Task Scheduling in Cloud Based on Three Stage Method using Historical Data

Abstract

The on-demand availability of computer system resources such as data storage and computing power is cloud computing. Scheduling is the method of allocating jobs onto resources in time. Scheduling increases the efficiency and performance of cloud environment by maximizing the resource utilization. This scheduling process has to respect constraints given by the jobs and the cloud providers. Ordering the tasks by scheduler along with maintaining the balance between Quality of Service (QoS), fairness and efficiency of jobs is difficult. Scheduling algorithms are designed and implemented considering some parameters like latency, cost, priority, etc. This paper proposes a method for task scheduling in cloud using a three-stage method. The first stage makes use of historical scheduling data to classify tasks. Based on this VMs are created. In the second stage newly arrived tasks are considered. Based on Bayes classifier principle a matching degree is calculated to mark a task with a VM Type. In the third stage, tasks are matched with corresponding VMs. Then the tasks are scheduled using a scheduling algorithm and are executed in the host. Keywords: Task scheduling, Cloud computing. I. INTRODUCTION Cloud is a trendy term for a network or remote servers that can be accessed via an Internet connection store and manage information. Two types of models present such as deployment models and service models. The deployment model includes private, public and hybrid cloud. Private Clouds are Data center architecture owned by a single company. E.g., IBM's BlueCloud, SunCloud, WindowAzure. Public Clouds are basically the Internet. To make resource available to general people, service provider use internet. E.g., Gmail, Office 365, Dropbox. In case of hybrid clouds, for instance during peak periods individual applications or portion of applications can be migrate to the public cloud. The service model includes Software as a Service (SaaS) such as Dropbox, Google Apps, Platform as a Service (PaaS) such as Google Compute Engine, Apache Stratos and Infrastructure as a Service (IaaS) such as Virtual Machine, Storage, Servers. Cloud provides on demand computational resources in the form of virtual machines. These Virtual Machines are deployed in a cloud provider's data center. The computational resources are shared among different cloud consumers who pay for the service accessed as per the usage. Allocation of resources and proper scheduling has a considerable impact on the performance and efficiency of the system. The main goal of cloud computing is to provide efficient access to remote and geographically distributed resources. An efficient scheduling is a key to manage the access to different resources, load balancing as well as resource allocation. Different types of resource scheduling algorithms are available in cloud computing based on certain parameters like time, cost, and performance, utilization of resources, throughput, bandwidth, resource availability, physical distances and priority. A. Scheduling In Cloud Computing Scheduli...