.
Log on to manage.windowsazure.com and select SQL database option. Create database and table structure in window
azure. The database and table structure should be the same as local database.
1. Click the New button found on the upper left-hand corner of the Azure portal.
2. Select Databases from the new page, and select SQL Database from the Databases page.
3. Fill out the SQL Database form with the required information upper left-hand corner of the Azure portal
• Database name: mySampleDatabase
• Resource group: myResourceGroup
• Source:Sample (AdventureWorksLT)
4. Click Server to create and configure a new server for your new database. Fill out the new server form specifying
a globally unique server name, provide a name for the Server admin login, and then specify the password of your
choice.
5. Click Apply.
6. Click Create to provision the database. Provisioning takes a few minutes.
7. On the toolbar, click Notifications to monitor the deployment process.
CREATE A SERVER-LEVEL FIREWALL RULE
Follow these steps to create a SQL Database server-level firewall rule for your client's IP address and enable external
connectivity through the SQL Database firewall for your IP address only.
1. Click Set server firewall on the toolbar The Firewall settings page for the SQL Database server opens.
2. Click Add client IP on the toolbar and then click Save. A server-level firewall rule is created for your current IP
address.
After the deployment completes, click SQL databases from the left-hand menu and click your new database, mySample
Database, on the SQL databases page.
After followed above steps, test the connection of window azure database from local SQL server using following
credential.
SERVER NAME, LOGIN AND PASSWORD.
FOLLOW THESE STEPS TO SETUP JOB IN LOCAL DATABASE:
1. Create linked servers on local database to link between local database server and window azure database server.
2. Create a stored procedure on local database then just do a normal select query with a join with temporary table.
3. Fetch the latest data from the operational table by joining with temporary table ID and timestamp column.
4. Within stored procedure write a INSERT statement to insert fetched local data to cloud database.

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Figure 1
5. Expand Sql server agent in SQL database engine.
6. Right-click Jobs, and then click New Job.
7. On the General page, in the Name box, type a name for the job.
8. Clear the Enabled check box if you do not want the job to be run immediately following its creation. For example,
if you want to test a job before it is scheduled to run, disable the job.
9. Then, you can choose which logins you decided to authorize and category also choose what we needed.
10. Click new and give new name, then what type of language is to be selected. I am selecting T-SQL.
11. After selecting this, you have to insert your queries like this or by using open button; you have to browse your stored
procedure.
12. If job is a failure, what's next? You can run another job or quiet the job.
13. Also, you can save that success or failure in a T-SQL format set path for output.
14. After completing all these steps which login to perform this job, so you choose logins.
15. Click ok, and then click on the SCHEDULING tab. Set the one hour interval.
16. Give the name that you already created, time, occurs, time, date for user option.
17. Finally click on OK to finish the configuration.
Note: If any transaction fails during synchronization this SQL agent will send data to cloud database in next time slot.
RESULTS:
CASE1: LOCAL DATABASE TABLE DATA
After invoked Sql agent check window azure database table.
REPEAT THE SAME STEPS AFTER ONE HOUR

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Case 2: Local Database table data
After invoked Sql agent check window azure database table. Updated record is now inserted to cloud database.
CONCLUSION AND FUTURE WORK
The objective of the research is to provide an algorithm to solve the problem that when all clients are reliant on a single
server or local database. Data synchronization between local database and cloud database makes data accessible across the
world but this research has limitation that it will sink data from local database to cloud database at scheduled time. We have
tested these algorithms with SQL server database but this algorithm can be fit to other relational database like Oracle,
PostgreSQL, MySQL etc. In the future, researcher solved the problem of data synchronization from local database to
cloud database at real time. And also researcher will solve the problem of data synchronization between local–non
relational database and cloud non-relational database.
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