In Dynamic Resource Allocation, WE PRESENT A SYSTEM THAT USES VIRTUALIZATION TECHNOLOGY TO ALLOCATE DATA CENTER RESOURCES DYNAMICALLY.
WE INTRODUCE THE CONCEPT OF “SKEWNESS”.
And BY MINIMIZING SKEWNESS, WE CAN COMBINE DIFFERENT TYPES OF WORKLOADS NICELY AND IMPROVE THE OVERALL UTILIZATION OF SERVER RESOURCES.
WE DEVELOP A SET OF HEURISTICS THAT PREVENT OVERLOAD IN THE SYSTEM EFFECTIVELY WHILE SAVING ENERGY USED.
Dynamic resource Allocation using Virtual Machines For Cloud Computing
Directory are listing of static information that are usually inputted manually and not CRAWLED. Some of the common characteristics of today’s search engines are as follows: * A search engine component usually contain the following components… I would like you to take a mental note of the Spider … since this will be a important topic we will discuss later on today. In early day’s for you who remember this WebCrawler was one of the many crawler based directory search engines …. another common one that still exists today is AltaVista search engine.
Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment
DYNAMIC RESOURCE ALLOCATION USING
VIRTUAL MACHINES FOR CLOUD
S.SAI KIRAN REDDY (11QA1A05A6)
Project coordinatorProject coordinator
Mrs.R.Usha Rani,M.Tech.Mrs.R.Usha Rani,M.Tech.
Associate professorAssociate professor
DEPT OF CSEDEPT OF CSE
Project guideProject guide
Associate professorAssociate professor
DEPT OF CSEDEPT OF CSE
• Existing System
• Proposed System
• System Requirements
• UML Diagrams
Cloud computing allows business customers
to scale up and down their resource usage
based on needs. Many of the touted gains in the
cloud model come from resource multiplexing
through virtualization technology.
In this paper, we present a system that uses
virtualization technology to allocate data center
resources dynamically based on application
demands and support green computing by
optimizing the number of servers in use
• WE PRESENT A SYSTEM THAT USES
VIRTUALIZATION TECHNOLOGY TO ALLOCATE
DATA CENTER RESOURCES DYNAMICALLY.
• WE INTRODUCE THE CONCEPT OF “SKEWNESS”.
• BY MINIMIZING SKEWNESS, WE CAN COMBINE
DIFFERENT TYPES OF WORKLOADS NICELY AND
IMPROVE THE OVERALL UTILIZATION OF
• WE DEVELOP A SET OF HEURISTICS THAT
PREVENT OVERLOAD IN THE SYSTEM
EFFECTIVELY WHILE SAVING ENERGY USED.
• VIRTUAL MACHINE MONITORS (VMMS) LIKE XEN
PROVIDE A MECHANISM FOR MAPPING VIRTUAL
MACHINES (VMS) TO PHYSICAL RESOURCES.
• THIS MAPPING IS LARGELY HIDDEN FROM THE
• IT IS UP TO THE CLOUD PROVIDER TO MAKE SURE
THE UNDERLYING PHYSICAL MACHINES (PMS)
HAVE SUFFICIENT RESOURCES TO MEET THEIR
• VM LIVE MIGRATION TECHNOLOGY MAKES IT
POSSIBLE TO CHANGE THE MAPPING BETWEEN
VMS AND PMS WHILE APPLICATIONS ARE
• WE PRESENT THE DESIGN AND IMPLEMENTATION OF AN
AUTOMATED RESOURCE MANAGEMENT SYSTEM THAT
ACHIEVES A GOOD BALANCE BETWEEN OVERLOAD
AVOIDANCE AND GREEN COMPUTING
▫ OVERLOADAVOIDANCE: THE CAPACITY OF A PM SHOULD
BE SUFFICIENT TO SATISFY THE RESOURCE NEEDS OF ALL
VMS RUNNING ON IT. OTHERWISE, THE PM IS
OVERLOADED AND CAN LEAD TO DEGRADED
PERFORMANCE OF ITS VMS.
▫ GREEN COMPUTING: THE NUMBER OF PMS USED SHOULD
BE MINIMIZED AS LONG AS THEY CAN STILL SATISFY THE
NEEDS OF ALL VMS. IDLE PMS CAN BE TURNED OFF TO
• WE DEVELOP A RESOURCE ALLOCATION SYSTEM THAT CAN
CLOUD COMPUTING MODULE
• Cloud computing refers to applications and services
offered over the Internet. These services are offered from
data centers all over the world, which collectively are
referred to as the "cloud."
• Cloud computing is a movement away from applications
needing to be installed on an individual's computer
towards the applications being hosted online. Cloud
resources are usually not only shared by multiple users
but as well as dynamically re-allocated as per demand.
This can work for allocating resources to users in
different time zones.
RESOURCE MANAGEMENT MODULE
• Dynamic resource management has become an active area of
research in the Cloud Computing paradigm. Cost of resources varies
significantly depending on configuration for using them. Hence
efficient management of resources is of prime interest to both Cloud
Providers and Cloud Users.
• The success of any cloud management software critically de-pends
on the flexibility; scale and efficiency with which it can utilize the
underlying hardware resources while pro-viding necessary
• Successful resource management solution for cloud environments,
needs to provide a rich set of resource controls for better isolation,
while doing initial placement and load balancing for efficient
utilization of underlying resources.
• Virtualization, in computing, is the creation of a virtual
(rather than actual) Version of something, such as a
hardware platform, operating system, and a storage
device or network resources. VM live migration is a
widely used technique for dynamic resource allocation in
a virtualized environment.
• The process of running two or more logical computer
system so on one set of physical hardware. Dynamic
placement of virtual servers to minimize SLA(Service
level agreement) violations.
GREEN COMPUTING MODULE
• Many efforts have been made to curtail energy
consumption. Hardware based approaches include novel
thermal design for lower cooling power, or adopting
power-proportional and low-power hardware. Dynamic
Voltage and Frequency Scaling (DVFS) to adjust CPU
power according to its load in data centers.
• Our work belongs to the category of pure-software low-
cost Solutions. It requires that the desktop is virtualized
with shared storage. Green computing ensures end user
satisfaction, regulatory compliance, telecommuting,
virtualization of server resources.
Use Case DiagramUse Case Diagram
Sequence DiagramSequence Diagram
serviceProvider Register Login viewCloudUser
viewCloudSites vieServerStatus viewResource
enterRegistrationDetails store in DB
enter uname&password verify
views cloud user request retrive form DB
views websites hosted in the cloud retrive from DB
viewing the status of servers i.e memory alloted or availablememory get from DB
views Memory alloxcation Status in Graphical format
retrive from DB
• Operating System : Windows
• Technology : Java and J2EE
• IDE : My Eclipse
• Web Server : Tomcat
• Cloud Tool : SDB Navigator
• Database : My SQL
• Java Version : J2SDK1.5
• Hardware : Pentium
• Speed : 1.1 GHz
• RAM : 1GB
• Hard Disk : 20 GB
• Floppy Drive : 1.44 MB
• Key Board : Standard Windows Keyboard
• Mouse : Two or Three Button Mouse
• Monitor : SVGA
• WE HAVE PRESENTED THE DESIGN AND EVALUATION OF A
RESOURCE MANAGEMENT SYSTEM FOR CLOUD COMPUTING
• OUR SYSTEM MULTIPLEXES VIRTUAL TO PHYSICAL
RESOURCES ADAPTIVELY BASED ON THE CHANGING
• WE USE THE SKEWNESS METRIC TO COMBINE VMS WITH
DIFFERENT RESOURCE CHARACTERISTICS APPROPRIATELY
SO THAT THE CAPACITIES OF SERVERS ARE WELL UTILIZED.
• OUR ALGORITHM ACHIEVES BOTH OVERLOAD AVOIDANCE
AND GREEN COMPUTING FOR SYSTEMS WITH MULTI-
• Maintenance is the last phase in the software
engineering process. As more programs are
developed, a distributing trend has emerged the
amount of effort and a resource expended on software
maintenance is growing. In total project development
maintenance takes 65% of effort.
• So we will take lead on this and Strive to Produce
More better Experience to Users according to the