Opportunistic job sharing for mobile cloud computing

International Journal on Cloud Computing: Services and Architecture (IJCCSA) ,Vol. 4, No. 4, August 2014

OPPORTUNISTIC JOB SHARING FOR MOBILE CLOUD
COMPUTING
PARIDHI VIJAY
1
AND VANDANA VERMA
2
1B.E, Computer Science and Engineering, Rajasthan College of Engineering for Women,
Jaipur, Rajasthan
2Asst. Professor (CSE Dept.), Rajasthan College of Engineering for Women, Jaipur,
Rajasthan
ABSTRCT

Cloud Computing is the evolution of new business era which is covered with many of technologies.These
technology are taking advantage of economies of scale and multi tenancy which are used to decrees the
cost of information technology resources. Many of the organization are eager to reduce their computing
cost through the means of virtualization. This demand of reducing the computing cost and time has led to
the innovation of Cloud Computing. Itenhanced computing through improved deployment and
infrastructure costs and processing time. Mobile computing its applications in smart phones enable a
new, rich user experience. Due to extreme usage of limited resources in smart phones it create problems
which are battery problems, memory space and CPU. To solve this problem, we propose a dynamic mobile
cloud computing architecture framework to use global resources instead of local resources. In this
proposed framework the usefulness of job sharing workload at runtime reduces the load at the local client
and the dynamic throughput time of the job through Wi-Fi Connectivity.
KEYWORDS

Cloud Computing, Offloading, Cost, Time, Smartphone, Wi-Fi.
1. INTRODUCTION
Cloud Computing technology maintain data and application using central remote server. It permit
the user to use thesetechnologies without installation their related files at any computer. At any
time resources and applications are available to be use from the cloud via the internet. Cloud
technology is the base of new business. Cloud technology are taking advantage of economies of
scale and multi tenancy which are used to decrees the cost of information technology resources.
However, data use a significant and growing portion of energy, an average data consumes as
much energy as 30,000 households. Thecurrent demand of cloud computing technology is that
consumer only used those data which they required, and only pay for what they actually consume.
Mobile computing is an interaction between human and computer by which computer is expected
to be transported during usage [4]. It includes mobile hardware, mobile communication n mobile
software [4]. The greatest feature of the mobile cloud computing is that it allows user to connect
its relevant data from anywhere in the world via network. Energy-aware computing is crucial for
cloud computing systems that consume considerable amount of energy [5]. Problems occur when
trying to support mobility in computing devices: resource sparseness, hazardousness, finite
energy source, and low connectivity [5].
DOI : 10.5121/ijccsa.2014.4402 9

In this paper we refer job sharing/scheduling based algorithm so that each connected devices gets
their part of work and using offloading process each one can do their work properly
acknowledges to the central server. By using of Service Level Agreement, achieving high[35]
performance in cloud computing and of great significance for improving resource load balance,
security, reliability and reducing energy consumption of the whole system.[32,35In this paper we
used Wi-Fi as connectivity option. Using Wi-Fi based architectural framework we can utilize all
the global resources via network connectivity but not only limited to the local resources. Cloud is
available for low end mobile device as well as high end mobile device in this framework. Most of
the cloud resource would be mobile, computer, laptop etc. Dynamic mobile cloud framework can
handle run time resources and connectivity. In the framework we explain vision towards the
process large amount of job which requires huge hardware resources with smart phones by
partitioning the task into the number of jobs which is cost-saving, battery-life saving. Using this
architectural framework huge task can be done in just a matter of time using global resources.
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2. RESEARCHD ETAILS
Now days,Cloud Computing is one of the most famous topic and it is play very important role in
enterprises due to the cost charges and computational promises it gives. I am doing the study on
the issue of “Opportunistic Job Sharing For Mobile Cloud Computing” Opportunistic Job Sharing
group is an enterprise which is using Cloud Computing andmy research question are: What are
the basicprofits and drawback regarding cost, time and data security by using Wi-Fi technic for
Enterprises to adopt Cloud Computing?
2.1Purpose of Research
Basic fundamental of the thesis is to extract the advantages and drawbacks with respect to cost,
time, datasecurity and data availability so organizations can have by the use of Cloud Computing
for the implementation of their information system. Finally concluding the factors in terms of
cost, time and data security by using Wi-Fi technic, enterprises should keep in mind while
adopting CC for the effective and efficient use of their information system.
2.2 Related Work
In this section we provide a review of related research efforts, ranging from the earlier approaches
that focus two methods relating to offloading, job scheduling work from mobile.
Marinelli [2] introduce Hyrax, mobile cloud computing technology consumer that agrees mobile
devices to utilize cloud computing platforms. Based on Hadoop1, the main focus of this work is
to port a client into a mobile device to enable the integration. The author introduces the concept of
using mobile devices as resource providers, but further experimentation is not included. [2]
Integration between mobile devices and cloud computing is presented in several previous works.
Christensen [1] presents general requirements and key technologies to achieve the goal of mobile
cloud computing. The author introduces an exploration on latest smart phones, framework
awareness, cloud and restful based web services, and explains how to create this innovative
components for a better experience for mobile phone users. [1]
Fernando, W. Loke and WennyRahayu, Introduce the feasibility of a mobile cloud computing
framework to use local resources [4]. Main aim of the framework is to determine a usefulness of
sharing workload at runtime. The results of experiments conducted with Bluetooth transmission.
[4]

RehanSaleem (831015-T132),It Introduce cloud computing’s effect on enterprises, theirresearch
work is define, How to handle the effects of Cloud Computing in the enterprises. The specific
areas he researched during his study were cost and security and specially he give the differences
between grid computing and cloud computing, Cloud Computing is the sum of Software as a
Service (SaaS) and Utility Computing, but does not include Private Clouds. [6]
PriyankaGuptaPoojaDeshpande, It introduceto Efficient Resource Allocation and Scheduling
Approach to Enhance the Performance of Cloud Computing [32].Attempts to schedule the jobs
such a way that cloud provider can gain maximum benefit for his service and Quality of Service
(QoS) requirement user's job which enhances the performance of cloud service.[32]
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2.3 Motivation forthe Work
Let’s consider the scenario of Mr Rahul (Photo editor) travelling by car. He suddenly gets an
email to edit a large size image. He starts editing. Since the large size image need to be edited
only on laptop because it cannot be edited on the smart phones due to memory constraints, limited
battery power low CPU processing of smart phones. As the matter of the fact he cannot edit the
image.
In this scenario if he has a dynamic mobile cloud computing framework through this he can
create a cloud using network (Wi-Fi) then the result would be different. He uploads image to the
central server (cloud) using Wi-Fi network asks some of his colleagues to do it. All the cloud
clients (colleagues) edit the particular part of the image and again send back the response to the
server. Central server processes all the responds and again sends back to the Rahul.
In this way Rahul explores the dynamic architectural framework by using sharing/offloading
process to complete his job and moved over four major challenges: reduce bulkiness, time-saving,
limited memory and battery power. Now John is still available to do any urgent work which is the
best part of using this framework.
3. THEORETICAL DETAILS
Main idea of this section is to introduce the framework of my research thesis.
3.1 Cloud Computing
DEFINITION
There are lots of definitions of Cloud Computing giving by different-different researchers.
Barkley RAD defines Cloud Computing as [6]:
“Cloud Computing refers to both the applications as services over the Internet and the hardware
and systems software in the datacentres that provide those services. The services themselves have
long been referred to as Software as a Service (SaaS). The datacentre hardware and software is
what we will call a Cloud. When a Cloud is made available in a pay-as-you-go manner to the
general public, we call it a Public Cloud; the service being sold is Utility Computing. We use the
term Private Cloud to refer to internal datacentres of a business or other organization, not made
available to the general public. Thus, Cloud Computing is the sum of SaaS and Utility
Computing, but does not include Private Clouds. People can be users or providers of SaaS, or
users or providers of Utility Computing.”[6]

Cloud Computing is a new addingpattern. Infrastructure resources (hardware, storage and system
software) and applications are provided in as-a-Service manner. When these services are offered
by an independent provider or to external customers, Cloud Computing is basically based on
fundamental of paid-per-use concept. Main features of Clouds are virtualization and dynamic
scalability on demand. Utility computing technology and software as a services are provided in
acombinedstyle, whereas utility computing might be consumed separately. Cloud services are
used up either via Web browser or Application programming interface. [33]
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Figure 1. Cloud Services and Applications
3.2Cloud Service Models
There are 3 Cloud Services Models which are explain below
• Cloud Software as Service: - It is also known as “On demand Software”and it is a
software licensing and it provide the software to consumer on subscription base.
• Cloud Platform as Service:-In this type of service, the consumer can deploy, the user
generated or developed applications which is create by using programming or tools given
by provider, on the cloud infrastructure.[6]
• Cloud Infrastructure as Service: - This is a capability provided to the consumer by which,
it can provision processing, storage, networks and other fundamental computing
resources where the consumers can deploy and run the software.
3.3 Cloud Deployment Models
• Public Cloud:-This public cloud is available for every organization.
• Private Cloud:-This cloud is available only for particular organization or company.
• Community Cloud: - In this type of cloud deployment model, the infrastructure of the
cloud system is commonly used by many of the organizations and supports a specific
community with shared concerns.
• Hybrid Cloud:-It is a composition of two or more different clouds that is private or
community or public. Element of the hybrid cloud are tightly coupled.

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4. PROPOSED ARCHITECTURE
Figure 2. Main component of a cloud framework
The three main components of the architectural framework are cloud client, central server and ad-hoc
network.
CLOUD CLIENT
It’s like a master component of the cloud. This client sends request to the central server. SOAP
protocol is used as communicating medium among the connected devices. This is the master user
as this controls the all the query. It offloads all it works to the central server.
SOAP sender: Cloud Client
CENTRAL SERVER/Resource Manager
It is the heart of the architecture. It gets all the SOAP requests from the master that is cloud client
and converts into XML language. This server uses basic job sharing algorithm for distribute the
job intimidate to the other cloud connected devices according to their resource and capabilities.
It acts as a resource manager.
SOAP message path: Central Server
AD-HOC NETWORK/Job Handler
It is the bunch of connected devices which is responsible for the load balance. These are kind
of slave devices who acts on getting the SOAP request from the server. Whole devices share the
same cloud and every device gets the SOAP request from the central server depending on the size
of task from the master cloud client. Once the jobs have been distributed, the clients would
proceed to execute their job/s. When the job handler (client) devices finish their job, result are
sent back to the master and reassembled.
SOAP receiver: Ad-hoc network

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5. PROPOSED WORK AND IMPLEMENTATION
5.1 Basic Architecture
Figure 3.Basic Architecture
Figure 4. Flow Diagram of Cloud request and response
5.2 Processof Cloud Request and Response
Mobile user send the request to the cloud server, it passes through many step until acceptance
andrun or rejected. This process is shown in figure 4.As can be seen in figure 4, Cloud users(Job
submitter) send the request to the cloud sever to distribute or schedule the jobs according their
cost and availability time of volunteers(Job processor) and after they send the response to cloud
user through cloud servers . This entire step described in following:

15
• Request send to cloud server
• Waiting in buffers
• Reject the request because buffer is full or inapplicable
• Accept the request to server and distribute/scheduled the job
• Perform operation by job processor
• Send response to client
5.3 Job Scheduling
Proposed Algorithm described as follows:
Step 1: Cloud user send job request to the server.
Step2: Job request will be store in the JOB QUEUE according to their occurrence time.
Step 3: Select the ready job from the JOB QUEUE and put into BUFFER the job according.
Step 4: Place this job into VIRTUALE MACHINE and process the job according to the FCFS
(First Come First Serve) algorithm method.
Step 5: Scheduler distribute the sorted list according to the mobile client and balance loader and
send to the Resource pool.
Step 6: Repeat Step 3 to 5 for next set of job.
5.4 Image Processing:-
Image processing is a form of signal processing for which the input is an image, the output of
image processing may be either an image or a set of characteristics or parameters related to the
image. Image processing is a process to convert an non edited image into more clear image
through converting into digital signals in order to get more detailed image or to apply some more
effects on it .The purpose of image processing are image sharpening, restoration , visualization
,image recognition etc.
5.4.1Gray Scale
Gray-scale images represent data per element in a shade of gray that ranges in intensity from zero
(being black) to a maximum (being white) with various shades [13]. For example, an 8-bit gray
scale will range from 0 to 255, providing 256 different possible levels of brightness. [13]

International Journal on Cloud Computing: Services and Architecture
5.4.2 Conversion to Gray Scale
(IJCCSA) ,Vol. 4, No. 4, August 2014
There are many methods to define how to get
majority of colour images arestore in
image. A common conversion to gray scale is to take an average of the three values. However, a
weighted average of these three values is more appropriate to form a
the relative brightness for the sum of the three
system. [13-16]

a gray-scale image according to the user format.The
RGB (red, green, blue), and are combined to form the final

5.4.3 Gray Level Transformation Functions
gray intensity that preserves
colour components according to the human vision
To define a function that maps a gray level in the in
This is called a Gray Level Transformation function, and it looks like this:
input image to a gray level in the output image.

[15]

Where and represent a certain tain gray level, and it is
defined between 0 and 1.Eq (2)
every pixel on the image. These functions can be used for contrast enhancement, contrast
stretching, or thresholding. There here is some inverse function that exists that will return th
data. [13-16]
5.5 Implementation and Result
Figure 5.Gray Scale
In my thesis, I am takingan Image as a job
scheduled according to their time and
user and Laptop users).Allare connected to the Cloud server by using Wi
process the job and convert the image into Gray scale image
to convert into gray image, which is distribute or
cost to number of Job processor (Mobile users, Computer
are Wi-Fi connection
by using formula (1).
Figure 6. Job Submitting Process
16

put
is applied to
the original
connection. They

Step: 1 Job submitter connect via Wi-Fi to cloud server by using IP address of Server.
Step: 2 Job Submitter browse the original picture and submit and upload into server show in
figure [7].
Step: 3 When upload image to the server, it start to scheduling or distribute the jobs to Job
Processor according their time n cost.
Step: 4 Job Processors connect to cloud server and it will get jobs according their cost and time
performance show in figure [8].
Step: 5 All Job Processor start to convert original image into gray image, least cost get highest
jobs show in fig [8]
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Figure 7. Job Processor Process
Step 6: Send the response with grey image to Job submitter.
Step 7: Job Processor get money according the jobs count and cost
Job highest Priority sequence will be shown as below:-
Cost 1 Cost 2 Cost 3
(*coz cost 1take least amount compare to cost 2 and cost 3)
Advantage of the system
• MORE RELIABLE
• LOW COST RESOURCE
• LESS EXECUTION TIME
6. SIMULATION OF INSTRUMENT
In simulation with Cloud Analyst tools, there are two main components which are introduced
below.Two phones are Samsung Star Pro S7262,Samsung Galaxy Grand Neo Gti9060and a PC
were used in experiments. These three devices were used since they represent a range (low end
mobile, high end mobile, resource rich PC) of devices. The PC used had Microsoft Windows 8
Enterprise with Intel(R) Core(TM) Duo CPUE7300 @ 2.66 GHz 2.67 GHz as processor, hard
disk 20GB[64 bit] 2 GB RAM and requires a display adapter and a Wi-Fi adapter that supports
Wi-Fi Direct. Other details describe in below table

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Table 1.Mobile Client
Table 2.Server Specification
Scenario1:-We had an experiment of our implementation of our software. We used Go daddy
specification for testing on cloud computing. We took four kind of server configuration from the
vendor
• VMware Based: - We configured five VM on it with 1GB RAM and different OS on all
the VM for checking the cloud computing traffic.
• Cirtrixxen server:-We configured same five OS on xen server also but we found out that
xencitrix is easy for mobile traffic also.
Observations: - When we start the job from client as laptop and pc then we were having good job
scheduler. We are getting good response time and as well as processing time. We were doing on
all the five VM simultaneously for the traffic generations we used standard tool IOMETER_1.1.
We generated both kind of random as well as sequential jobs for the server.

Scenario2:-We noticed that we are getting very good performance with PC and laptop clients.
Then we thought why not we are merging the code for the mobile also. Right now all the
enterprise are using different kind of job scheduler software for the mobile traffic and laptop
traffic. So we merged the code to see how the code will perform having laptop and mobile traffic
simultaneously. We configured 10 VM (virtual machine) for the test configuration. Thenwe
observed that processing time and response were little bit on higher side but when we configured
10 Data Centres then we are getting approximate same values as were getting before.Please find
the comparative data for the above test below:-

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Figure 8 Average processing time Figure 9 Average response of laptop and mobile
7. CONCLUSION
The concept of cloud computing and job sharing over cloud provides a brand new opportunity for
the development of mobile applications that can get heavy tasks done over cloud by offloading
computation tasks on cloud, it allows smart mobile devices to retain a small layer for consumer
applications and change the processing overhead to the virtual situation. Using the proposed
framework the usefulness of job sharing workload at runtime reduces the load at the local client
and the dynamic throughput time of the job through Wi-Fi Connectivity instead of the Bluetooth.
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AUTHOR
Paridhi Vijay received the B.E degree in Computer Science and Engineering from
R.C.E.W,Jaipur in 2007 and pursuing M.Tech in Computer Science from R.C.E.W,
Jaipur She has one year of experience in teaching field in COMPUCOM college.
and 2 year experience in software development

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