Title of article :
Optimization Task Scheduling Algorithm in Cloud Computing
Author/Authors :
Taherian Dehkordi, Somayeh Department of Computer Engineering - Kerman Branch Islamic Azad University , Khatibi Bardsiri, Vahid Department of Computer Engineering - Kerman Branch Islamic Azad University
Abstract :
Since software systems play an
important role in applications more than ever, the
security has become one of the most important
indicators of softwares.
Cloud computing refers to services that run in
a distributed network and are accessible through
common internet protocols. Presenting a proper
scheduling method can lead to efficiency of
resources by decreasing response time and costs.
This research studies the existing approaches of
task scheduling and resource allocation in cloud
infrastructures and assessment of their advantages
and disadvantages.
Afterwards, a compound algorithm is presented
in order to allocate tasks to resources properly and
decrease runtime. In this paper we proposed a new
method for task scheduling by learning automata
(LA). This method where has named RAOLA is
trained by historical information of task execution
on the cloud, then divide task to many classes and
evaluate them. Next, manage virtual machine for
capture physical resources at any period based on
rate of task classes, such that improve efficiency of
cloud network.
Keywords :
learning automata , cloud environment , Resource allocation
Journal title :
Astroparticle Physics