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Towards a Bell-Curve Calculus and its Application to e-Science

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Title: Towards a Bell-Curve Calculus and its Application to e-Science


1
Towards a Bell-Curve Calculus and its Application
to e-Science
  • Lin Yang
  • Supervised by Alan Bundy, Dave Berry, Sophie
    Huczynska and Conrad Hughes

2
Content
  • Background
  • Workflow
  • QoS properties
  • Interval arithmetic
  • Experimental environment
  • Bell-Curve calculus
  • Importance
  • Definition
  • Methodology
  • Discussion

3
Background (1) -- workflow
  • What is workflow?
  • Web services
  • The orchestration of web services
  • An automation of a web process
  • Pass documents, information or data from one web
    service to another for action
  • Grid service web service implementing Grid
    functionality

4
Background (2) -- workflow
  • An example of workflow

Query information
  • Ticket booking system
  • Four services (generally sequential, partially
    parallel)

Query
Ticket information
Ticket information
Check_available1
Check_available2
Booking information1
Booking information2
Deal_made
Deal information
5
Background (3) quality of service properties
  • Why QoS properties?
  • Describe/evaluate the quality of
  • a Grid/web service
  • Which QoS properties?
  • Run time, reliability and accuracy

6
Background (4) interval arithmetic
  • Error bound an interval that represents the
    possible values of the result
  • e.g. 42 ? 41, 43
  • Propagation extension of numerical analysis
  • e.g. unary and monotonically increasing
  • f(x, y) f(x), f(y)
  • A worse-case analysis the biggest accumulated
    error

7
Background (5) experimental environment
  • Agrajag
  • Developed by Conrad Hughes for Dependability
    Infrastructure for Grid Services (DIGS) project
  • Define classic distribution functions, operations
    and numeric approximation of function
    combinations
  • http//sourceforge.net/projects/digs

8
Bell-Curve calculus (1) -- importance
  • Why Bell-Curve
  • An average case analysis likely or unlikely
  • Bell-Curve Normal Distribution
  • Easy to store and propagate
  • To deal with complex workflows efficiently
  • Commonly occurs in the real world

9
Bell-Curve calculus (2) -- importance
  • Evidence
  • Experimental evidence from DIGS
  • A possible approximation to probabilistic
    behaviour of run time, accuracy and reliability
    (mean time to failure)
  • Central Limit Theorem
  • The distribution of an average tends to be
    Normal,
  • even when the distribution from which the
    average
  • is computed is decidedly non-Normal.
  • May extend calculus to more complicated curves
    in due course

10
Bell-Curve calculus (3) -- definition
  • Normal Distribution (Bell-curve)

11
Bell-Curve calculus (4) -- definition
  • Three QoS properties
  • Run time, accuracy and reliability
  • Four ways of combining Grid services
  • Sequential
  • Parallel_All
  • Parallel_First
  • Conditional
  • So 12 fundamental combinations

12
Bell-Curve calculus (5) combination methods
  • Sequential
  • Parallel_All
  • Parallel_First
  • Conditional

13
Bell-Curve calculus (6) basic combination
functions
  • 12 bell-curve simple situations

Seq Para_All Para_Fir Cond
run time sum max min cond1
accuracy mult combine1 varies? cond2
reliability mult combine2 varies? cond3
14
Bell-Curve calculus (7) proposed work
  • Our proposed work
  • For each 12 functions, find function for
  • and in terms of , , and
  • Induce the 24 functions
  • By experiment using Agrajag
  • Find other suitable calculi to describe the
    combination functions

15
Bell-Curve calculus (8) -- sum
16
Bell-Curve calculus (9) -- max
17
Bell-Curve calculus (10) -- methodology
  • is the bell-curve approximation of
    the combination curve
  • experimental tasks
  • find functions to calculate and
  • e.g. for sequential/run time
  • ,
  • experiment with functions for and
  • determine ranges of acceptable error
  • plot 3D graph ( vs. vs. error)

18
Discussion (1)
  • A better representation of probabilistic
    behaviour of QoS properties?
  • e.g. log-normal calculus
  • More QoS properties?
  • e.g. failure detection time

run
run
service
down
failure detection system
suspect
confirm
time
failure detection time
19
Discussion (2)
  • f.d.t. An instantiation of run time
  • More combination situations?
  • e.g. voting

seq Para_All Para_Fir Cond
f.d.t. sum max min cond4
voting service
20
The end
  • Any questions?
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