1) The document discusses quality of service (QoS)-aware data replication for data-intensive applications in cloud computing systems. It aims to minimize data replication cost and number of QoS violated replicas. 2) It presents a mathematical model and algorithm to optimally place QoS-satisfied and QoS-violated data replicas. The algorithm uses minimum-cost maximum flow to obtain the optimal placement. 3) The algorithm takes as input a set of requested nodes and outputs the optimal placement for QoS-satisfied and QoS-violated replicas by modeling the problem as a network flow graph and applying existing polynomial-time algorithms.

1. QoS-Aware Data Replication for
Data-Intensive Applications in Cloud
Computing Systems
Guided by:-
Ms.Shikha Jain
Computer Science &
Engineering
JIIT NOIDA
Submitted By:-
Rahul Garg(10103499)

2. Cloud Computing
• An expression used to describe a variety of computing concepts.
• Involves a large number of computers connected through a real-time
communication network such as the Internet.
• Relies on sharing computing resources rather than
having local servers or personal devices to
handle applications.

3. Why Cloud Computing is
important ?
• In traditional desktop computing we run software in our own PC and data
is stored in there only, hence traditional computing is PC centric.
• Cloud computing is an emerging Paradigm in computer industry where
the computing is moved to a cloud of computers.
• Now documents are stored on a collection of servers accessed via
internet. Hence the cloud computing is document centric.

5. Properties of Cloud Computing
• Powerful : Powerful in the sense that as there is large number of computers ,
thus more computing power and mass data storage possible.
• Task Centric : Cloud computing focus on what one need and how application can
do it for us. Here documents are given more priority than the applications which
create them.
• Flexible : Flexible as the users may be of different varieties and hence it has to
match with their needs.
• Self Healing : Self healing because backups are available for every document in
the cloud. Hence if one document crashes there will be it's duplicate ready to
run.

6. Problem Statement
 In this project , we are focusing on “Quality of Service
Aware Data Replication for Data Intensive Applications
in Cloud Computing” which investigates the QADR
problem for data-intensive applications in cloud
computing systems.
 QADR concerns how to efficiently consider the QoS
requirements of applications in the data replication.
 The main goal of the QADR problem is to minimize the
data replication cost and the number of QoS violated data
replicas.

7.  Data Intensive Applications
 Data-intensive applications are increasingly more demanding in
sophisticated algorithms to store, manage, and interpret data.
 Storage and Security of such large data requires additional
resources and innovative techniques.
Arising Problems

8.  Quality of Service
 Quality of service is the overall performance of
a computer network, particularly the performance seen by the
users of the network
 Quality of service is particularly important for the transport of
traffic with special requirements.
 Quality of service comprises requirements on all the aspects of a
connection, such as service response time, signal-to-noise ratio,
loss, interrupts, frequency response.

9.  Data Replication
 Involves sharing of information so as to ensure
consistency between redundant resources, such
as software or hardware components.
 To improve reliability, fault-tolerance, and accessibility.
 Copies a database and synchronizes a set of replicas
such that changes made to one replica are reflected in
all the others.

10. Mathematical Model
Where ,
• y(ri,qj) is 1 if qj is a QoS violated replica,0 otherwise
• x(ri,qj) is 1 if qj is a qualified node for replication,0 otherwise
• Tstorage(ri,qj) is the total time for replication including Tdisk_access and Tnode_comm

11. Algorithm
The Goal is to minimize the two parameters :
• Total replication cost in a qualified node
• Number of QoS-violated data nodes
Input: A set of requested nodes Sr
Output: Optimal Placement for the QoS-satisfied and QoS-violated data
replicas.
1. Sq NULL
2. for each requested node ri in Sr do
3. Sq
r
i  Find the correspondingly qualified nodes of ri
4. Sq  Sq U Sq
r
i
5. end for
6. Use Sr and Sq to model a network flow graph.

12. 7. Set appropriate (capacity, cost) values on the edges of the edges of the network flow
graph.
8. Apply an existing polynomial-time MCMF algorithm to obtain the MCMF solution of
the network flow diagram.
9. Obtain the optimal placement for the QoS-satisfied data replicas from the MCMF
solution.
10. Sur  NULL and Suq  NULL
11. For each requested node ri in Sr do
12. fleaving  the amount of flow leaving from ri
13. If fleaving < rf then
14. Sur  Sur U ri
15. Sq
r
i  S - Sq
r
i / * the qualified nodes for ri */
16. Suq  Suq U Sq
r
i
17. end if
18. end for
19. Use Sur and Suq to model a new network flow graph.
20. Set appropriate (capacity, cost) values on the edges of the new network flow graph.
21. Apply the MCMF algorithm on the new network flow graph to obtain the MCMF
solution.
22. Follow the MCMF solution to make the optimal placement of the QoS- Violated data
replicas