International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 02 Issue: 05 | Aug-2015
p-ISSN: 2395-0072
www.irjet.net
Hybridization of algorithms for Cloud Computing
Loopy Bhatti1, Gureshpal Singh2, Sanjeev Mahajan3
M.Tech Scholar, Computer Science and Engg., B.C.E.T Gurdaspur, Punjab, India
Associate Professor, Information and Technology, B.C.E.T Gurdaspur, Punjab, India
3 Associate Professor, Computer Science and Engg., B.C.E.T Gurdaspur, Punjab, India
---------------------------------------------------------------------***--------------------------------------------------------------------1. Introduction
Abstract - “Cloud Computing” is a term, which involves
1
International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 02 Issue: 05 | Aug-2015
p-ISSN: 2395-0072
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helpful. Jobs and job streams can be planned to run at
enhance the QoS of task scheduling indirectly in a
whatever point needed, taking into account business
cloud environment.
capacities, needs, and needs. Job streams and procedures
v.
The
throughput
of
the
system-Mainly
for
can set up every day, week after week, month to month,
distributed computing frameworks, throughput is a
and yearly ahead of time, and keep running on-interest
measure
jobs without need for help from support staff.
streamlining execution, and it is likewise an objective
1.2 Need of job scheduling
which must be considered in plan of action
The objective of job scheduling in Cloud computing is give
ideal tasks scheduling for clients,
and to give good
throughput and QoS at the same time. Subsequent are the
needs of job scheduling in cloud computing:
i.
has nearly related with one another in the cloud
environment, task planning system capable for the
matching
of
tasks
and
assets. Task
scheduling algorithm can keep up load balancing. So
load balancing get to be another imperative measure
in the cloud.
ii.
computing
and
distributed
storage
administrations, asset interest for clients and assets
supplied by supplier to the clients in such a route
along these lines, to the point that quality of service
can be accomplished. At the point when job
scheduling administration comes to job assignment,
it is important to ensure about QoS of assets.
iii.
Economic Principles-Cloud computing assets are
generally conveyed all through the world. These
assets may fit in with diverse associations. They have
their own particular administration strategies. As a
plan of action, distributed computing as indicated by
the
distinctive
prerequisites,
give
applicable
administrations. So the demand charges are sensible.
iv.
The best running time -jobs can be partitioned into
diverse classes as indicated by the needs of clients,
and after that set the best running time on the
premise of distinctive objectives for every job. It will
advancement. Build throughput for clients and cloud
suppliers would be advantage for both of them.
2. Proposed Work
cloud providers and cloud users. On one hand, providers
hold massive computing resources in their large
datacenters and rent resources out to users on a per-usage
basis. On the other hand, there are users who have
applications with fluctuating loads and lease resources
from providers to run their applications. First, a user
sends a request for resources to a provider. When the
provider receives the request, it looks for resources to
Quality of Service-The cloud is primarily to give
clients
framework
In cloud computing environments, there are two players:
Load Balance-Load balancing and task scheduling
optimal
of
satisfy the request and assigns the resources to the
requesting user. Then the user uses the assigned resources
to run applications and pays for the resources that are
used. When the user’s job is completed then the resources
are free and returned to the service provider. Proper
scheduling is needed to meet user’s requirements and
satisfies the Qos parameters. In this thesis, an efficient
hybrid scheduling approach is proposed in computational
cloud. Proposed work is grouping the tasks before
resource allocation according to job priority to reduce the
communication overhead. The purpose work has been
divided into three sessions namely job creation, system
creation and the schedule.
Following are the metrics on the basis of which results are
evaluated:1. CPU Utilization: - The CPU time is measured in clock
ticks or seconds. Often, it is useful to measure CPU time as
a percentage of the CPU's capacity, which is called the CPU
usage.
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International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 02 Issue: 05 | Aug-2015
p-ISSN: 2395-0072
www.irjet.net
2. Response time:- The elapsed time between the end of
an inquiry or demand on a cloud and the beginning of a
response is called the Response time.
3. Time to complete a batch of jobs:-This is the total
time taken by the cloud to complete the execution of
submitted batch of jobs from beginning to ending by the
different algorithms. To analyze the time to complete the
execution of submitted jobs, first we select 10 jobs from
the selection part and initialize the server configuration.
Fig -1: Proposed algorithm
To analyze the performance of proposed algorithm, 48
simulations have been performed in the cloud and results
are obtained. First of all, the cloud is started by choosing
the configuration and the jobs are created with different
requirements. During the simulation, first we select ten
jobs, then the system checks all the selected jobs that are
Chart -1: CPU Utilization verses number of jobs.
to be executed by the scheduler. It creates the groups of
jobs for execution and set the priority on the basis of CPU
utilization by each group. Now we have task groups to
execute by the scheduler. Here hybrid algorithm performs
their function to optimize the execution of jobs. Then
priority algorithm will sort the groups according to their
priority. The priority is set on the basis of system
threshold value which is evaluated on the basis of CPU
utilization. All the jobs in each group will be executed by
FCFS algorithm. When the jobs under each group are
Chart -2: Response time versus number of jobs
executed completely then performance parameters are
evaluated.
3. CONCLUSIONS
Job scheduling is an essential requirement in cloud
computing environment with the given constraints. Some
intensive researches have been done in the area of job
scheduling of cloud computing. The scheduling algorithms
should order the jobs in a way where balance between
improving the performance and quality of service and at
Chart -3: Total Time to complete verses Jobs
the same time maintaining the efficiency and fairness
among the jobs. This thesis proposed the solution to
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International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 02 Issue: 05 | Aug-2015
p-ISSN: 2395-0072
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