2012an20

Dynamic Load Balancing in Grid Computing withMulti -Agent System Integration by Using Tree

Structure

A Report submitted for seminar assignment

M.Tech.

in

ADVANCED NETWORK

by

VISHNU KUMAR PRAJAPATI - (2012AN20)

ABV INDIAN INSTITUTE OF INFORMATION

TECHNOLOGY AND MANAGEMENT

GWALIOR-474 010

2013

Contents

1 INTRODUCTION 3

1.1 Historical Background of the Grid Computing . . . . . . . . . . . . . . . 3

1.2 Load Balancing in Grid Environment . . . . . . . . . . . . . . . . . . . . 3

1.3 Goal of Load Balancing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.4 Type of load balancing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2 MOTIVATION 5

3 LITERATURE REVIEW 6

3.1 Dynamic Load Balancing Policies . . . . . . . . . . . . . . . . . . . . . . 6

3.2 Multi-Agent System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

3.3 Grid Computing Service Architecture . . . . . . . . . . . . . . . . . . . . 7

3.4 OBJECTIVES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

4 METHODOLOGY 9

5 POSSIBLE SOLUTIONS 12

6 CONCLUSION 13

1

List of Figures

1 Grid Structure Environment . . . . . . . . . . . . . . . . . . . . . . . . . 6

2 Grid Computing Service Layered Architecture . . . . . . . . . . . . . . . 8

3 Comparison between Existing policy and proposed policy . . . . . . . . . 9

4 Grid Structure Environment . . . . . . . . . . . . . . . . . . . . . . . . . 10

5 Combining Architecture for Grid Load Balancing with service model . . . 12

2

1 INTRODUCTION

The Grids can be defined as services that shares computer power and data storage

capacity over the Internet and Intranet. It is not just simple communication between

computers but it aims finally to turn the global network of computer into a huge compu-

tational resource. It can coordinate those resources which are not subject to centralized

control. The grid is to use standard, open, general-purpose protocols and interfaces.

The grid is to deliver nontrivial Quality of Service. A computational grid environment

behaves like a virtual organization consisting of distributed resources. A Virtual Orga-

nization is a set of individuals and institutions defined by a definite set of sharing rules

like what is shared, who is allowed to share, and the conditions under which the sharing

takes place. A number of Virtual Organizations exist such as the application service

providers, storage service providers, but they do not completely satisfy the requirements

of the grid. Grid computing focuses on dynamic and cross-Organizational sharing, it

enhances the existing distributed computing technologies.

1.1 Historical Background of the Grid Computing

Technology yearNetworked operating systems 1979-81Distributed operating systems 1988-91Heterogeneous computing 1993-93Parallel and distributed computing 1995-96Grid computing 1998

Table 1: history of grid computing

1.2 Load Balancing in Grid Environment

n a Grid environment , there are several Load Balancing techniques such as Random-

ized load balancing, round robin load balancing, dynamic load balancing, hybrid load

balancing, agent based load balancing and multi-agent load balancing . Round robin

and randomized load balancing are simple and easy to implement. Dynamic, hybrid,

agent base and multi-agent based load balancing are going to improvement or new ones

introduced in grid load balancing solution.

1.3 Goal of Load Balancing

The Goal of load balancing is that the workload is fairly distributed among the nodes

and that none of the nodes are overloaded or under loaded. So that the computing power

fully utilize from the multiple hosts without disturbing the user

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1.4 Type of load balancing

there are two types of load balancing strategies called static load balancing and dynamic

load balancing - Static load balancing makes the balancing decision at compile time and

it will remain constant. In dynamic load balancing makes more informative decisions in

sharing the system load based on runtime. the dynamic load balancing provide better

performance compare to static load balancing. Dynamic load balancing classified into

centralized approach and decentralized approach. In Centralized approach is managed

by central controller that has a global view of load information in the system which is

used to decide how to allocate jobs to each other. Another one decentralized approach all

joints nodes are involved in making the load balancing decision. In the grid computing

is the method based on collecting the power of many computers, in order to solve the

large-scale problems; On the other hand, it offers to share hardware and software grid

resources. So that maximizes the overall grid performance. Tree base infrastructure is

focusing on the load balancing algorithm for the grid computing services (GCS). The

main goal of the design to submit their computing task simply by having access to our

grid computing service web site(GCSWS)and another objective of GCS to access the

powerful computers or expensive software with very low cost to the our grid users.

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2 MOTIVATION

The distributed computing technology are use to share the resources between the insti-

tutional, by using grid computing it will give more better performance them existing

distributed computing technology. Currently, Grid computing technology can be used to

connect heterogeneous computing resources to each other in a way that user can regard

all of this structure as a single machine on which we can run very highly complex and

massive application programs that require a high processing power and huge volume of

input data. The grid computing systems have improved the throughput and increase the

performance to the individual nodes and whole grid system by using the load balancing.

So the load balancing in the grid system has a big role for utilization of the resource and

reduced the response time.

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3 LITERATURE REVIEW

Decentralize load balancing approach are based on redistribution of tasks among the

available processors. The processors which is overloaded are transfer the tasks to the

under load processors, by using High Level Architecture (HLA) environment. This

process work at the run time, so generally there is none of the nodes are heavily loaded.

3.1 Dynamic Load Balancing Policies

here are four type of load balancing .which consists of Transfer policy, Selection policy,

Location policy and Information policy.

Figure 1: Grid Structure Environment

• Transfer Policy: Transfer Policy should be transfer the load or not and it is based

on various criteria such as workload value and computing Power. If the load

balancing is needed it will sent to the selection policy. if not, the job will process

locally.

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• Selection Policy: The tasks define that it should be Transference or migrated from

overloaded resources (source) to most idle resources (receiver). The decisions made

by selection policy are then directed to the location policy for further process.

• Location Policy: Location Policy are Uses the results of the Selection policy to

find a suitable partner for a Sender or receiver.

• Information Policy: In the information policy, the worked as what workload infor-

mation to be collected, when it is to be collected and from where it is collected.

3.2 Multi-Agent System

An Agent is a computer system that has a capability of taking independent action on

behalf of its user or owner. The Multi-agent system hold several characteristics such as

autonomy, local views, cooperation, social ability, reactivity, proactive, goal oriented and

decentralized. Multi-agent system consists of communication layer, coordination layer

and local management layer. The communication layer provides an agent with interfaces

to heterogeneous networks and operating systems. It will receive the request and then

explain and submit to the coordination layer to decide the suitable action according to

its own knowledge. The local management layer performs functions of an agent for local

grid load balancing. A Multi-agent system is composed of multiple intelligent agents that

have the ability to interact or communicate, collaborate and negotiate among them.

3.3 Grid Computing Service Architecture

Grid computing service (GCS) is allows to submit their computing tasks along with

required hardware or software resources. It allocates tasks to the available resources

and then executes the tasks. After execution, grid computing service will reply to the

user and send back the results.

As the following figure, GCS have four layers Web Service Task Submission layer,

Grid Resource Monitoring layer, Task Allocation and Load balancing layer and Grid

Task Execution layer. In the Web Service Task submission layer, work with user tasks

submission and their requirements (resources and quality of service information). In the

Grid Resource Monitoring layer, need to monitor those resources which are underutilized

or overloaded. Each grid entry point is called a Grid Agent Manager (GAM).in the load

balancing layer, there are two level of load balancing which are worker layer and GAM

level load balancing. And the last Layer is Grid Task Execution layer, it is mainly

responsible to perform tasks executions and also update the status of the hardware and

software resources at a given computing unit.

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Figure 2: Grid Computing Service Layered Architecture

3.4 OBJECTIVES

To reduced the communication between worker nodes and Leader nodes and also between

the Leader nodes. So that reduced the overhead compare to pool based approach and do

the efficiently load balancing process. The main objective is to increase the performance

of the Grid system, maximize the overall system throughput, minimize the response time

and allow the good grid resources utilization.

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4 METHODOLOGY

Figure 3: Comparison between Existing policy and proposed policy

The information policy has making a decision and lot of contributions. We can say

that information policy has a big implication on performance in grid computing through

accurate, efficient and suitable for taking a decision. The transfer policy and selection

policy are combined which is known as migration policy. By combining these policies,

reduced the internal communication between policies in the agent as showing the above

figure. Agent have a multifunction capabilities due to the role of embedded them. It will

be two statuses which are leader of the computing element and worker of the computing

element. The agent is automatic determined statuses or role themselves. If the agent

is leader, it wills auto-notify the workload system manager. It also has the capability

to communicate among the agent and exchange the information. The main work of the

migration policy is receiving the data or if already holding the data, it will analyze the

load and decide where process is locally or remotely. The decision made by the migration

policy will submit to the location policy for further processing. Here the load balancing

function work globally or locally. The load balancing decision making by the workload

system manager which sits at top of the grid as described in the following figure.

The workload system manager makes the decision based on computing element power

or index and also to allocate the correct load value the correct computing elements which

are the leaders in the local grid. Then, the computing element leader will decide how

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Figure 4: Grid Structure Environment

to distribute the load according to the worker node available computing power. Each

worker node has the capability to auto-notify to the leader on itself computing power

information, so that reduce the communication overhead compare to polling method.

Load Balancing Algorithms:

• APC=PC*L GPC =is the maximum processing capacity (tasks/seconds) at grid

threshold utilization. So, AVGPC=GPC-APC All the above parameter are dy-

namic nature. APC=Actual Processing Capacity, GPC-Grid Processing Capacity,

AVGPC=Available Grid Processing capacity.

• Worker Level Load Balancing: If N is the number of received tasks at a given

GAM(General Agent Manager), we define the following parameters-

Where TPC= Total Processing Capacity, TAPC =Total Actual Processing Capac-

ity.

• GAM level Load Balancing: The GAM have to managed by tree structure in grid,

the tree structure is selected to ensure the scalability (add/remove GAMS) and

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minimize the communication between the GAMS. it also ensure that only one load

balancing operation work at a time, so that ignore the inconsistency or wrong load

balancing operations. by circulating the token message between GAM in the whole

tree for exchange the information. The token message contains the global view of

the grid system. it contain the following information about each GAM. Manager

ID ,Total Available Processing Capacity(TAPC) of the GAM, status, Neutral(N)

,Receiver(R) and Sender(S) .

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5 POSSIBLE SOLUTIONS

Figure 5: Combining Architecture for Grid Load Balancing with service model

The user can be submitting a task to the grid web service. The user may choose

the deferent web browser though web server to submit the task and also responsible

to forward the request to the Grid Resource Monitoring Layer. The Grid Resource

Monitoring Layer do the monitoring in heterogeneous resources like different Processing

Power, different Internet speed, and the systems are in distributed manner, after that this

layer work the central Workload system Manager for doing the accurate load balancing

and task allocation (as by Bakri Yahaya ijincaa,2011) and forward the process to the next

layer for execution of task. Workload system Manager have a Multi- Agent, An agent

will determined what they are and automatically turn themselves into the determined

status or role. If the agent is a leader, it will auto-notify the workload system manager.

The agent itself has the capabilities to communicate among the agent and performs the

information exchange. The global load balancing decision will be made by Workload

system manager and the local load balancing will be made by leaders. The Grid Task

Execution layer work as existing architecture (as by Abderezak Touzene IJCSI 2011).

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6 CONCLUSION

In the Tree base architecture for grid computing services and Multi-agent system will

reduced the internal communication. We also apply the load balancing policy to reduce

the communication between policies. The workload system maintains the consistency

and removed the wrong load balancing. By combining the policy method and grid

computing Service Architecture we can achieve the maximum throughput, minimize the

overall tasks response time and finding fault. In future we can apply the fault tolerance

in the grid load balancing strategy.

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REFERENCE

1. Sakadasariya Achyut R,”Survey of Resource and Job Management for Load Bal-ancing In Grid Computing”. of the IJISME ISSN: 2319-6386 vOLUME-1 iSSUE-3,2013.

2. S. Gokuldev, Shahana Moideen,” Global Load Balancing and Fault Tolerant Schedul-ing in Computational Grid”. of the International Journal of Engineering and In-novative Technology (IJEIT) Volume 2, Issue 11, May 2013.

3. Preeti Gulia,Deepika Nee Miku, Analysis and Review of Load Balancing in GridComputing using Artificial Bee Colony, in Proc. of IInternational Journal of Com-puter Applications (0975 8887) Volume 71 No.20, June 2013

4. Leyli Mohammad Khanli and Behnaz Didevar, A New Hybrid Load BalancingAlgorithm in Grid Computing Systems, IJCSET, E-ISSN: 2044 - 6004 ., 2011 .

5. Bakri Yahaya, Rohaya Latip, Mohamed Othman, and Azizol Abdullah, DynamicLoad Balancing Policy with Communication and Computation Elements in GridComputing with Multi-Agent System Integration, International Journal on NewComputer Architectures and Their Applications (IJNCAA) 1(3): 757-765 TheSociety of Digital Information and Wireless Communications, 2011.

6. Abderezak Touzene, Sultan Al-Yahai, Hussien AlMuqbali, Abdelmadjid Bouab-dallah, Yacine Challal, Performance Evaluation of Load Balancing in HierarchicalArchitecture for Grid Computing Service Middleware,IJCSI International Journalof Computer Science Issues, Vol. 8, Issue 2, March 2011.

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