2. ABSTRACT
Cloud computing is an emerging concept combining
many fields of computing. Cloud computing consists of
two provisioning plan for allocating resources in cloud,
they are Reservation plan and on-demand plan.
Resource allocation is done by using Reservation plan
in this proposed method. The proposed scheme has
two features, they are
• Virtual Machine Deployment
• Implementation of optical code resources
provisioning(OCRP).
3. INTRODUCTION
• In recent years, applications targeted at mobile devices have started
becoming abundant with application in various categories such as
entertainment, gaming, business, travel and news.
• The mobile computing is able to provide a tool to the user when and
where it is needed irrespective of users movement, hence supporting
location independence. Indeed mobility is one of the characteristic of
pervasive computing environment where the user is able to continue
his/her work seamlessly regardless of his or her movement.
• Mobility has its inheritance problems such as resource scarceness,
finite energy and low connectivity.
• Cloud computing is a evolved computing terminology based on utility
and consumption of computing resources.
4. • Major issue in cloud computing is provisioning method for allocating
resources to cloud consumers.
• Cloud computing consists of two provisioning plan for allocating
resources in cloud, they are
Reservation plan
On-demand plan
• Cloud customer could not fully meet the required resources in
reservation plan.
• Issue with reservation plan is over provisioning of resources, where
the reserved resources will be more than what actually needed.
5. WHAT IS CLOUD COMPUTING?
A network of providing resources,
is called a Cloud.
Cloud computing is an
emerging concept,
combining many fields,
of computing,
which provides services,
over the internet.
6. WHAT IS MOBILE CLOUD
COMPUTING(MCC)?
MCC is the combination
of cloud computing,
mobile computing and,
wireless networks to,
bring rich computational,
resources to mobile
users,network operators,
as well as cloud
computing providers.
8. PROBLEM STATEMENT
• In bin packing PM’s are regarded as bins and
VM’s, which have capacity and weights
respectively.
• Only VM request is mapped to PM, leads to
limited packing and load balancing capability.
• Multiple VM’s can be mapped to one PM
results to low resources utilization and
imbalanced load.
9. OBJECTIVES
• Allocating the resources and storage in mobile
by cloud computing based on the reservation
priority.
• Using Hungarian method for resource
allocation.
• Stochastic integer programming to achieve
optimal solution.
OBJECTIVES
10. LITERATURE SURVEY
“On network and computing environments” [2]
• MCC resource management framework should
simultaneously take into consideration,
Wireless/radio access resources pool aiming at
always-best connectivity context.
Computing resources pool for data processing or
storage aiming at flexible virtualized infrastructure
sharing solutions.
• The ultimate vision is to fullfil the dream of
providing information at every one’s fingertips
anywhere at anytime.
LITERATURE SURVEY
11. Advantage
• Widely accepted abstract paradigm the feature
computing continuum is expected to embrase
distant cloud infrastructure, proximate cloudlet
infrastructures, communicating objects and smart
devices.
Disadvantage
• Problem of battery power restriction are inevitable.
• Explosion of mobile applications market, the
average mobile users demand for
computing/storage power is much higher than the
one that can be supported by an average MT and
this gap is continuously growing.
12. “Optimal resource allocation for multimedia cloud”[5]
• Many multimedia applications, such as
image/video retrieval and 3D model rendering,
require intensive computation and/or intensive
storage, especially to the mobile devices.
• In Multimedia Cloud(MC),cloud service providers
deploy cloud resources as utilities to process
multimedia requests and then deliver computing
results to customers.
Advantage
• Optimally allocate resources to satisfy the Quality
of Service(QoS) requirements of various
multimedia applications.
13. Disadvantage
• Difficult to analyse the performance in priority
service scheme, when the number of priority class
exceeds two.
“Optimization of cost in cloud computing using OCRP
algorithm”[6]
• The OVMP algorithm used to solve both resources
provisioning for cloud consumers and VM
placement.
Advantage
• OCRP algorithm improves the number of provision
stages.
• Reduces the cost.
•
15. HUNGARIAN METHOD
• The Hungarian method is a combinational optimization algorithm
that solves the assignment problem.
• The VM, tasks, and an n×n matrix containing the cost of assigning
each VM to a task, find the cost minimizing assignment.
• Problem is written in the form of a matrix as given below:
a1 a2 a3 a4
b1 b2 b3 b4
c1 c2 c3 c4
d1 d2 d3 d4
• Where a, b, c and d are the VM who have to perform tasks 1, 2, 3
and 4. a1, a2, a3, a4 denote the penalties incurred when VM "a"
does task 1, 2, 3, 4 respectively. The same holds true for the other
symbols as well.
17. RESOURCE PROVISIONING MODEL
• The computing resources are provisioned by using
the resource provisioning model and the provision
resources are network, storage, CPU processing
power.
• Resource Provisioning model is proposed using
Stochastic Integer Programming algorithm.
20. CONCLUSION
• The open stack private cloud environment is
configured by using java language.
• Using Hungarian method virtual machine
deployment implemented and resources utilization
is monitored in an effective manner.
• The Stochastic Integer programming with resource
is applied to solve the complexity of optimization
problems under uncertainty.
• This algorithm reduces reservation and expending
cost.
21. REFERENCES
1. “OCRP in resource allocation using cloud computing” M.C Babu,
S.Umamageswari, International of journal of computer science and information
technologies, 2014.
2. Skoutas, D.N.; Skianis, C. “On networking and computing environments'
integration: A novel mobile cloud resources provisioning approach “
3. “Resource allocation and storage using Hungarian method in cloud computing”
Praveena Akki, Poonguzhali.E, International journal of advanced computer
science and software engineering, 2013.
4. “Applying Stochastic Integer Programming to Optimization of Resource
Scheduling in Cloud Computing”, Qiang Li, Journal of networks, 2012.
5. He, Yifeng; Guan, Ling “Optimal resource allocation for multimedia cloud in
priority service scheme “ in Circuits and Systems (ISCAS), 2012 IEEE International
Symposium on 20-23 May 2012 .
6. Bu-Sung Lee; Niyato, D. “Optimization of Resource Provisioning Cost in Cloud
Computing “Services Computing, IEEE Transactions on April- June 2012 Volume:
5, Issue: 2 [5] “
In bin packing PM’s are regarded as bins and VM’s which have capacity and weights respectively.
Only VM request is mapped to PM, leads to limited packing and load balancing capability.
Multiple VM’s can be mapped to one PM results to low resources utilization and imbalanced load.
OBJECTIVES
“On network and computing environments”
MCC resource management framework should simultaneously take into consideration,
Wireless/radio access resources pool aiming at always-best connectivity context.
Computing resources pool for data processing or storage aiming at flexible virtualized infrastructure sharing solutions.
The ultimate vision is to fullfill the dream of providing information at every one’s fingertips anywhere at anytime.
Advantages
Widely accepted abstract paradigm the feature computing continum is expected to embrase distant cloud infrastructure, proximate cloudlet infrastructures, communicating objects and smart devices.
Disadvantages
Problem of battery power restriction are inevitable.
Explosion of mobile applications market, the average mobile users demand for computing/storage power is much higher than the one that can be supported by an average MT and this gap is continuously growing.
LITERATURE SURVEY
