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Compositional Analysis Framework using EDP Resource Models

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units of resource in every time units. Bandwidth / as component interface ... Repeat supply every time units. 12. Supply bound function (sbf ) lsbf. W. t. Q. P ... – PowerPoint PPT presentation

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Title: Compositional Analysis Framework using EDP Resource Models


1
Compositional Analysis Framework using EDP
Resource Models
  • Arvind Easwaran, Madhukar Anand, Insup Lee
  • Real-Time Group
  • University of Pennsylvania

2
Outline
  • Compositional schedulability analysis
  • Hierarchical scheduling frameworks
  • Periodic resource models
  • EDP model based interfaces
  • Model definition and properties
  • Notions of optimality
  • Techniques for interface generation

3
Compositional Schedulability Analysis
4
Hierarchical Scheduling Framework
  • Sporadic task
  • T (p,e,d), d ? p
  • Notations
  • Leaf ? C1, C2, C3
  • Non-leaf ? C4, C5
  • Uniprocessor platform

5
Compositional Analysis
6
Resource model interface
  • Characterization of resource supply
  • Partial resource supply bounded-delay, periodic
  • Periodic resource model ? (?,?)
  • ? units of resource in every ? time units
  • Bandwidth ?/?
  • ? as component interface
  • Schedulability condition for component under ?

7
Schedulability conditions
  • A leaf component C with EDF is schedulable using
    a periodic resource model ? (?,?)
  • sbf?(t) Supply bound function Minimum resource
    supply of model ? in any time interval of length
    t
  • lsbf?(t) Linear lower bound of sbf?(t)

if and only if, for all t LCM, dbfC(t)
sbf?(t)
if, for all t LCM, dbfC(t) lsbf?(t)
  • A leaf component C with DM is schedulable using a
    periodic resource model ? (?,?)

if and only if, for all i, exists t di,
rbfC,i(t) sbf?(t)
if, for all i, exists t di, rbfC,i(t)
lsbf?(t)
8
Compositional Analysis
Task (p,e,d)
9
Sub-optimality of periodic interfaces
  • R1 Use of lsbf? instead of sbf?

To reduce starvation length, one must increase
bandwidth
  • R2 Mapping ? (?,?) ? T? (?,?,?)

? (?,?)
?(?,??),?gt0
  • R3 Dependency between starvation
  • length and bandwidth in sbf?

dbf
10
EDP resource model based interfaces
11
What are they?
  • Explicit Deadline Periodic resource
  • Specification ? (?,?,?)
  • Explicit deadline ?
  • ? resource units in ? time units
  • Repeat supply every ? time units

12
Supply bound function (sbf?)
  • sbf?(t)
  • lsbf?(t)

Q
lsbf
(
t
)
(
t
(
2
)
)

-
P

D
-
Q
W
1
2
4
4
3
4
4
P

Bandwidth
Starvation length
13
Schedulability conditions
  • A leaf component C with EDF is schedulable using
    a EDP resource model ? (?,?,?)

if and only if, for all t LCM, dbfC(t)
sbf?(t)
  • A leaf component C with DM is schedulable using a
    EDP resource model ? (?,?,?)

if and only if, for all i, exists t di,
rbfC,i(t) sbf?(t)
14
Bandwidth optimal interface
  • Given leaf component C, period ?
  • Compute ? and ?
  • Relation between ? and ? desired
  • We use bandwidth optimality
  • Minimizes resource bandwidth ?/?
  • Occurs when ?? (Theorem 3.2)

15
Bandwidth-deadline optimal
  • Choose interface with Largest ? among all
    bandwidth optimal interfaces
  • Reduced demand for composition
  • Interface generation procedure
  • Set ??, compute ? (?,?,?)
  • Set ??, compute ? (?,?,?)

16
EDP Interface Composition
Task (p,e,d)
17
Addressing Sub-optimalities
  • R1 Use of lsbf instead of sbf
  • R2 Mapping from resource model to
    periodic task
  • R3 Dependency between starvation
  • length and bandwidth in sbf

18
Addressing R1
  • Function y takes only two values
  • yk or k-1, where t k??
  • Solving eqn. dbfC(t) sbf?(t) (Algorithm 1)
  • Fix y, solve for ?
  • No need to use lsbf?

19
Addressing R2
  • Mapping under EDF (Definition 5.2)
  • ?(?,?,?) ? T?(?,?,??-?)
  • Demand-supply optimal (Theorem 5.3)
  • R ? Any uniprocessor resource supply
  • sbfR ? sbf? if and only if R satisfies task T?

20
Addressing R3
  • Dependency between starvation length and
    bandwidth in sbf

Reduce starvation length without increasing
bandwidth
? (?,?,?)
?(?,?,?-?),?gt0
dbf
21
Conclusion and future work
  • Conclusion
  • Introduced EDP resource model interfaces
  • Developed compositional analysis techniques
  • Similar techniques under DM scheduler
  • Future work
  • Support for incremental analysis
  • Independence from order of composition
  • Development of bandwidth bounds
  • Comparison to different resource models

22
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