Grid Load Balancing Scheduling Algorithm Based on Statistics Thinking The 9th International...
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Transcript of Grid Load Balancing Scheduling Algorithm Based on Statistics Thinking The 9th International...
Grid Load Balancing Scheduling Algorithm Based on Statistics
ThinkingThe 9th International Conference for Young Computer Scientists
Bin Lu, Hongbin Zhang
Present by Chen, Ting-Wei
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Table of content
• Introduction
• Hierarchical Grid system model
• Grid resource allocation and task scheduling
• Simulative experiments
• Conclusions
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Introduction
• Propose a new task scheduling and resource allocation algorithm– Load tracking module– Job distributing module– Load monitoring module
• Simulate the algorithm
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Introduction (cont.)
• Based on the hierarchical Grid structure model– Distribution of Grid resources – The strategy of task scheduling– Following statistical thinking
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Hierarchical Grid system model
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Grid resource allocation and task scheduling
Load (LLoad (Lxx))Length of CPU Length of CPU Ready queueReady queue
CPU UtilizationCPU Utilization
Light LoadLight Load LLxx < Llow Short Low
Heavy LoadHeavy Load LLxx >Lhigh Long High
Moderate Moderate LoadLoad
Llow < LLxx < Lhigh Normal Normal
• Definition of the Load
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Grid resource allocation and task scheduling (cont.)
• Algorithm analysis and implementation– Three components
• Load tracing module
• Job distributing module
• Load monitor module
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Grid resource allocation and task scheduling (cont.)
– Three tables are installed on the database server in GRM and DRM
• The first: Every sub-DRM load information
• The second: The number of tasks being operated
• The third: The throughput and the average delayed response
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Grid resource allocation and task scheduling (cont.)
• Load tracing module– Get the load information of DRM– Monitor periodically the implementation state o
f operations– Report it to the upper level for the overall mana
gement and scheduling
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Grid resource allocation and task scheduling (cont.)
• Job distributing module– According to load balancing– GRM chooses a suitable DRM to carry out job
distributing– Consider
• CPU utilization • Memory usage
– The weight of load indicators can be determined statically or dynamically
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Grid resource allocation and task scheduling (cont.)
– Load computing formula of the CN
– The average of the sub-DRM’s load or CN’s load
– Variance of load
2
1
n
i j ijj
L a L
1
1 m
DK ii
L Lm
2( ) [( ) ]DK i DKVar L E L L
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Grid resource allocation and task scheduling (cont.)
– Job algorithmInitialize;For (;;){do
If (There was information form the DRMs or CNs){
Updating the load information of DRM or CNs according to the formula (1)-(3);Calculating the rate of throughput;Calculating the average response delay;If (There was information of completed assignment){
Deducting one assignment of corresponding DRM;
}}
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Grid resource allocation and task scheduling (cont.)
If (Portal gives the assignment to GRM){
If (The node having the load is not unique){ ;Making the node whose variance is as the scheduling nodes, if still not unique, selecting the first node;}Else{Making the node whose load value is be the scheduling node;}Giving it the assignment for scheduling, and updating the number of assignment of DRM;}
}
min min kk
L L
minmax max
DKDK
L LVar Var
maxVar
minL
minL
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Grid resource allocation and task scheduling (cont.)
• Load monitor module– Surveillance
• The current load of all the DRMs
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Grid resource allocation and task scheduling (cont.)
For (;;){
If (sum < ){
The opening of stand-by resources manager;}Reading the load vector of domain resources manager;Reading the upper and lower threshold provided in profile;If (Every load exceeds the threshold ){
Opening the stand-by resources manager;}If (Every load is below the threshold ){
Removing stand-by resources manager;}
mb
highL
lowL
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Grid resource allocation and task scheduling (cont.)
Else{
Get the last updated time of the nodeIf (The current time – last updated time) > (timeout)Means that the main resource manager failed and it takes proper measures;
}}
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Simulative experiments
• Use Gridsim to simulate
• Compare performance of the load balancing scheduling method– Min-Min algorithm– Ant algorithm– This algorithm (This paper proposed)
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Simulative experiments (cont.)
• Configuration of experiment environment
GRM
DRM1 DRM2 DRM3
DRM11 DRM12 DRM13 CN-17台CN-21台
CN-18台 CN-25台 CN-28台
USER
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Simulative experiments (cont.)
• Comparison of experiment results
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Conclusions
• Statistical load balancing scheduling scheme
• Future work– Granular computing idea to improve this
algorithm– More the flexibility and efficiency of this
algorithm
Thank you for your attentionThank you for your attention