SCHEDULING IN CLOUD COMPUTING ENVIRONMENT

Submitted By: Sakshi Saxena(10103451), Mayuri Saxena(10104758)

Submitted To: Mr. Prakash Kumar

Introduction

What is Cloud Computing?What is Cloud Computing?

• Shared computing resourcesShared computing resources

• As opposed to local servers and devicesAs opposed to local servers and devices

• Made up of Grid InfrastructureMade up of Grid Infrastructure

• ScalableScalable

• VirtualizationVirtualization

• Web applicationsWeb applications

• Specialized raw computing servicesSpecialized raw computing services

Introduction 2Cloud computing refers to both the applications delivered as services

over the Internet and the hardware and systems software in the data centers that provide those services. With the advent of the Cloud, new possibilities have arrived to build an application on the internet. The computing paradigm includes- cluster computing, grid computing, P2P computing, service computing, market oriented computing and most recently introduced cloud computing. The computing facilities however, must be efficient, candid, time-tested and hefty. Since the customer satisfaction is the foremost priority, therefore quality of services are provided by two promising computer paradigms: Grid computing and Cloud computing.

The cloud computing services themselves have long been referred to as Software as a Service (SaaS). Some vendors use terms such as IaaS (Infrastructure as a Service) and PaaS (Platform as a Service) to describe their products. Cloud computing systems promise to offer subscription-oriented & enterprise-quality computing services to users worldwide.

Cloud Computing ArchitectureCloud Computing Architecture

Virtualization

• Virtual Machine (VM) is a software artifact that executes other software as if it was running on a physical resource directly.

• Typically uses a Hypervisor or VMM which abstracts the hardware from an Operating System

Problem StatementCloud is developing day by day and faces many challenges, one of

them is scheduling. The efficient job scheduling increases the client satisfaction and utilize the system energy in terms of time. How to use Cloud computing resources efficiently and gain the maximum profits with efficient utilization of resources is one of the Cloud computing service providers’ ultimate goals. Repetitive evaluation of the performance of Cloud provisioning policies, application workload models, and resources performance models in dynamic system are difficult to achieve and rather a time consuming and costly approach.

The objective of this project is analyzing and evaluating the performance of various CPU scheduling in cloud environment to improve the application performance under resource and service demand variations. We will discuss different Task(cloudlet) Scheduling Policies in Virtual Machine and their performance analysis in Virtual environment of cloud computing in order to achieve better Quality of Service (QoS).

Experimental Study

Several simulators have been specifically developed for performance analysis of cloud computing environments including CloudSim, GreenCloud, NetworkCloudSim, CloudAnalyst, EMUSIM and MDCSim but the number of simulation environments for cloud computing data centers available for public use is limited. The CloudSim simulator is probably the most sophisticated among the simulators overviewed.

A comparative study was done comparing the various existing algorithms with the proposed algorithm in CloudSim and the results were illustrated in the form of graphs.

CloudSimCloudSim ToolKit - CloudSim is a framework developed by the GRIDS

laboratory of University of Melbourne which enables seamless modeling on designing Cloud computing infrastructures. It provides basic classes for describing data centers, virtual machines, applications, users, computational resources, and policies for management of diverse parts of the system. It provides features for modeling and creating the data center. By using CloudSim, developers can focus on particular system design issues of the infrastructure of cloud system, without getting into the lower level details related to Cloud-based infrastructures and services.

CloudSim supports various functions of cloud system entities (services, host, data center, broker, VMs) such as queuing and processing of events & communication between components.

ImplementationInput data, or test data, will be manually, and sporadically, input using the test data created for the project. This test data contains requests like length of cloudlets, processing element required by them, priority(default=0), start time of cloudlets etc. A web interface using MVC framework has been created with the help of Struts2.0 framework.

HARDWARE INTERFACEProcessor: Core I3 and aboveRAM: 1 GBDisk space: Min. 1Gb

SOFTWARE INTERFACEOperating System: Windows 7/8Language: JAVA, Struts 2Tools: Eclipse Keepler , Apache Tomcat ServerCloudSim Toolkit

Use Case Diagram

Comparison with Existing Algorithms

Product Functions

This project is implementing following scheduling algorithms on cloudlets submitted to VM and then comparing the response time and turnaround time of all the cloudlets.

• Time Shared Scheduling • Space Shared Scheduling• Shortest Job First• First Come First Serve• Round Robin• Proposed algorithm

User Interface-MVCModel View Controller or MVC as it is popularly called, is a software design pattern for

developing web applications. A Model View Controller pattern is made up of the following three parts:

• Model - The lowest level of the pattern which is responsible for maintaining data.

• View - This is responsible for displaying all or a portion of the data to the user.

• Controller - Software Code that controls the interactions between the Model and View.

MVC is popular as it isolates the application logic from the user interface layer and supports separation of concerns. Here the Controller receives all requests for the application and then works with the Model to prepare any data needed by the View. The View then uses the data prepared by the Controller to generate a final presentable response. The MVC abstraction can be graphically represented as follows.

Struts 2.0The model:The model is responsible for managing the data of the application. It

responds to the request from the view and it also responds to instructions from the controller to update itself.

The view:A presentation of data in a particular format, triggered by a controller's

decision to present the data. They are script based templating systems like JSP, ASP, PHP and very easy to integrate with AJAX technology.

The controller:The controller is responsible for responding to user input and perform

interactions on the data model objects. The controller receives the input, it validates the input and then performs the business operation that modifies the state of the data model.

NoveltyCloud computing has been one of the fastest growing parts in IT industry. Simulation based approaches become popular in industry and academia to evaluate cloud computing systems, application behaviors and their security. This project compares the existing scheduling algorithms for cloud computing environment. On the basis of the results we have designed an efficient scheduling algorithm for faster execution of jobs submitted to run in a datacenter, A Virtual Machine is an abstraction of computer hardware within software. The basic information of virtual machine is given . It includes process speed, image size, ram size, bandwidth, and number of CPUs of virtual machine. Also, there are cloudlet properties such as length, file size and output size. CloudSim uses these factors to configure datacenters, brokers, and virtual machines. To simulate the system, startsimulation method is called in the user code. This method calls other methods such as run, runStart, runClockTick, and runStop in sequence. As a novelty, this policy incorporates MIPS rating of virtual machines in the decision process.

Conclusion In this project we have compared various scheduling algorithm in cloud

computing environment and tried to find an optimized solution which will overcome the limitations of existing algorithm.The Round Rubin (RR) job scheduling algorithm considered in this study distributes the selected job over the available VMs in a round order where each job is equally handled. The idea of the RR algorithm is that it sends the selected jobs to the available VMs in a round form. In the First Come First Serve job scheduling the arrival time of jobs are queued in the order of which come first.In Shortest Job First they give more priority to small jobs, medium and long jobs are executed after the execution of small jobs. Fragmentation occurs at many stages leads to waste of energy and increase the cost of customer on pay per use. In space shared the form of either VM Scheduler Space Shared or Cloudlet Scheduler Space Shared. It means that if there are more running VM’s or Cloudlets than available PEs, the last elements to arrive wait on a queue until enough resources are free. Cloudlet Scheduler Time Shared fraction of available PEs are shared among running elements, and all the elements run simultaneously.

References

• A.K. Amoura, E. Bampis, C. Kenyon, and Y. Manoussakis, “Scheduling Independent Multiprocessor Tasks”, Algorithmica, vol. 32, pp. 247–261, 2002.

• Burya R Raman, R. Calheiros, R.N.(2009) “Modeling and Simulation of Scalable Cloud Environment and the Cloud Sim Toolkit: Challenges and Opportunities’’, IEEE publication 2009,pp1-11

• B.Furht, and A. Escalante, “Handbook of cloud computing,” Cloud computing fundamentals chapter writen by B. Furht, Springer, 2010.

• CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms Rodrigo N. Calheiros1, Rajiv Ranjan2, Anton Beloglazov1,C´ esar A. F. De Rose3 and Rajkumar Buyya1.

•• G. Raj , S. Setia “Effective Cost Mechanism for Cloudlet Retransmission and Prioritized VM Scheduling

Mechanism over Broker Virtual Machine Communication Framework ,” International Journal on Cloud Computing: Services and Architecture(IJCCSA),Vol.2, No.3, June 2012, pp. 41-50.

• M. Gahlawat , P. Sharma “Analysis and Performance Assessment of CPU Scheduling Algorithms in Cloud using Cloud Sim,” International Journal of Applied Information Systems (IJAIS) Volume 5 - No. 9 , July 2013 , pp. 5-8.

• Pinal Salot, “A Survey of various Scheduling Algorithm in Cloud• Computing Environment,” IJRET, vol. 2, pp.131–135, 2013.

Thank You !!!