A New Framework for Job Scheduling and Resource Management in Grid Environment

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International Journal of Emerging Technology and Advanced Engineering

Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 4, April 2012)

462

A New Framework for Job Scheduling and Resource

Management in Grid Environment

1

Akash Malhotra,

2

Kunal Gupta

AMITY school of Engineering and Technology,University, Noida, India

1_{akash10malhotra@gmail.com} 2_{kunal2151@gmail.com}

Abstract: A Grid is a special form of distributed computing resources that are available over a network and appears to an end user as one large virtual computing system. Scheduling system plays a vital role to allocate resources to the input jobs. The goal of scheduling is to achieve maximum throughput with the available computing resources. One major issue with the grid environment is the effective utilization of the scheduling of jobs. The problem can be addressed by scheduling the jobs to those nodes and processors that are lightly loaded. This paper also discuss about the various attributes of grid computing and job scheduling algorithms at global queue and local queue.

Keywords-Job scheduling, Global queue, Local queue, Available CPU Resource.

I. I

NTRODUCTION

:

Grid computing is an extension of distributed computing where every computer on the network shares all its resources turning the network more powerful. A network can be hardwired or wireless (over the internet). System can also be homogenous or heterogeneous. If two grid computing systems do not follow same set of protocols then they may not be compatible with each other. Many organizations are working together in the same direction to create standard protocols that make it easier to set up grid environments. In grid computing, at least one computer acts as a server which allocate the resources to all jobs that are ready to execute. The emergence of grids is due to the needs of large-scale computing infrastructures for solving major computing and data-intensive problems in the fields of science, engineering, industry and business. A grid job is typically submitted for execution by an appropriate node on the grid. It may perform a calculation, execute one or more system commands, operate machinery or move or collect data. Sometimes the job has one of many other names such as “transaction", “work unit", “submission", all of which mean the same thing. In the system, users need to describe their job requirements. These include job name, required software applications, required data, execution time and resource specifications (CPU count, speed, operating system, physical and virtual memory).

In the system, jobs can also migrate from node to node within the grid environment in order to complete the job if a failure occurs. The collection of jobs that fulfil the whole task is called the grid application.

For example, a grid application can be the simulation of business scenarios such as stock market development that require a large amount of data as well as a high demand for computing resources in order to calculate and handle the great number of variables and their effects [1]. The grid infrastructure provides different kinds of support to a wide range of applications which can be categorized as follows Distributed supercomputing, High- throughput computing, On-demand computing, Data-intensive computing, Collaborative computing, Multimedia computing [2].

The paper is organized as follows. In the following section, background and related work is introduced. In the third section, architecture for the proposed scheme is proposed. In the fourth section, job scheduling algorithm is presented. The fifth section is experimental results followed by conclusion, future scope and the last section is references.

II. R

ELATED WORK

[image:1.595.318.515.615.744.2]

A grid is a collection of nodes connected via a network and managed by a resource broker. It promotes the sharing of services, computing power and resources such as disk storage databases and software applications. A node is the most basic component in grid computing. It is a collection of work units that can be shared and that can provide some capabilities. The grid nodes usually differ in speed, capacity, architecture and operating systems. Basic Grid Model is discussed in [3]. Various types of Grids are discussed in [4] [5]. Novel method of modeling job execution on Grid compute clusters is discussed in [6]. Different types of scheduling and structures are shown in [7].

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International Journal of Emerging Technology and Advanced Engineering

463

III. P

ROPOSED

A

RCHITECTURE

A grid scheduling architecture is described in Fig 2. User first login with a genuine username and password. After successful authentication, the job is collected by job collector. The Job collector maintains all the resource requirement of the jobs. Then global scheduler schedules the job according with the algorithm used like FCFS, resources. When the job is finished, the user is informed. Grid Resource Database maintains all the basic details about the nodes like CPU frequency, SJF, etc. Job of resource discovery is to find suitable nodes for the execution of job that is ready to execute.

Once the resource list has been assembled, the optimal resources that meet the user's requirements such as cost are selected from it. Once the job and resources have been selected, input job is transferred to and run on the number of sub processors, RAM, IP Address and Available CPU Resource(ACR). ACR=(frequency of CPU * CPU idle time)/100

[image:2.595.82.524.278.719.2]

Security is an important requirement for grid computing. In any grid environment there must be mechanisms to provide security, including authentication, authorization and data encryption. The proposed architecture has all the necessary securities required like authentication as shown in the figure 2

Figure 2: Proposed Grid Architecture

GRID DATABASE RECOURCE

N1

N2

Nn

LOCAL SCHEDULER

USER SELECTS THE NODE WHERE APPLICATION IS TO BE EXECUTED

RESOURCE DISCOVERY

SCHEDULER

JOB COLLECTOR

AUTHENTICATION

USER

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International Journal of Emerging Technology and Advanced Engineering

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P

ROPOSED

S

CHEDULING

M

ODEL

NODE 1

USER

[image:3.595.79.504.186.452.2]

NODE N

Figure 3: Scheduling Model

A node is the most basic component in grid computing. It is a collection of work units that can be shared and that can provide some capabilities. The grid nodes usually differ in speed, capacity, architecture and operating systems. Communication between nodes is achieved via network capabilities such as LAN and WAN Nodes may be identified as computational, storage and network resources. They also share services, computing power and other resources such as disk storage database and software applications. They are under the control of different administrative domains with different levels of security. Grid computing is a way to share computing resources [8]. Users with genuine username and password login with the Grid system. They submit their applications in the Global Queue. User can then check which node is best suited for the job (which is ready to execute). Once the node is selected user can select the particular processor within the node where he wants his job to be executed depending upon CPU speed, start and end time of other jobs, RAM and other parameters. Algorithm for job scheduling is:

STEP 1: Authentication of User

STEP 2: User loads the job into the Global Queue STEP 3: User selects the node where the job is to be executed

STEP 4: User selects the resource where the job is to executed

STEP 5: Job is executed or loaded in the Queue if the resource is not free

STEP 6: User gets the output

V. E

XPERIMENTAL RESULTS

The experiment is carried by creating our own simulator in Java. Our simulator consists of 4 nodes having 3 processors each. The load on each processor is calculated using table 1.

Each processor has a specification of Intel(R) Pentium(R) Dual CPU T2390 @1.86GHz 1.87 GHz, RAM of 2.00 GB, System type 64-bit Operating System.

Figure 4 shows the output on the console when scheduling starts. Simulator calculates the total load on each processor within the node and checks if another node is available at the same time with less node or not. At this stage the user can see the available nodes.

USER 1

L.Q USER

P11

P12

P13

P21

P22

P23

USER 2

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International Journal of Emerging Technology and Advanced Engineering

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User can check the details like which processor in the node is lightly loaded and can select the required processor for the execution of his application.

Table 1: Minimum Load on the node

Node No

Load of Node

Load of P1

Load of P2

Load of P3

Total load of Node

1 30 59 41 130

2 46 54 35 135

Figure 4: Selection of Node

VI. C

ONCLUSION

Grid computing helps IT enterprises use various techniques to optimize and secure application performance in a cost-effective manner. Grid computing systems are the latest computing environments and have been gaining popularity for the past few years. Grid can be considered as extensions of distributed computing systems in which their number and heterogeneity are much higher.

Grid providers often have several powerful servers and resources in order to provide appropriate services for their users but grid is at risk similar to other Internet-based technology. The model we have proposed is the working configuration eliminates the selection of processor by Grid. In the model user can select the processor where he wants the job to be execute. Better job scheduling is the basic need to achieve maximum throughput with the available computing resources.

VII. F

UTURE

W

ORK

The future work will focus on the simulator extension adding SAN techniques and further refinement of energy models used in the simulated components. The dream of grid computing is to create a single grid that can operate as one vast computational resource. There is really no telling how far grid computing can go. As Grid computing becomes more wide-spread, energy efficiency will become more important.

After the advances made in distributed system design, collaborative environments, high performance computing and high throughput computing, the Grid is the logical next step [9]. Grid computing can be used in many areas like [10]. The key to successful grid computing initiatives is achieving a balance between the business benefits and the hidden potential risks which can impact efficacy. Enterprises like IBM, HP, and Oracle are trying to set up a system that will use resources in multiple parts of a company to support workload that dynamically connect the computing at one place with data in another place [11].

Sony has grid-enabled its PlayStation 3 for movie-like graphics [12]. Sun Microsystems is working on Grid that promises to make purchasing computer time over a network as easy as buying electricity and water [12]. Finance industries are also helped with the Grid environment as it reduces the risk involved, improves wealth management, trading analytics [13]. Grids are well suited for complex scientific work in virtual organizations [14]. Benefits of Grid computing are discussed in [15].

Load balancing and fault tolerant measure are an important issue in Grid Computing that are not discussed in this paper. This area is an interesting direction for future research.

R

EFERENCES

[1] http://my.safaribooksonline.com/book/operating systems-and-server-administration/grid-computing/

0738453331/application-architecture-consideration s/ch03lev1sec2

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[3] Raksha Sharma, Vishnu Kant Soni, Manoj Kumar Mishra, Prachet Bhuyan, World Academy of Science, Engineering and Technology 64 2010 “ A Survey of Job Scheduling and Resource Management in Grid Computing ”

[4] Mr. Rakesh Kumar, Navjot Kaur “ Job Scheduling in Grid Computers ”

[5] The Grid Computing Weblog

“http://thegridweblog.blogspot.in/2005/10/types-of -grids.html ”

[6] Anne Benoit, Murray Cole, Stephen Gilmore and Jane Hillston “Enhancing the effective utilisation of Grid clusters by exploiting on-line performability analysis ” [7] Volker Hamscher, Uwe Schwiegelshohn, Achim Streit,

and Ramin Yahyapour “ Evaluation of Job-Scheduling Strategies for Grid Computing ”

[8] Resource Sharing

http://www.e-sciencecity.org/EN/gridcafe/resource -sharing.html

[9] The Future Of Grid Computing

http://www.eu-datagrid.org/the-future-of-grid-com puting.htm

[10] Grid Applications and application support:

http://sfx.cceu.org.cn/cgi-bin/tgxx.cgi?issn=0167-7 39X [11] Expert charts future for grid computing

http://searchcio.techtarget.com/news/895039/Expert-charts-future-for-grid-computing

[12] The Future in Grid Computing

http://betanews.com/2005/02/21/interview-the-futu re-in-grid-computing/

[13] Overcoming Complexity and Security Issues http://www.xtalks.com/gridcomputing.ashx

[14] Grid Computing and the Future of Cloud Computing

“http://www.enterprisestorageforum.com/outsourcing/feat ures/article.php/3859956/Grid-Computing-and-the-Future-of-Cloud-Computing.htm ”

[15] Grid Computing: the Benefits