Final report on GOING BACK AND FORTH EFFICIENT MULTIDEPLOYMENT AND MULTI SNAPSHOTTING ON CLOUDS.pptx

BY
T.Sai Srinivas
(09781A1240)
S.Praneeth Kumar N.Janardhan B.Venkat Ramana
(09781A1238) (09781A1226) (09781A1203)
UNDERTHE ESTEEMED GUIDANCE OF
Mr. G.N.Vivekanandha M.Tech.,
Assistant Professor of IT Dept.
Going Back and Forth:Efficient Multideployment
and
Multisnapshotting on Clouds
SRI VENKATESWARA COLLEGE OF ENGG & TECHNOLOGY

CONTENTS
 Abstract
 Existing System
 Proposed System
 System requirements
 Modules description
 System Design
 Data dictionary
 Screen Shots
 Testing Strategies
 Conclusion
 References
2

ABSTRACT
Infrastructure as a Service (IaaS) cloud
computing has transform the way we think of acquiring
resources by introducing a simple change: allowing users
to lease computational resources from the cloud
provider’s datacenter for a short time by deploying
virtual machines (VMs) on these resources. This new
model raises new challenges in the design and
development of IaaS middleware. One of those
challenges is the need to deploy a large number
(hundreds or even thousands) of VM instances
simultaneously.
3

Once theVM instances are
deployed, another challenge is to simultaneously take a
snapshot of many images and transfer them to persistent
storage to support management tasks, such as suspend-
resume and migration.
With datacenters growing rapidly and
configurations becoming heterogeneous, it is important to
enable efficient concurrent deployment and snapshotting that
are at the same time hypervisor independent and ensure a
maximum compatibility with different configurations.
4

EXISTING SYSTEM
The huge computational potential offered by large distributed
systems is hindered by poor data sharing scalability.
5

CON’S
• To give an less performance and storage space.
Network traffic consumption is also very high due to
non concentrating on application status.
• It is not possible to build a scalable, high-performance
distributed data-storage service that facilitates data
sharing at large scale.
6

PROPOSED SYSTEM
A DISTRIBUTEDVIRTUAL FILE SYSTEM specifically
optimized for both the multi deployment and multi
snapshotting patterns.
7

PRO’S
 A good balance between performance, storage
space, and network traffic consumption.
 It handles snapshotting transparently and exposes
standalone, raw image files.
8

SYSTEM REQUIREMENTS
 Hardware System Configuration
Processor - Pentium –IV(min)
Speed - 1.1 GHZ(min)
RAM - 512 MB (min)
Hard Disk - 40 GB (min)
Key Board - StandardWindows Keyboard
9

 Software System Configuration
Operating System : WindowsXP
Front End : Java, Swings
Database : MsAccess
Database Connectivity : JDBC
10

MODULES
 APPLICATION ACCESS PATTERN
 APPLICATION STATE MAINTENANCE
 AGGREGATETHE STORAGE AND MIRRORING
 OPTIMIZE MULTISNAPSHOTTING
 ZOOM ON MIRRORING
11

SYSTEM DESIGN --Class diagram
aggregate the storage and
mirroring
sno()
sname()
age()
address()
cell number()
insert()
copy()
search()
update()
Registration
user name()
password()
conform password()
network()
insert into registration
()
cloud infrastructure
aggregate the storage and
mirroring()
optimize multi snapshotting()
zooming and mirroring()
insert into
cloud()
user
optimize multi
snapshotting
sno()
sname()
age()
address()
cell number()
no.of duplicate key()
find()
duplicate()
zooming and mirroring
sno()
sname()
age()
address()
cell number()
server()
vm-server()
12

Usecase diagram
User
create user
login
storage and
mirroring server
cloud infrastructure
insert the data
copy the data search data
update data
optimize multi
snapshotting
create duplicate
key
zooming on
mirroring
13

Sequence diagram
user
cloud
storage and
mirroring server
database
enter the details
to store the cloud
information
server data store
with database
optimize multi
snapshotting
zooming on
mirroring
after to perform
copy,search and
update process
view the data and
to generate
duplicate key
view the data and
to generate
duplicate key
finally data store with database
14

Activity diagram
check
no
yes
cloud
optimize multi
snap shotting
zooming and
mirroring
insert,copy,
search and
update the
data
storage and
mirroring server
User
login
15

Data Dictionary
 User details table:
 UsersTable
17

SCREEN SHOTS – Login Form
18

Cloud infrastructure
21
 IaaS platforms are typically built on top of clusters made out of loosely-
coupled commodity hardware that minimizes per unit cost and favors low
power over maximum speed .
 Disk storage (cheap hard-drives with capacities in the order of several
hundred GB) is attached to each machine, while the machines are
interconnected with standard Ethernet links.
 The machines are configured with proper virtualization technology, in
terms of both hardware and software, such that they are able to host the
VMs.
 In order to provide persistent storage, a dedicated repository is deployed
either as centralized or as distributed storage service running on dedicated
storage nodes.

Application State Maintenance Page
22

Application state maintenance
23
 TheVM deployment is defined at each moment in time by two
main components: the state of each of theVM instances and the
state of the communication channels between them (opened
sockets, in-transit network packets, virtual topology, etc.).
 To saving the application state implies saving both the state of all
VM instances and the state of all active communication channels
among them.
 While several methods have been established in the virtualization
community to capture the state of a runningVM (CPU registers,
RAM, state of devices, etc.), the issue of capturing the global state
of the communication channels is difficult and still an open
problem.

Aggregate the storage and image mirroring page
24

Aggregate the storage&Image mirroring
Aggregate the storage & Image mirroring
25
 In most cloud deployments, the disks locally attached to the compute nodes are
not exploited to their full potential. Most of the time, such disks are used to hold
local copies of the images corresponding to the runningVMs, as well as to
provide temporary storage for them during their execution, which utilizes only a
small fraction of the total disk size.
 A newVM needs to be instantiated; the underlyingVM image is presented to the
hypervisor as a regular file accessible from the local disk. Read and write
accesses to the file, however, are trapped and treated in a special fashion.
 A read that is issued on a fully or partially empty region in the file that has not
been accessed before (by either a previous read or write) results in fetching the
missing content remotely from theVM repository, mirroring it on the local disk
and redirecting the read to the local copy. If the whole region is available locally,
no remote read is performed.Writes, on the other hand, are always performed
locally.

Application access pattern page
26

Application access pattern
27
 AVM typically does not access the whole initial image.
 For example, it may never access some applications and
utilities that are installed by default with the operating
system.
 In order to model this aspect, it is useful to analyze the life-
cycle of aVM instance, it will based onThree phases.
 They are boot, application and shutdown.

Optimize multi snapshotting page
28

Optimize multisnapshotting
29
 Saving a fullVM image for eachVM is not feasible in the
context of multi snapshotting. Since only small parts of the
VMs are modified, this would mean massive unnecessary
duplication of data, leading not only to an explosion of
utilized storage space but also to unacceptably high
snapshotting time and network bandwidth utilization.

Zoom on mirroring
31
 One important aspect of on-demand mirroring is the decision of
how much to read from the repository when data is unavailable
locally, in such way as to obtain a good access performance.
 A straightforward approach is to translate every read issued by the
hypervisor in either a local or remote read, depending on whether
the requested content is locally available.
 While this approach works, its performance is questionable. More
specifically, many small remote read requests to the same chunk
generate significant network traffic overhead (because of the extra
networking information encapsulated with each request), as well as
low throughput (because of the latencies of the requests that add
up).

Testing Strategies
 UnitTesting
 IntegrationTesting
 AcceptanceTesting
32

Conclusion
As cloud computing becomes increasingly
popular, efficient management of VM images, such as image
propagation to compute nodes and image snapshotting is
critical.The performance of these operations directly affects
the usability of the benefits offered by cloud computing
systems.This paper introduced several techniques that
integrate with cloud middleware to efficiently handle two
patterns: multideployment and multisnapshotting.
Future enhancement:To provide more
security for the data in the cloud .
33

References
 [1] Amazon elastic blockstorage(ebs).http://aws.amazon.com/ebs/.
 [2] File system in userspace (fuse).http://fuse.sourceforge.net.
 [3] Nimbus. http://www.nimbusproject.org/.
 [4] Open nebula. http://www.opennebula.org/.
34

THANK YOU….
any QUERIES ????
35

Final report on GOING BACK AND FORTH EFFICIENT MULTIDEPLOYMENT AND MULTI SNAPSHOTTING ON CLOUDS.pptx

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