Dynamic Load Sharing and Balancing
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Dynamic Load Sharing and Balancing

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Dynamic Load Sharing and Balancing




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Presentation on theme: "Dynamic Load Sharing and Balancing"— Presentation transcript:

Slide1

Dynamic Load Sharing and Balancing

Haidong

Xue

Slide2

Part One: Knowledge in Textbook Motivation, Models, Concepts, AlgorithmsPart Two: Recent WorkUse the Mobile Agent and Include I/ODuplex Loading Balancing StrategyStability Analysis BasedExtension-based Dynamic Load BalancingPart Three: Future Work

Content

Slide3

Part One: Knowledge in the Textbook

Motivations,

Models

Concepts,

Algorithms

Slide4

For most distributed applications: The prior knowledge of processes is not realistic

Motivation

Slide5

Goal:Reduce the overall turnaround time = communication overhead + computational constraints

Motivation

Slide6

(5.1c)

Models – Disjoint Process Model

Slide7

(5.3c)

Models – Workstation Model

Slide8

Load Sharing Joining the shortest queue (Randy Chow, Theodore Johnson, 1997)Load Balancing Equalizing queue sizes (Randy Chow, Theodore Johnson, 1997)

Concepts

Slide9

Sender-initiated AlgorithmReceiver-initiated Algorithm

Algorithms

Slide10

Transfer policy: When does a node become the sender? SQ STSelection policy: How does the sender choose a process for transfer? The last one.Location policy: Which node should be the target receiver? RQ PL

Sender-initiated Algorithm

Slide11

Sender-initiated Algorithm

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1

2

4

3

5

4

4

ST=3

5

2

SQ = sender’s queue size

ST = sender threshold

RQ = receiver queue size

PL = poll limit

Slide12

Sender-initiated Algorithm

Slide13

Receiver-initiated Algorithm

1

6

2

4

3

5

4

4

ST=3

5

7

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Receiver-initiated Algorithm

1

1

2

4

3

5

4

4

ST=3

5

2

Slide15

Algorithms

Slide16

Depends on LoadStock Exchange

Algorithms - Hybrid

Slide17

Part Two: Recent Work

Use the Mobile Agent and Include I/O

Duplex Loading Balancing Strategy

Stability Analysis Based

Extension-based Dynamic Load Balancing

Slide18

In order to distribute the incoming load on participating nodes, use mobile agent (MA).A value function which is sum of all three types of resources including CPU, Memory and I/O is considered. (Neeraj Nehra, R.B.Patel, 2007)

Use the Mobile Agent and Include I/O

Slide19

When comes to OBS, an Object-based Storage System, most of these strategies are hard to comply with the new featureDLBS can be utilized in the real OBS system to provide more effective and efficient load balance than other methods (Tan Zhipeng et al, 2009 )

Duplex Loading Balancing Strategy

Slide20

the unstable behavior such as oscillatory action which caused by delay can intensely influence the performance of load balancing algorithm. a linear dynamic load balancing model (Qingyang Meng et al, 2008)

Stability Analysis Based

Slide21

Connect extension theory with loadExtension engineering method is initially proposed by Prof. Cai Wen (Zhang Xiayu et al, 2007)

Extension-based Dynamic Load Balancing

Slide22

Part Three: Future Work

Other theories

Collect more information

Slide23

Incorporate other theoryCollect more information of the processesDevelop load balancing algorithm based on those information

Future Work

Slide24

Randy Chow, Theodore Johnson. Distributed Operating Systems& Algorithms. Addison Wesley, 1997Neeraj Nehra, R.B. Patel. Towards Dynamic Load Balancing in Heterogeneous Cluster using Mobile Agent. International Conference on Computational Intelligence and Multimedia Applications 2007, 2007, 15-21Tan Zhipeng, Feng Dan, Tu Xudong, He Fei. DLBS: Duplex Loading Balancing Strategy on Object Storage System. 2009 IEEE International Symposium on Parallel and Distributed Processing with Applications, 2009, 45-52

Reference

Slide25

Qingyang Meng, Jianzhong Qiao, Jun Liu, Shukuan Lin. A Dynamic Load Balancing Method Based on Stability Analysis. 2008 International Symposium on Computer Science and Computational Technology, 2008, 404-408Zhang Xiayu, Yu Yongquan, Chen Baixing, Ye Feng, Tan Xingxing. An Extension-based Dynamic Load Balancing Model of Heterogeneous Server Cluster. 2007 IEEE International Conference on Granular Computing, 2007, 675-679

Reference Contd.