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What’s the Problem. Web Server 1. Web Server N. Web system played an essential role in Proving and Retrieve information. Cause Overloaded Status and Longer Response Time Duplicated Web System is Widely Used Today with Purpose to Scatter the Client’s Request and Shorten the Response Time - PowerPoint PPT Presentation
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What’s the Problem
WebServer 1
WebServer N
• Web system played an essential role in Proving and Retrieve information.
• Cause Overloaded Status and Longer Response Time
• Duplicated Web System is Widely Used Today with Purpose to Scatter the Client’s Request and Shorten the Response Time
• Key Problem How to allocate the request efficiently to maximally Shorten the Response Time
Client Client
Request Request
Which Web Server to Choose?
? ?
Related Works on Web Systems
• CISCO Distributed Director…
• GIT Feo et al, Dynamic Server Selection,…
• NCSA Scalable Web Server….
Web Components and Their Interaction
Subnet 2
LBA 1Router
Client
1. Request
2.Request
3.Request/Web Address
Network
Subnet 1
LBA Message
4. Request/ Web Address
WebServer 1
WebServer 2
WebServer 3
Subnet 3
Subnet 4Client
Router LBA 2
RequestDocument
Request
Request/WebAddress
5. Request 6. Document
7. Document
8.Document
LBA Message
RequestDocument
Request Document
Document
RequestLBA Message
Two Metrics
1. Current Load
L1,t /S1 = L2,t /S2 = L3,t /S3 … = Lk,t /Sk
The goal is to Make the Loads Even among the Web Servers
2. Average Response Time (ART)
ART load-balancing status = min(ART)
The Goal is to Maximally Shorten the Response Time
Factors That Affect Load Balancing• Size of Request
• Web Processing Power
• The Number of pending Requests at the Web Server
• The Size of Pending Requests at the Web Server
• Distance of the Path between Client and Web Server
• Available Bandwidth along the Path
• Hop Count of the Path
• Traffic Status
• Number of Web Servers
• Divide into Two Information: Static and Dynamic:
• Static Information: Web Server Processing Power, Distance, Bandwidth, Web Server Number, Hop Count
Load Balancing Algorithm Design
Concern Two Processing Times in Load Balancing Algorithm:1. Time from Client to Web Server. It Includes Time: Transmission Delay Queuing Delay2. Time Stay at Web Server. It Includes Time: Queuing at Web Server Processing Time at Web Server
IdeaBalancing Those Times. Load Balancing Algorithm should try to shorten the End-to-End Response Time of the Request.
Load Balancing Algorithm I
1. LBA-I: Use all Static Information
Selected Web Server i = Min{Distance/Bandwidth + Loads of Web Server i / + Process Power of Web Server i}
• Use the Ratio of Distance to Bandwidth to Measure the Path, • Use the Ratio of Web Server Loads to Processing Power to Measure the Web Status.
There are two Variation Algorithms:LBA-I-1: Add Hop CountLBA-I-2: Just Concern Web Status
Load Balancing Algorithm II
LBA-II: LBAs communicate with each other. When a LBA Makes an Assignment Decision, It Passes this info to Other LBAs, Other LBAs Update their Assignment Table.
Advantage: Improve the estimated precision of loads of web server.Disadvantage: Generate heavy communication overhead and take away available bandwidth for web access..
A Variation Algorithm LBA-II-1. Just Pass the Assignment info to Neighboring LBAsAdvantage: Reduce Communication Overhead.Disadvantage: Decrease the Estimated Precision of Web Server Loads.
Load Balancing Algorithm III
Using Static Information to Measure the Path Traffic in LBA-I and LBA-II.
LBA-III: Using Dynamic Path Information. Periodically sendprobing packets to probe path bandwidth. Advantage: Improve the Estimated Precision of Path Traffic.Disadvantage: Generate Heavy Communication Overhead, reduce available bandwidth.
Load Balancing Algorithm IV
Using Assignment Number of Request to Measure the Web Server Loads in LBA-I, LBA-II and LBA-III.
LBA-IV: Using Left Loads Information to Measure the Web Server Load Status. Web Servers Periodically Send the Left Load Message to LBAs Advantage: Improve the Estimated Precision of Web Server Loads.Disadvantage: 1. Generate Heavy Communication Overhead, reduce available bandwidth. 2. The performance of the algorithm depends on web server reporting period.There are Two Variations of AlgorithmsLBA-IV(E)LBA-IV(Tc)
Sequence Chart Of Simulation ProgramClient Router LBA Web
Server
Request Request
Req./WebAddress
Req./WebAddress
DocumentDocument
Probe-Path
Probe-Path
Probe-Path
Load-Report
Load-Report
LBA
Message
Message
Probe-Path
Web Server and Client Traffic CharacterizationsLog Files of Five Web Server are analyzed:
1. Department wide server at UCCS run on an Alpha workstation owl.uccs.edu. 2. Campus wide server at UCCS run on an Alpha workstation www.uccs.edu. 3. ClarkNet WWW server, which is a full Internet access provider for the Metro Baltimore-Washington DC area. 4. EPA WWW server located at Research Triangle Park, NC. 5. BU-Web-Client in the Boston University Computer Science Department.
Characterize the Workload of Web Server and Client.Compare Those Characterization with Other Reports
Characterizations of Document Type
0%
10%
20%
30%
40%
50%
60%
70%
80%
owl uccs clarknet epa bugs
.gif
.mpg
.html
.au
.ps
.pl
.jpg
.avi
.wav
.mid
.mpeg
.jpeg
.pdfother
Most Frequently Requested by the Clients are Image and HTML type, Which Account Over 80%of all Requested Type.
Characterization of Document Size
Most Document Size Requested by Clients is 1 ~ 5 KB
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
<100B
< 1 K 1~2K 2~3K 3~4K 4~5K 5~6K 6~7K 7~8K 8~9K 9~10K > 10K
owl
uccs
epa
clarknet
bugs
Characterization of Request Time Interval
0%
10%
20%
30%
40%
50%
60%owl
uccs
epa
bugs
clarknet
Most Time Interval of Request is less 1 sec
Test PlanThere are Following Factors Affecting Performance of Algorithms1. Network Topology2. Request Count3. Request Time Interval4. Bandwidth
We will Change Those Parameters to Test the Performance of the Algorithms. We will collect the statistics of the following Data1. Average Response Time2. Web Queuing Delay Time3. Router Queuing Delay Time4. Transmission Delay Time5. Propagation Delay 6. Processing Time7. Various Communication Overhead
Performance of Load Balancing Algorithms
Response T Web QueuingDelay
TransmissionDelay
OverheadMessages
Period
LBA-I 0.016226 0.000308 0.014775 0 NoLBA-I-1 0.016226 0.000308 0.014775 0 NoLBA-I-2 0.017708 0.000035 0.016528 0 NoRR 0.017663 0.000037 0.016483 0 NoRandom 0.017924 0.000053 0.016706 0 NoLBA-II(I) 0.016425 0.000292 0.015014 400% NoLBA-II(I-2) 0.017688 0.000027 0.016582 400% NoLBA-III 0.270639 0.253463 0.017664 2% 2 (s)LBA-IV-1(3) 0.019813 0.0039813 0.014800 2% 5(s)
Distribution of Request Time Interval as Figure 6-2Distribution of Document Size as Figure 6-1Request Count from 800 to 10000Average Bandwidth as 5 MbNew-Jersey Network as Figure 5-1Transmission Delay ( 90%) Dominates the Response Time
Performance of Load Balancing AlgorithmsResponse T Web Queuing
DelayTransmissionDelay
OverheadMessages
Period
LBA-I 0.0288746 0.0013823 0.0244098 0 NoLBA-I-1 0.027373 0.001351 0.0228792 0 NoLBA-I-2 0.032093 0.0005428 0.0267744 0 NoRR 0.0319824 0.0004043 0.0266921 0 NoRandom 0.032012 0.000417 0.026793 0 NoLBA-II(I) 0.030891 0.002312 0.253481 400% NoLBA-II(I-2) 0.032236 0.002415 0.026345 400% NoLBA-III 0.207321 0.176451 0.034561 2% 5 (s)LBA-IV-1(3) 0.356712 0.001856 0.0277451 2% 5 (s)
Distribution of Request Time Interval as Figure 6-2Distribution of Document Size as Figure 6-1Request Count from 800 to 10000Average Bandwidth as 5 Mbr50 Network as Append ATransmission Delay ( 80%) Dominates the Response Time
Performance of Load Balancing Algorithm
0
0.05
0.1
0.15
0.2
-500 0 500 1000 1500 2000 2500 3000
Bandw idth (Mb)
Ave
rage
Res
pons
e Ti
me
(s)
LBA-I
LBA-I-1
LBA-I-2
RR
Random
LBA-II(I)
LBA-II(I-2)
LBA-III
LBA-IV-1(3)
From above Figure, we can see when the bandwidth increases,the Average Response Time of all algorithms decrease in the case that the transmission delay dominates the response time of the request
Performance of Load Balancing Algorithms
Now We Change the Request Interval Time as Figure 6-18(Chow: show Figure 6-18 here)The Web Queuing Delay Dominates the Response Time of Request.(how much)Following Figure Shows the Performance of Algorithms
Performance of Load Balancing Algorithms
0
0.05
0.1
0.15
0.2
0.25
0 10 20 30 40 50
Bandw idth (Mb)
Avera
ge R
esponse T
ime
(sec)
LBA-I
LBA-I-1
LBA-I-2
RR
Random
LBA-II(I)
LBA-IV
LBA-II(I-2)
0
0.05
0.1
0.15
0.2
0.25
-1000 0 1000 2000 3000
Bandw idth (Mb)
Average R
esponse T
ime (
s)
LBA-I
LBA-I-1
LBA-I-2
RR
Random
LBA-II(I)
LBA-IV
LBA-II(I-2)
Summary of Load Balancing Algorithm Performance
1. Algorithm LBA-I and LBA-I-1 have the Better Performance When the Transmission Delay Dominates the Response Time.2. Algorithm LBA-II(I-2) has the Better Performance When the Web Queuing Delay Dominates the Response Time3. As the Bandwidth Increases, except Algorithm LBA-I and LBA-I-2, all Algorithm Decreases the Response Time.4. Algorithms LBA-I, LBA-I-1 are Sensitive to Bandwidth Changes
Network Design Issues
If the Transmission Delay Dominates the Response Time, We have Following Suggestions for Network Design:
1. Reduce Document Size.2. Choose Proper Ratio of Web Servers and Clients3. Choose Proper Process Power of Web Servers4. Choose Proper Location of Web Servers
Conclusions
1. Algorithm LBA-I and LBA-I-1 have the Better Performance When the Transmission Delay Dominates the Response Time. They are independent of ant Period and Do not Generate any Overhead Messages.2. Algorithm LBA-II Have the Better Performance When The Web Queuing Delay Dominates the Response Time. It Generates very Heavy Overhead Messages and is independent of reporting Period.3. Algorithm LBA-III Have the Worse Performance in Both case-- Transmission Delay Dominates the Response Time and Web Queuing Delay Dominates Response Time. It Generates Very Heavy Overhead Messages and is dependent on reporting Period.4. Algorithm LBA-IV has the Better Performance When the Web Queuing Delay Dominates the Response Time. It Generates Overhead Messages and is dependent on reporting period.
Future Directions
1. Using real and larger networks to test the proposed load balancing algorithms2. Investigate algorithm performance under heavy web server load.3. Investigate aggregate server/LBA reporting and impact of reporting frequencies.4. Implement load balancing algorithms in a prototype.
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