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Task Model for Process Composition

Stuart Wheater

Santosh Shrivastava

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Objective

Distributed applications constructed by combining existing applications

– Such applications can be very complex in structure Contain many notification and dataflow dependencies between

their constituent applications

– The execution of such an application may take a long time to complete, and may contain long periods of inactivity

Long running applications will require support for fault-tolerance: machines may fail, services may be moved or withdrawn

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Computational Model

Computational model for expressing process logic– Tasks– Dependencies– Task composition

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Tasks

Can have multiple input sets– Contains a set of input

objects– The first complete input set

causes a task to be started Can have multiple output

sets– Contains a set of output

objects– A task can produces one

output set

i3

i2

i4

i1

t

I1

I2

I3

o2

o3

o1

O1

O2

O3

5Multi-source Multi-sink Multi-source Multi-sink

Dataflow Dependencies

Source Output Source Input

Dependencies Types

Output

Input

Sink

Notification Dependencies

Source Output Source Input

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A

C

B

D

Example of Tasks and Dependences

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Compound Tasks

Compositional building blocks for collections of tasks

The first complete output set causes a compound task to be completed

A

B

E

C

D

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Genesis Tasks

Tasks which instantiate a workflow definition when executed

– Allows “just in time” instantiation

– Allows recursive execution of defined workflows

AA’

B

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Model Summary

Tasks – Multiple ways of starting (input sets)– Multiple ways of completing (output sets)

Recursive task definition– Compound tasks

Recursive task execution– Genesis task

Multiple input sources– Redundant sources of input

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Flexible Task Composition

Application level fault-tolerance– Alternative tasks– Compensating tasks

Forward error recovery Backward error recovery

– Input time-out support tasks

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Alternative Tasks

Primary task A Alternative task A’ If A fails A’ is started

– With same input

B will be triggered by successful completion of A or A’

– Otherwise another process could be triggered

A’

BA

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Compensating Tasks

Task C outcomes:– Successful– Nothing– Partial

Forward error recovery Backward error recovery

-C

C D

+C

C D

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Input Time-Out Support Tasks

If task E does not complete within required time, task TO will trigger task F using secondary input set.

TO

E F

Process Deployment Model

Process definition contains annotations which are interpreted based on the deployment definition

Deployment definition

Processdefinition

Deploymentengine

Process instance

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Process Deployment Definition

Organisation

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Process Deployment Definition

Organisation

Provided Processes

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Process Deployment Definition

Organisation

Required Processes

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Org A

Org B

Org C

Org Da

b

c

d

Example Deployment

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Summary

Computational Model Deployment Model

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