CHAPTER 3 LOAD BALANCING MECHANISM USING MOBILE AGENTS

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "CHAPTER 3 LOAD BALANCING MECHANISM USING MOBILE AGENTS"

Transcription

1 48 CHAPTER 3 LOAD BALANCING MECHANISM USING MOBILE AGENTS 3.1 INTRODUCTION Load balancing is a mechanism used to assign the load effectively among the servers in a distributed environment. These computers work together so that in many respects it can be viewed as a single computer. The load balancing operations are transparent to the user. The existing work reveals that for effective load balancing, comprehensive and current load information should be available. In the pursuit of achieving the above, excessive bandwidth of the network is utilized in the existing methods for collection and exchange of load information. There exists contention between collecting load information and dispatching user request under the limited bandwidth condition. The limited availability of bandwidth becomes a restriction in carrying out other useful work. Also in the existing system, when a mobile agent fails, the reliability of the load balancing mechanism is reduced and thereby increasing the possibility of system overload. A load balancing strategy is proposed in this work which streamlines the bandwidth usage for effective utilization of resources. This

2 49 proposed method uses a mobile agent based solution to the problem of load distribution in a dispatcher based client/server environment. This proposed system of Load Distribution by dynamically Fixing input to the server using Mobile agent (LDFM) addresses the problem of excessive utilization of network bandwidth for collection and exchange of load information. The proposed work also provides solution for the failure of mobile agents by monitoring its status and creating a new agent, thus leading to improved reliability of the load balancing mechanism. 3.2 LOAD DISTRIBUTION BY DYNAMICALLY FIXING INPUT TO THE SERVER USING MOBILE AGENT (LDFM) SYSTEM The proposed system consists of a set of clients and a network of servers. The LDFM framework considers two worlds, namely: Client world and server world. The client world is an aggregation of all the clients in the physical world and the server world is an aggregation of the web servers or replicas in a cluster as shown in Figure The data structure for qitem is organized as class qitem { int load; int ipaddr [] = new int [4]; } qitem [ ] mmu_queue = new qitem [L]; The data structure for ipdata is defined as class ipdata { char servr_id [ ] = new char[l]; int ipaddr [ ] = new int [4]; int rank; } ipdata [ ] dispatcher_table = new ipdata [L];

3 50 In the proposed system, the client world communicates with the server world through the dispatcher. The number of servers in the multi server environment is configured as fixed entity L. The system deploys two data structures namely qitem and ipdata. qitem is used for collecting the load information from the server and ipdata for organizing, ranking and distributing the requests to the server. Figure 3.1 Client-Server Dispatcher based System

4 51 The dispatcher receives the HTTP request from the client world and sends it to the server world according to the IP address available in the dispatch table. The dispatcher table in the dispatcher is updated by the Mobile Management Unit (MMU). The purpose of the mmu_queue is to receive the server load information according to the IP address of the server. The MMU uses this information to sort the load of the servers, in ascending order. Once the server loads are sorted, it is used to update the dispatch table. The dispatch table now contains the IP address of the servers according to the ascending order of server load. The least loaded server will be the first entry in the table and the heavily loaded server will be the last entry in the table. The load information is proactively collected and used to dynamically update the table. The dispatcher table is shown in Table 3.1. Table 3.1. Dispatcher table Server ID IP address Rank P Q R The dispatcher is a front end machine having a virtual IP address and has a dispatcher table and a Mobile Management Unit (MMU). The server to which the http request is to be sent for processing by the dispatcher is available in the dispatcher table.

5 Assigning Request Identification Number The cyclic property of the mod function is used for assigning the Request Identification Number(RID). Let n be a positive integer and let m be any integer. Then there exist unique integers q and r such that m = qn + r, 0 r < n. Here q is called the quotient and r the remainder when m is divided by n. i.e. m mod n. When a range of values is assigned to m and the mod operation is carried out, then the remainder value will be cyclic in the range 0<=r<n. Consider n=5 and m=1, 2,3,4,5,6,7,8,9,10,11,12,13,14,15,16, 17,18,19,20. The possible values for mod operation will be 1,2,3,4, or 0. When the HTTP requests sent by the user arrives at the dispatcher the dispatcher increments the count value by one. The RID is generated for each request using the mod function. The HTTP request is associated with a RID. The mod function computes the RID using count value and the number of servers available in the distributed system for serving HTTP requests from the user. The RID value is computed as RID = count mod (L+1). The RID values assigned will be cyclic in nature Processing the Request The HTTP request received from the user is sent to the dispatcher. The dispatcher associates the request with the RID and sends it to a server. The dispatcher uses the rank of the server for distributing the HTTP requests. The HTTP request and the associated RID are received at the server. When the request with RID is received by the server, the incoming RID is compared with the previous RID in the queue. If the incoming RID is greater than the

6 53 previous RID then the current load of the server is communicated to the MMU. Initially the requests are distributed in a round robin fashion as the ranks of all the servers are assigned with a value 1, the highest rank. As the HTTP requests arrive at the server queue it is processed in sequential fashion on a first come first served basis as long as the server is not overloaded and the processing of requests proceeds normally. If the server is overloaded then requests are held up in the queue for processing and the processing of the requests will be delayed. In order to avoid this delay, it is necessary to detect the overload condition of the server. For this purpose the incoming RID is compared with the previous RID in the queue. In the normal operating conditions of the server, the incoming RID will be lesser than the previous RID. However under overload conditions of the server, this condition will fail and at this point of time the mobile agent communicates the server load information to the MMU. Consider the normal arrival pattern of the HTTP request at the servers where the number of servers here is assumed to be four as shown Figure 3.2. The RID have a periodicity equal to the number of servers plus one in the distributed environment. The periodicity of RID triggers the mobile agent to send the server load information on a periodic basis. The mobile agent in the server will transfer load information periodically which is equal to the number of servers in the distributed environment. However when the servers become overloaded the periodicity of information transfer by the mobile agent is altered depending upon the update of dispatch table. The HTTP request is transferred based on the rank of server in the table.

7 54 Server RID Figure 3.2 RID Pattern Ranking of Servers The MMU initiates the mobile agent to the server. The mobile agent in the server monitors the load on the server to which it is associated. The mobile agent in the server communicates the load information to the MMU only when the RID of the incoming request is greater than the RID in the queue.the above condition ensures that any two mobile agent will not communicate to the MMU simultaneously. This helps in avoiding unnecessary usage of network bandwidth for communicating load information between the mobile agent and MMU. The MMU ranks the server according to the load information received from the mobile agent The MMU is responsible for the mobile agent and ensures that it is active and has not crashed. The mobile agent periodically sends an I AM ALIVE (IAA) signal to the MMU. The MMU based on the IAA signal checks the status of mobile agent and creates a new mobile agent when needed. The

8 55 MMU sets the time out timer on receipt of IAA. When the time out occurs a new mobile agent is initiated from the MMU for the server Update of Dispatcher Table Each server in the server world has a mobile agent initiated from the MMU so that polling of server by the mobile agent is avoided. This reduces the latency in collecting the load information. At any point of time only one mobile agent will be communicating the load information to the MMU. Initially the dispatcher assigns the user request with RIDs to the servers 1, 2, 3.N in a round robin fashion. This process continues as long as the incoming RID is lesser than the previous RID. Due to the cyclic property of the mod function the above condition will fail, initiating the mobile agent. This arrangement enables staggered communication between the mobile agent and the MMU. The mobile agent collects the load of the server proactively and sends it to the MMU. The mobile management unit after receiving the information from the mobile agent computes and updates the dispatcher table with IP addresses along with ranks 1, 2, 3 of N servers with the lightest load. The ranking of the server in the dispatch table will be different every time the load information is received and the dispatch table is updated dynamically. The table is used by the dispatcher for allocation of server for new HTTP request Formal Presentation of the Algorithm The algorithm is event based. The event can be one of the following 1. Receiving HTTP request from client at dispatcher

9 56 2. Receiving request with RID at server from dispatcher 3. Receiving server load from mobile agent at dispatcher running MMU 4. Receiving I Am Alive (IAA) signal from mobile agent at dispatcher running MMU 5. Receiving server response at dispatcher A set of instructions corresponding to each event is executed when the event occurs. 1. On receiving HTTP request from client at dispatcher count = count+1 RID = count mod (L+1) send request with RID to server 2. On receiving request with RID at server from dispatcher if (incoming RID > previous RID in the queue) send load of server using mobile agent to dispatcher running Mobile Management Unit (MMU) process the request 3. On receiving server load from mobile agent at dispatcher running MMU Accept the load of server Compute the rank of server Update the dispatcher table according to the rank of server

10 57 4. On receiving I Am Alive (IAA) signal from mobile agent at dispatcher running MMU Set time out timer On time out at MMU create mobile agent move mobile agent to corresponding server 5. On receiving server response at dispatcher Send server response to corresponding client 3.3 PERFORMANCE ANALYSIS The performance of the proposed system is analyzed through simulation. The main objective of the simulation is comparing the performance of the proposed system with the existing system. Among the several parameters, system throughput i.e. the total number of requests processed per second is considered. The simulation was performed by the number of servers (L) set to 30. The request from the user will have uniform execution time. The servers are heterogeneous, having varying CPU capability and memory capacity. The simulation was performed and the system throughput was measured by gradually increasing the number of user requests. The experiment was repeated a number of times and the average value is used for evaluation. The system throughput of the server (the total number of requests processed per second) is plotted against the number of requests from client world. The results of the proposed system (LDFM) and the existing system(without LDFM) are shown in Figure 3.3. It was observed that the throughput of the proposed system is better than the existing system.

11 58 System Throughput existing proposed Number of clients Figure 3.3 Comparison of Throughput Impact of Mobile Agent Failure The result also shows a performance degradation when mobile agent failure was simulated. New mobile is created after timeout, when a mobile agent fails. However a performance degradation was observed and this is due to the fact that in the intervening period, the mobile agent is not communicating the load information and the dispatcher table is not updated. The dispatcher table is not updated with the current information of load on the server, resulting in the performance degradation. The same phenomenon was observed in the other works, but the failure condition was not restored the performance was poor.it was observed that in LDFM the performance degradation was temporary until the new agent was restored,but in existing work the degradation was severe as there was no

12 59 inbuilt mechanism to restore the mobile agent. The results are shown in Figure 3.4. System Throughput Number of clients existing proposed Figure 3.4 Throughput with Mobile Agent Faliure The communication overhead in the LDFM and the existing method were compared. It was observed that the communication overhead in LDFM was a constant, whereas in the existing method, it was observed that it was increasing with the number of servers. In LDFM only one mobile agent will communicate with the MMU at any point of time and the possibility of two or more communicating at the same instance is a remote possibility and this has contributed to the low overhead. The increased overhead in the existing work can be attributed to the load collection and update mechanism used.when the servers become overloaded all the overloaded servers try to communicate their load information at the same time resulting in the high overhead. The result of the simulation is shown in Figure 3.5.

13 Network Traffic without LDFM LDFM Number of servers Figure 3.5 Communication Overhead Response time The response time of the existing method is compared with the proposed method and the results are shown in Figure 3.6. It can be observed that the average improvement in response time of the proposed method is 6%. This can be attributed to common overheads like round trip time, double IP address rewriting in both the methods. 2.5 Comparison of response time without LDFM with LDFM Load (% ) Figure 3.6 Response Time

14 CONCLUSION The improvement in performance is attributed to the reduced message complexity of mobile agents. The reduced message complexity compared with other method has contributed to processing more user requests. The reduction in message complexity is achieved by using mobile agent to communicate with the MMU for collection of load information. The mobile agent communicates only when the RID condition fails. The failure of the condition is achieved by the use of mod function. This arrangement helps the mobile agent to communicate always in a sequential manner. In the previous work of Hong et al (2006) the load information was broadcast to all the servers. Also Pao & Chen (2006) have used the advertisement technique to convey the load information to the dispatcher from the backend servers. The communication is not at all regulated. In the experiment there is no distribution of job request from the one queue to another. The load information was proactively collected, ranked and dispatcher table updated. The sequence of distribution of user request by the dispatcher to the server is altered whenever the dispatcher table is updated. The next chapter 4 deals with the challenges faced and the proposed methods to handle Load Balancing in a peer to peer environment.

Load Balancing in Fault Tolerant Video Server

Load Balancing in Fault Tolerant Video Server Load Balancing in Fault Tolerant Video Server # D. N. Sujatha*, Girish K*, Rashmi B*, Venugopal K. R*, L. M. Patnaik** *Department of Computer Science and Engineering University Visvesvaraya College of

More information

ELIXIR LOAD BALANCER 2

ELIXIR LOAD BALANCER 2 ELIXIR LOAD BALANCER 2 Overview Elixir Load Balancer for Elixir Repertoire Server 7.2.2 or greater provides software solution for load balancing of Elixir Repertoire Servers. As a pure Java based software

More information

High Availability and Clustering

High Availability and Clustering High Availability and Clustering AdvOSS-HA is a software application that enables High Availability and Clustering; a critical requirement for any carrier grade solution. It implements multiple redundancy

More information

The International Journal Of Science & Technoledge (ISSN 2321 919X) www.theijst.com

The International Journal Of Science & Technoledge (ISSN 2321 919X) www.theijst.com THE INTERNATIONAL JOURNAL OF SCIENCE & TECHNOLEDGE Efficient Parallel Processing on Public Cloud Servers using Load Balancing Manjunath K. C. M.Tech IV Sem, Department of CSE, SEA College of Engineering

More information

Efficient Parallel Processing on Public Cloud Servers Using Load Balancing

Efficient Parallel Processing on Public Cloud Servers Using Load Balancing Efficient Parallel Processing on Public Cloud Servers Using Load Balancing Valluripalli Srinath 1, Sudheer Shetty 2 1 M.Tech IV Sem CSE, Sahyadri College of Engineering & Management, Mangalore. 2 Asso.

More information

Load Balancing in Distributed System. Prof. Ananthanarayana V.S. Dept. Of Information Technology N.I.T.K., Surathkal

Load Balancing in Distributed System. Prof. Ananthanarayana V.S. Dept. Of Information Technology N.I.T.K., Surathkal Load Balancing in Distributed System Prof. Ananthanarayana V.S. Dept. Of Information Technology N.I.T.K., Surathkal Objectives of This Module Show the differences between the terms CPU scheduling, Job

More information

Abstract. 1. Introduction

Abstract. 1. Introduction A REVIEW-LOAD BALANCING OF WEB SERVER SYSTEM USING SERVICE QUEUE LENGTH Brajendra Kumar, M.Tech (Scholor) LNCT,Bhopal 1; Dr. Vineet Richhariya, HOD(CSE)LNCT Bhopal 2 Abstract In this paper, we describe

More information

Keywords Load balancing, Dispatcher, Distributed Cluster Server, Static Load balancing, Dynamic Load balancing.

Keywords Load balancing, Dispatcher, Distributed Cluster Server, Static Load balancing, Dynamic Load balancing. Volume 5, Issue 7, July 2015 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com A Hybrid Algorithm

More information

Running a Workflow on a PowerCenter Grid

Running a Workflow on a PowerCenter Grid Running a Workflow on a PowerCenter Grid 2010-2014 Informatica Corporation. No part of this document may be reproduced or transmitted in any form, by any means (electronic, photocopying, recording or otherwise)

More information

CHAPTER 5 WLDMA: A NEW LOAD BALANCING STRATEGY FOR WAN ENVIRONMENT

CHAPTER 5 WLDMA: A NEW LOAD BALANCING STRATEGY FOR WAN ENVIRONMENT 81 CHAPTER 5 WLDMA: A NEW LOAD BALANCING STRATEGY FOR WAN ENVIRONMENT 5.1 INTRODUCTION Distributed Web servers on the Internet require high scalability and availability to provide efficient services to

More information

Load Balancing of Web Server System Using Service Queue Length

Load Balancing of Web Server System Using Service Queue Length Load Balancing of Web Server System Using Service Queue Length Brajendra Kumar 1, Dr. Vineet Richhariya 2 1 M.tech Scholar (CSE) LNCT, Bhopal 2 HOD (CSE), LNCT, Bhopal Abstract- In this paper, we describe

More information

A NOVEL RESOURCE EFFICIENT DMMS APPROACH

A NOVEL RESOURCE EFFICIENT DMMS APPROACH A NOVEL RESOURCE EFFICIENT DMMS APPROACH FOR NETWORK MONITORING AND CONTROLLING FUNCTIONS Golam R. Khan 1, Sharmistha Khan 2, Dhadesugoor R. Vaman 3, and Suxia Cui 4 Department of Electrical and Computer

More information

Lecture 3: Scaling by Load Balancing 1. Comments on reviews i. 2. Topic 1: Scalability a. QUESTION: What are problems? i. These papers look at

Lecture 3: Scaling by Load Balancing 1. Comments on reviews i. 2. Topic 1: Scalability a. QUESTION: What are problems? i. These papers look at Lecture 3: Scaling by Load Balancing 1. Comments on reviews i. 2. Topic 1: Scalability a. QUESTION: What are problems? i. These papers look at distributing load b. QUESTION: What is the context? i. How

More information

Fault-Tolerant Framework for Load Balancing System

Fault-Tolerant Framework for Load Balancing System Fault-Tolerant Framework for Load Balancing System Y. K. LIU, L.M. CHENG, L.L.CHENG Department of Electronic Engineering City University of Hong Kong Tat Chee Avenue, Kowloon, Hong Kong SAR HONG KONG Abstract:

More information

CDBMS Physical Layer issue: Load Balancing

CDBMS Physical Layer issue: Load Balancing CDBMS Physical Layer issue: Load Balancing Shweta Mongia CSE, School of Engineering G D Goenka University, Sohna Shweta.mongia@gdgoenka.ac.in Shipra Kataria CSE, School of Engineering G D Goenka University,

More information

Dynamic Adaptive Feedback of Load Balancing Strategy

Dynamic Adaptive Feedback of Load Balancing Strategy Journal of Information & Computational Science 8: 10 (2011) 1901 1908 Available at http://www.joics.com Dynamic Adaptive Feedback of Load Balancing Strategy Hongbin Wang a,b, Zhiyi Fang a,, Shuang Cui

More information

Rackspace Cloud Databases and Container-based Virtualization

Rackspace Cloud Databases and Container-based Virtualization Rackspace Cloud Databases and Container-based Virtualization August 2012 J.R. Arredondo @jrarredondo Page 1 of 6 INTRODUCTION When Rackspace set out to build the Cloud Databases product, we asked many

More information

Comparative Study of Load Balancing Algorithms

Comparative Study of Load Balancing Algorithms IOSR Journal of Engineering (IOSRJEN) e-issn: 2250-3021, p-issn: 2278-8719 Vol. 3, Issue 3 (Mar. 2013), V2 PP 45-50 Comparative Study of Load Balancing Algorithms Jyoti Vashistha 1, Anant Kumar Jayswal

More information

An Approach to Load Balancing In Cloud Computing

An Approach to Load Balancing In Cloud Computing An Approach to Load Balancing In Cloud Computing Radha Ramani Malladi Visiting Faculty, Martins Academy, Bangalore, India ABSTRACT: Cloud computing is a structured model that defines computing services,

More information

A Link Load Balancing Solution for Multi-Homed Networks

A Link Load Balancing Solution for Multi-Homed Networks A Link Load Balancing Solution for Multi-Homed Networks Overview An increasing number of enterprises are using the Internet for delivering mission-critical content and applications. By maintaining only

More information

2. Research and Development on the Autonomic Operation. Control Infrastructure Technologies in the Cloud Computing Environment

2. Research and Development on the Autonomic Operation. Control Infrastructure Technologies in the Cloud Computing Environment R&D supporting future cloud computing infrastructure technologies Research and Development on Autonomic Operation Control Infrastructure Technologies in the Cloud Computing Environment DEMPO Hiroshi, KAMI

More information

International Journal Of Engineering Research & Management Technology

International Journal Of Engineering Research & Management Technology International Journal Of Engineering Research & Management Technology March- 2014 Volume-1, Issue-2 PRIORITY BASED ENHANCED HTV DYNAMIC LOAD BALANCING ALGORITHM IN CLOUD COMPUTING Srishti Agarwal, Research

More information

Cognos8 Deployment Best Practices for Performance/Scalability. Barnaby Cole Practice Lead, Technical Services

Cognos8 Deployment Best Practices for Performance/Scalability. Barnaby Cole Practice Lead, Technical Services Cognos8 Deployment Best Practices for Performance/Scalability Barnaby Cole Practice Lead, Technical Services Agenda > Cognos 8 Architecture Overview > Cognos 8 Components > Load Balancing > Deployment

More information

A Load Balancing Algorithm based on the Variation Trend of Entropy in Homogeneous Cluster

A Load Balancing Algorithm based on the Variation Trend of Entropy in Homogeneous Cluster , pp.11-20 http://dx.doi.org/10.14257/ ijgdc.2014.7.2.02 A Load Balancing Algorithm based on the Variation Trend of Entropy in Homogeneous Cluster Kehe Wu 1, Long Chen 2, Shichao Ye 2 and Yi Li 2 1 Beijing

More information

An Energy Efficient Server Load Balancing Algorithm

An Energy Efficient Server Load Balancing Algorithm An Energy Efficient Server Load Balancing Algorithm Rima M. Shah 1, Dr. Priti Srinivas Sajja 2 1 Assistant Professor in Master of Computer Application,ITM Universe,Vadodara, India 2 Professor at Post Graduate

More information

1. Comments on reviews a. Need to avoid just summarizing web page asks you for:

1. Comments on reviews a. Need to avoid just summarizing web page asks you for: 1. Comments on reviews a. Need to avoid just summarizing web page asks you for: i. A one or two sentence summary of the paper ii. A description of the problem they were trying to solve iii. A summary of

More information

Load Balancing using DWARR Algorithm in Cloud Computing

Load Balancing using DWARR Algorithm in Cloud Computing IJIRST International Journal for Innovative Research in Science & Technology Volume 1 Issue 12 May 2015 ISSN (online): 2349-6010 Load Balancing using DWARR Algorithm in Cloud Computing Niraj Patel PG Student

More information

A Review on Load Balancing In Cloud Computing 1

A Review on Load Balancing In Cloud Computing 1 www.ijecs.in International Journal Of Engineering And Computer Science ISSN:2319-7242 Volume 4 Issue 6 June 2015, Page No. 12333-12339 A Review on Load Balancing In Cloud Computing 1 Peenaz Pathak, 2 Er.Kamna

More information

Database Replication with MySQL and PostgreSQL

Database Replication with MySQL and PostgreSQL Database Replication with MySQL and PostgreSQL Fabian Mauchle Software and Systems University of Applied Sciences Rapperswil, Switzerland www.hsr.ch/mse Abstract Databases are used very often in business

More information

Resource Utilization of Middleware Components in Embedded Systems

Resource Utilization of Middleware Components in Embedded Systems Resource Utilization of Middleware Components in Embedded Systems 3 Introduction System memory, CPU, and network resources are critical to the operation and performance of any software system. These system

More information

Computer Networks. Chapter 5 Transport Protocols

Computer Networks. Chapter 5 Transport Protocols Computer Networks Chapter 5 Transport Protocols Transport Protocol Provides end-to-end transport Hides the network details Transport protocol or service (TS) offers: Different types of services QoS Data

More information

WHITE PAPER Guide to 50% Faster VMs No Hardware Required

WHITE PAPER Guide to 50% Faster VMs No Hardware Required WHITE PAPER Guide to 50% Faster VMs No Hardware Required WP_v03_20140618 Visit us at Condusiv.com GUIDE TO 50% FASTER VMS NO HARDWARE REQUIRED 2 Executive Summary As much as everyone has bought into the

More information

Process Scheduling CS 241. February 24, 2012. Copyright University of Illinois CS 241 Staff

Process Scheduling CS 241. February 24, 2012. Copyright University of Illinois CS 241 Staff Process Scheduling CS 241 February 24, 2012 Copyright University of Illinois CS 241 Staff 1 Announcements Mid-semester feedback survey (linked off web page) MP4 due Friday (not Tuesday) Midterm Next Tuesday,

More information

Multilevel Communication Aware Approach for Load Balancing

Multilevel Communication Aware Approach for Load Balancing Multilevel Communication Aware Approach for Load Balancing 1 Dipti Patel, 2 Ashil Patel Department of Information Technology, L.D. College of Engineering, Gujarat Technological University, Ahmedabad 1

More information

Deploying Load balancing for Novell Border Manager Proxy using Session Failover feature of NBM 3.8.4 and L4 Switch

Deploying Load balancing for Novell Border Manager Proxy using Session Failover feature of NBM 3.8.4 and L4 Switch Novell Border Manager Appnote Deploying Load balancing for Novell Border Manager Proxy using Session Failover feature of NBM 3.8.4 and L4 Switch Bhavani ST and Gaurav Vaidya Software Consultant stbhavani@novell.com

More information

International Journal of Scientific & Engineering Research, Volume 6, Issue 4, April-2015 36 ISSN 2229-5518

International Journal of Scientific & Engineering Research, Volume 6, Issue 4, April-2015 36 ISSN 2229-5518 International Journal of Scientific & Engineering Research, Volume 6, Issue 4, April-2015 36 An Efficient Approach for Load Balancing in Cloud Environment Balasundaram Ananthakrishnan Abstract Cloud computing

More information

A Survey on Load Balancing and Scheduling in Cloud Computing

A Survey on Load Balancing and Scheduling in Cloud Computing IJIRST International Journal for Innovative Research in Science & Technology Volume 1 Issue 7 December 2014 ISSN (online): 2349-6010 A Survey on Load Balancing and Scheduling in Cloud Computing Niraj Patel

More information

APPENDIX 1 USER LEVEL IMPLEMENTATION OF PPATPAN IN LINUX SYSTEM

APPENDIX 1 USER LEVEL IMPLEMENTATION OF PPATPAN IN LINUX SYSTEM 152 APPENDIX 1 USER LEVEL IMPLEMENTATION OF PPATPAN IN LINUX SYSTEM A1.1 INTRODUCTION PPATPAN is implemented in a test bed with five Linux system arranged in a multihop topology. The system is implemented

More information

Fair Scheduling Algorithm with Dynamic Load Balancing Using In Grid Computing

Fair Scheduling Algorithm with Dynamic Load Balancing Using In Grid Computing Research Inventy: International Journal Of Engineering And Science Vol.2, Issue 10 (April 2013), Pp 53-57 Issn(e): 2278-4721, Issn(p):2319-6483, Www.Researchinventy.Com Fair Scheduling Algorithm with Dynamic

More information

Study of Various Load Balancing Techniques in Cloud Environment- A Review

Study of Various Load Balancing Techniques in Cloud Environment- A Review International Journal of Computer Sciences and Engineering Open Access Review Paper Volume-4, Issue-04 E-ISSN: 2347-2693 Study of Various Load Balancing Techniques in Cloud Environment- A Review Rajdeep

More information

Sla Aware Load Balancing Algorithm Using Join-Idle Queue for Virtual Machines in Cloud Computing

Sla Aware Load Balancing Algorithm Using Join-Idle Queue for Virtual Machines in Cloud Computing Sla Aware Load Balancing Using Join-Idle Queue for Virtual Machines in Cloud Computing Mehak Choudhary M.Tech Student [CSE], Dept. of CSE, SKIET, Kurukshetra University, Haryana, India ABSTRACT: Cloud

More information

Keywords: Dynamic Load Balancing, Process Migration, Load Indices, Threshold Level, Response Time, Process Age.

Keywords: Dynamic Load Balancing, Process Migration, Load Indices, Threshold Level, Response Time, Process Age. Volume 3, Issue 10, October 2013 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Load Measurement

More information

SiteCelerate white paper

SiteCelerate white paper SiteCelerate white paper Arahe Solutions SITECELERATE OVERVIEW As enterprises increases their investment in Web applications, Portal and websites and as usage of these applications increase, performance

More information

SAP SMS 365, enterprise service Standard Rate SMS Messaging. October 2013

SAP SMS 365, enterprise service Standard Rate SMS Messaging. October 2013 SAP SMS 365, enterprise service Standard Rate SMS Messaging October 2013 Message Aggregation SAP SMS 365, enterprise service, provides: Aggregates access to send SMS to 700+ carriers around the world through

More information

TRUFFLE Broadband Bonding Network Appliance. A Frequently Asked Question on. Link Bonding vs. Load Balancing

TRUFFLE Broadband Bonding Network Appliance. A Frequently Asked Question on. Link Bonding vs. Load Balancing TRUFFLE Broadband Bonding Network Appliance A Frequently Asked Question on Link Bonding vs. Load Balancing 5703 Oberlin Dr Suite 208 San Diego, CA 92121 P:888.842.1231 F: 858.452.1035 info@mushroomnetworks.com

More information

EWeb: Highly Scalable Client Transparent Fault Tolerant System for Cloud based Web Applications

EWeb: Highly Scalable Client Transparent Fault Tolerant System for Cloud based Web Applications ECE6102 Dependable Distribute Systems, Fall2010 EWeb: Highly Scalable Client Transparent Fault Tolerant System for Cloud based Web Applications Deepal Jayasinghe, Hyojun Kim, Mohammad M. Hossain, Ali Payani

More information

LinuxWorld Conference & Expo Server Farms and XML Web Services

LinuxWorld Conference & Expo Server Farms and XML Web Services LinuxWorld Conference & Expo Server Farms and XML Web Services Jorgen Thelin, CapeConnect Chief Architect PJ Murray, Product Manager Cape Clear Software Objectives What aspects must a developer be aware

More information

Lecture Outline Overview of real-time scheduling algorithms Outline relative strengths, weaknesses

Lecture Outline Overview of real-time scheduling algorithms Outline relative strengths, weaknesses Overview of Real-Time Scheduling Embedded Real-Time Software Lecture 3 Lecture Outline Overview of real-time scheduling algorithms Clock-driven Weighted round-robin Priority-driven Dynamic vs. static Deadline

More information

International Journal of Computer Science Trends and Technology (IJCST) Volume 2 Issue 4, July-Aug 2014

International Journal of Computer Science Trends and Technology (IJCST) Volume 2 Issue 4, July-Aug 2014 RESEARCH ARTICLE An Efficient Priority Based Load Balancing Algorithm for Cloud Environment Harmandeep Singh Brar 1, Vivek Thapar 2 Research Scholar 1, Assistant Professor 2, Department of Computer Science

More information

CHAPTER 3 PROBLEM STATEMENT AND RESEARCH METHODOLOGY

CHAPTER 3 PROBLEM STATEMENT AND RESEARCH METHODOLOGY 51 CHAPTER 3 PROBLEM STATEMENT AND RESEARCH METHODOLOGY Web application operations are a crucial aspect of most organizational operations. Among them business continuity is one of the main concerns. Companies

More information

Ensuring Business Continuity and Disaster Recovery with Coyote Point Systems Envoy

Ensuring Business Continuity and Disaster Recovery with Coyote Point Systems Envoy Ensuring Business Continuity and Disaster Recovery with Coyote Point Systems Envoy WHITE PAPER Prepared by: Lisa Phifer Core Competence, Inc. As e-business quickly becomes the norm, virtually every enterprise

More information

IOS Server Load Balancing

IOS Server Load Balancing IOS Server Load Balancing This feature module describes the Cisco IOS Server Load Balancing (SLB) feature. It includes the following sections: Feature Overview, page 1 Supported Platforms, page 5 Supported

More information

A Survey Of Various Load Balancing Algorithms In Cloud Computing

A Survey Of Various Load Balancing Algorithms In Cloud Computing A Survey Of Various Load Balancing Algorithms In Cloud Computing Dharmesh Kashyap, Jaydeep Viradiya Abstract: Cloud computing is emerging as a new paradigm for manipulating, configuring, and accessing

More information

Chapter 6: CPU Scheduling

Chapter 6: CPU Scheduling Chapter 6: CPU Scheduling Basic Concepts Scheduling Criteria Scheduling Algorithms Multiple-Processor Scheduling Real-Time Scheduling Algorithm Evaluation Oct-03 1 Basic Concepts Maximum CPU utilization

More information

Application Note. Network Optimization with Exinda Optimizer

Application Note. Network Optimization with Exinda Optimizer Application Note Network Optimization with Exinda Optimizer Network traffic optimization reduces the reliance of business upon costly capacity bandwidth upgrades. Optimization is delivered either by prioritization

More information

Effective Virtual Machine Scheduling in Cloud Computing

Effective Virtual Machine Scheduling in Cloud Computing Effective Virtual Machine Scheduling in Cloud Computing Subhash. B. Malewar 1 and Prof-Deepak Kapgate 2 1,2 Department of C.S.E., GHRAET, Nagpur University, Nagpur, India Subhash.info24@gmail.com and deepakkapgate32@gmail.com

More information

Fax Server Cluster Configuration

Fax Server Cluster Configuration Fax Server Cluster Configuration Low Complexity, Out of the Box Server Clustering for Reliable and Scalable Enterprise Fax Deployment www.softlinx.com Table of Contents INTRODUCTION... 3 REPLIXFAX SYSTEM

More information

A Novel Approach for Efficient Load Balancing in Cloud Computing Environment by Using Partitioning

A Novel Approach for Efficient Load Balancing in Cloud Computing Environment by Using Partitioning A Novel Approach for Efficient Load Balancing in Cloud Computing Environment by Using Partitioning 1 P. Vijay Kumar, 2 R. Suresh 1 M.Tech 2 nd Year, Department of CSE, CREC Tirupati, AP, India 2 Professor

More information

Comparison of PBRR Scheduling Algorithm with Round Robin and Heuristic Priority Scheduling Algorithm in Virtual Cloud Environment

Comparison of PBRR Scheduling Algorithm with Round Robin and Heuristic Priority Scheduling Algorithm in Virtual Cloud Environment www.ijcsi.org 99 Comparison of PBRR Scheduling Algorithm with Round Robin and Heuristic Priority Scheduling Algorithm in Cloud Environment Er. Navreet Singh 1 1 Asst. Professor, Computer Science Department

More information

Server Management in the WSD

Server Management in the WSD Technical Application Note 1025 Server Management in the WSD Scope RADWare s Web Server Director (WSD) essentially allows multiple clients to be load balanced between an identical and redundant group of

More information

White Paper. Resonate Global Dispatch. White Paper June Intelligent Multisite Global Service Level Control

White Paper. Resonate Global Dispatch. White Paper June Intelligent Multisite Global Service Level Control White Paper White Paper June 2013 Resonate Global Dispatch Intelligent Multisite Global Service Level Control Resonate, Inc. 16360 Monterey St., STE 260 Morgan Hill, CA 95037 Phone: 1-408-545-5501 Fax:

More information

Load Balancing in cloud computing

Load Balancing in cloud computing Load Balancing in cloud computing 1 Foram F Kherani, 2 Prof.Jignesh Vania Department of computer engineering, Lok Jagruti Kendra Institute of Technology, India 1 kheraniforam@gmail.com, 2 jigumy@gmail.com

More information

Load Testing and Monitoring Web Applications in a Windows Environment

Load Testing and Monitoring Web Applications in a Windows Environment OpenDemand Systems, Inc. Load Testing and Monitoring Web Applications in a Windows Environment Introduction An often overlooked step in the development and deployment of Web applications on the Windows

More information

Storage I/O Control: Proportional Allocation of Shared Storage Resources

Storage I/O Control: Proportional Allocation of Shared Storage Resources Storage I/O Control: Proportional Allocation of Shared Storage Resources Chethan Kumar Sr. Member of Technical Staff, R&D VMware, Inc. Outline The Problem Storage IO Control (SIOC) overview Technical Details

More information

@IJMTER-2015, All rights Reserved 355

@IJMTER-2015, All rights Reserved 355 e-issn: 2349-9745 p-issn: 2393-8161 Scientific Journal Impact Factor (SJIF): 1.711 International Journal of Modern Trends in Engineering and Research www.ijmter.com A Model for load balancing for the Public

More information

TCP in Wireless Mobile Networks

TCP in Wireless Mobile Networks TCP in Wireless Mobile Networks 1 Outline Introduction to transport layer Introduction to TCP (Internet) congestion control Congestion control in wireless networks 2 Transport Layer v.s. Network Layer

More information

SCALABILITY AND AVAILABILITY

SCALABILITY AND AVAILABILITY SCALABILITY AND AVAILABILITY Real Systems must be Scalable fast enough to handle the expected load and grow easily when the load grows Available available enough of the time Scalable Scale-up increase

More information

Monitoring DoubleTake Availability

Monitoring DoubleTake Availability Monitoring DoubleTake Availability eg Enterprise v6 Restricted Rights Legend The information contained in this document is confidential and subject to change without notice. No part of this document may

More information

TRUFFLE Broadband Bonding Network Appliance BBNA6401. A Frequently Asked Question on. Link Bonding vs. Load Balancing

TRUFFLE Broadband Bonding Network Appliance BBNA6401. A Frequently Asked Question on. Link Bonding vs. Load Balancing TRUFFLE Broadband Bonding Network Appliance BBNA6401 A Frequently Asked Question on Link Bonding vs. Load Balancing LBRvsBBNAFeb15_08b 1 Question: What's the difference between a Truffle Broadband Bonding

More information

Various Schemes of Load Balancing in Distributed Systems- A Review

Various Schemes of Load Balancing in Distributed Systems- A Review 741 Various Schemes of Load Balancing in Distributed Systems- A Review Monika Kushwaha Pranveer Singh Institute of Technology Kanpur, U.P. (208020) U.P.T.U., Lucknow Saurabh Gupta Pranveer Singh Institute

More information

IOS Server Load Balancing

IOS Server Load Balancing IOS Server Load Balancing This feature module describes the Cisco IOS Server Load Balancing (SLB) feature. It includes the following sections: Feature Overview, page 1 Supported Platforms, page 5 Supported

More information

NetScope: Powerful Network Management

NetScope: Powerful Network Management NetScope: Powerful Network Management NetScope is a comprehensive tool set designed to effectively monitor and manage your network, from small installations, right through to complex multiple site enterprise

More information

MEASURING PERFORMANCE OF DYNAMIC LOAD BALANCING ALGORITHMS IN DISTRIBUTED COMPUTING APPLICATIONS

MEASURING PERFORMANCE OF DYNAMIC LOAD BALANCING ALGORITHMS IN DISTRIBUTED COMPUTING APPLICATIONS MEASURING PERFORMANCE OF DYNAMIC LOAD BALANCING ALGORITHMS IN DISTRIBUTED COMPUTING APPLICATIONS Priyesh Kanungo 1 Professor and Senior Systems Engineer (Computer Centre), School of Computer Science and

More information

Azure VM Performance Considerations Running SQL Server

Azure VM Performance Considerations Running SQL Server Azure VM Performance Considerations Running SQL Server Your company logo here Vinod Kumar M @vinodk_sql http://blogs.extremeexperts.com Session Objectives And Takeaways Session Objective(s): Learn the

More information

LOAD BALANCING TECHNIQUES FOR RELEASE 11i AND RELEASE 12 E-BUSINESS ENVIRONMENTS

LOAD BALANCING TECHNIQUES FOR RELEASE 11i AND RELEASE 12 E-BUSINESS ENVIRONMENTS LOAD BALANCING TECHNIQUES FOR RELEASE 11i AND RELEASE 12 E-BUSINESS ENVIRONMENTS Venkat Perumal IT Convergence Introduction Any application server based on a certain CPU, memory and other configurations

More information

SOLUTION BRIEF: SLCM R12.7 PERFORMANCE TEST RESULTS JANUARY, 2012. Load Test Results for Submit and Approval Phases of Request Life Cycle

SOLUTION BRIEF: SLCM R12.7 PERFORMANCE TEST RESULTS JANUARY, 2012. Load Test Results for Submit and Approval Phases of Request Life Cycle SOLUTION BRIEF: SLCM R12.7 PERFORMANCE TEST RESULTS JANUARY, 2012 Load Test Results for Submit and Approval Phases of Request Life Cycle Table of Contents Executive Summary 3 Test Environment 4 Server

More information

Cisco Application Networking for Citrix Presentation Server

Cisco Application Networking for Citrix Presentation Server Cisco Application Networking for Citrix Presentation Server Faster Site Navigation, Less Bandwidth and Server Processing, and Greater Availability for Global Deployments What You Will Learn To address

More information

CSE LOVELY PROFESSIONAL UNIVERSITY

CSE LOVELY PROFESSIONAL UNIVERSITY Comparison of load balancing algorithms in a Cloud Jaspreet kaur M.TECH CSE LOVELY PROFESSIONAL UNIVERSITY Jalandhar, punjab ABSTRACT This paper presents an approach for scheduling algorithms that can

More information

DELL. Virtual Desktop Infrastructure Study END-TO-END COMPUTING. Dell Enterprise Solutions Engineering

DELL. Virtual Desktop Infrastructure Study END-TO-END COMPUTING. Dell Enterprise Solutions Engineering DELL Virtual Desktop Infrastructure Study END-TO-END COMPUTING Dell Enterprise Solutions Engineering 1 THIS WHITE PAPER IS FOR INFORMATIONAL PURPOSES ONLY, AND MAY CONTAIN TYPOGRAPHICAL ERRORS AND TECHNICAL

More information

Network performance in virtual infrastructures

Network performance in virtual infrastructures Network performance in virtual infrastructures A closer look at Amazon EC2 Alexandru-Dorin GIURGIU University of Amsterdam System and Network Engineering Master 03 February 2010 Coordinators: Paola Grosso

More information

HUAWEI OceanStor 9000. Load Balancing Technical White Paper. Issue 01. Date 2014-06-20 HUAWEI TECHNOLOGIES CO., LTD.

HUAWEI OceanStor 9000. Load Balancing Technical White Paper. Issue 01. Date 2014-06-20 HUAWEI TECHNOLOGIES CO., LTD. HUAWEI OceanStor 9000 Load Balancing Technical Issue 01 Date 2014-06-20 HUAWEI TECHNOLOGIES CO., LTD. Copyright Huawei Technologies Co., Ltd. 2014. All rights reserved. No part of this document may be

More information

Implementation, Simulation of Linux Virtual Server in ns-2

Implementation, Simulation of Linux Virtual Server in ns-2 Implementation, Simulation of Linux Virtual Server in ns-2 CMPT 885 Special Topics: High Performance Networks Project Final Report Yuzhuang Hu yhu1@cs.sfu.ca ABSTRACT LVS(Linux Virtual Server) provides

More information

Grid Computing Approach for Dynamic Load Balancing

Grid Computing Approach for Dynamic Load Balancing International Journal of Computer Sciences and Engineering Open Access Review Paper Volume-4, Issue-1 E-ISSN: 2347-2693 Grid Computing Approach for Dynamic Load Balancing Kapil B. Morey 1*, Sachin B. Jadhav

More information

Best Practices for Managing Virtualized Environments

Best Practices for Managing Virtualized Environments WHITE PAPER Introduction... 2 Reduce Tool and Process Sprawl... 2 Control Virtual Server Sprawl... 3 Effectively Manage Network Stress... 4 Reliably Deliver Application Services... 5 Comprehensively Manage

More information

Adaptable Load Balancing

Adaptable Load Balancing Adaptable Load Balancing Sung Kim, Youngsu Son, Gaeyoung Lee Home Solution Group Samsung Electronics ABSTRACT The proposed load balancing system includes multiple counts of servers for processing network

More information

1. First thing you'll do is login to the New Control Panel, select Load Balancers from the list at the top, and then select Create Load Balancer.

1. First thing you'll do is login to the New Control Panel, select Load Balancers from the list at the top, and then select Create Load Balancer. Alternate Titles: Load Balancer Author: Muhammad Zeeshan Bhatti [LPI, VCP, OCP (DBA), MCSA, SUSE CLA,] (http://zeeshanbhatti.com) (admin@zeeshanbhatti.com) Load Balancer? Mission critical web-based applications

More information

Improved Virtualization Performance with 9th Generation Servers

Improved Virtualization Performance with 9th Generation Servers Improved Virtualization Performance with 9th Generation Servers David J. Morse Dell, Inc. August 2006 Contents Introduction... 4 VMware ESX Server 3.0... 4 SPECjbb2005... 4 BEA JRockit... 4 Hardware/Software

More information

Purpose-Built Load Balancing The Advantages of Coyote Point Equalizer over Software-based Solutions

Purpose-Built Load Balancing The Advantages of Coyote Point Equalizer over Software-based Solutions Purpose-Built Load Balancing The Advantages of Coyote Point Equalizer over Software-based Solutions Abstract Coyote Point Equalizer appliances deliver traffic management solutions that provide high availability,

More information

Cloud Performance Benchmark Series

Cloud Performance Benchmark Series Cloud Performance Benchmark Series Amazon Elastic Load Balancing (ELB) Md. Borhan Uddin Bo He Radu Sion ver. 0.5b 1. Overview Experiments were performed to benchmark the Amazon Elastic Load Balancing (ELB)

More information

CS423 Spring 2015 MP4: Dynamic Load Balancer Due April 27 th at 9:00 am 2015

CS423 Spring 2015 MP4: Dynamic Load Balancer Due April 27 th at 9:00 am 2015 CS423 Spring 2015 MP4: Dynamic Load Balancer Due April 27 th at 9:00 am 2015 1. Goals and Overview 1. In this MP you will design a Dynamic Load Balancer architecture for a Distributed System 2. You will

More information

STANDPOINT FOR QUALITY-OF-SERVICE MEASUREMENT

STANDPOINT FOR QUALITY-OF-SERVICE MEASUREMENT STANDPOINT FOR QUALITY-OF-SERVICE MEASUREMENT 1. TIMING ACCURACY The accurate multi-point measurements require accurate synchronization of clocks of the measurement devices. If for example time stamps

More information

Ecole des Mines de Nantes. Journée Thématique Emergente "aspects énergétiques du calcul"

Ecole des Mines de Nantes. Journée Thématique Emergente aspects énergétiques du calcul Ecole des Mines de Nantes Entropy Journée Thématique Emergente "aspects énergétiques du calcul" Fabien Hermenier, Adrien Lèbre, Jean Marc Menaud menaud@mines-nantes.fr Outline Motivation Entropy project

More information

Windows Server Performance Monitoring

Windows Server Performance Monitoring Spot server problems before they are noticed The system s really slow today! How often have you heard that? Finding the solution isn t so easy. The obvious questions to ask are why is it running slowly

More information

The Effectiveness of Request Redirection on CDN Robustness

The Effectiveness of Request Redirection on CDN Robustness The Effectiveness of Request Redirection on CDN Robustness Limin Wang, Vivek Pai and Larry Peterson Presented by: Eric Leshay Ian McBride Kai Rasmussen 1 Outline! Introduction! Redirection Strategies!

More information

ZEN LOAD BALANCER EE v3.04 DATASHEET The Load Balancing made easy

ZEN LOAD BALANCER EE v3.04 DATASHEET The Load Balancing made easy ZEN LOAD BALANCER EE v3.04 DATASHEET The Load Balancing made easy OVERVIEW The global communication and the continuous growth of services provided through the Internet or local infrastructure require to

More information

Measuring IP Performance. Geoff Huston Telstra

Measuring IP Performance. Geoff Huston Telstra Measuring IP Performance Geoff Huston Telstra What are you trying to measure? User experience Responsiveness Sustained Throughput Application performance quality Consistency Availability Network Behaviour

More information

Design and Implementation of Efficient Load Balancing Algorithm in Grid Environment

Design and Implementation of Efficient Load Balancing Algorithm in Grid Environment Design and Implementation of Efficient Load Balancing Algorithm in Grid Environment Sandip S.Patil, Preeti Singh Department of Computer science & Engineering S.S.B.T s College of Engineering & Technology,

More information

A Network Monitoring System with a Peer-to-Peer Architecture

A Network Monitoring System with a Peer-to-Peer Architecture A Network Monitoring System with a Peer-to-Peer Architecture Paulo Salvador, Rui Valadas University of Aveiro / Institute of Telecommunications Aveiro E-mail: salvador@av.it.pt; rv@det.ua.pt Abstract The

More information

LOAD BALANCING OF USER PROCESSES AMONG VIRTUAL MACHINES IN CLOUD COMPUTING ENVIRONMENT

LOAD BALANCING OF USER PROCESSES AMONG VIRTUAL MACHINES IN CLOUD COMPUTING ENVIRONMENT LOAD BALANCING OF USER PROCESSES AMONG VIRTUAL MACHINES IN CLOUD COMPUTING ENVIRONMENT 1 Neha Singla Sant Longowal Institute of Engineering and Technology, Longowal, Punjab, India Email: 1 neha.singla7@gmail.com

More information