QUICKER: A Model-driven QoS Mapping Tool for QoS-enabled Component Middleware - PowerPoint PPT Presentation

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QUICKER: A Model-driven QoS Mapping Tool for QoS-enabled Component Middleware

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Raise the level of abstraction. Support a number of Quality of Service (QoS) ... Uses Bogor Input Representation (BIR) at a higher level of abstraction ... – PowerPoint PPT presentation

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Title: QUICKER: A Model-driven QoS Mapping Tool for QoS-enabled Component Middleware


1
QUICKER A Model-driven QoS Mapping Tool for
QoS-enabled Component Middleware
Amogh Kavimandan, Krishnakumar Balasubramanian,
Nishanth Shankaran, Aniruddha Gokhale, Douglas
C. Schmidt schmidt_at_dre.vanderbilt.edu
2
Background
  • COTS middleware technologies
  • Raise the level of abstraction
  • Support a number of Quality of Service (QoS)
    configuration knobs
  • Flexibility in configuration complicates DRE
    system development
  • System QoS now depends on how middleware is
    configured
  • Achieving desired QoS increasingly becoming
    configuration problem than design problem

Lack of effective QoS configuration tools result
in QoS policy mis-configurarions that are hard to
analyze debug
3
Motivating Application
  • NASAs Magnetospheric MultiScale (MMS) space
    mission
  • Consists of four identically instrumented
    spacecraft, ground control system
  • Collect mission data
  • Send it to ground control at appropriate time
    instances
  • MMS mission QoS requirements span across two
    dimensions
  • Multiple modes of operation
  • Varying importance of data collection activity of
    satellite sensors
  • Need to translate QoS requirements into QoS
    options as well as resolve QoS dependencies

4
Challenge 1 Translating policies to
configuration options
Prioritized service invocations (QoS Policy)
needs to be mapped to Banded Connection (QoS
configuration)
  • Large gap between application QoS policies
    middleware QoS configuration options
  • Necessary to realize the desired QoS policies
  • Not a straightforward mapping
  • Requires understanding of middleware
    configuration space
  • e.g., multiple levels of QoS requires configuring
    appropriate number of thread pools, threadpool
    lanes (server) and banded connections(client)

5
Challenge 2 Choosing appropriate values for QoS
options
  • Individually configuring components is tedious
    error-prone
  • e.g., 140 QoS options for MMS mission
  • Choosing valid values for configuration options
    inherently doesnt scale well as size of
    application increases

6
Challenge 3 Validating QoS options
  • Each QoS option value chosen has to be validated
  • Every system reconfiguration (design time) should
    be validated
  • e.g., reconfiguration of bands of Analysis should
    be validated such that the modified value
    corresponds to (some) lane priority of Comm
    component

6
7
Challenge 4 Resolving QoS options
dependencies(2/2)
ThreadPool priorities of Comm should match
priority bands defined at Gizmo
  • Manually tracking dependencies difficult or in
    some cases infeasible
  • Dependent components may belong to more than one
    assembly
  • Dependency may span beyond immediate neighbors
  • e.g., dependency between Gizmo and Comm
    components
  • Empirically validating a change in configuration
    slows down design process considerably
  • Several iterations before desired QoS is achieved
    (if at all)

7
8
Solution Approach Model-Driven QoS Mapping
  • QUality of service pICKER (QUICKER)
  • Allows modeling of application QoS policies
  • Provides automatic mapping of QoS policies to
    configuration options
  • Allows validating the generated QoS options
  • Automated QoS mapping and validation process
    can be used iteratively in the design process

9
Enabling Technologies
  • Enhanced Platform Independent Component Modeling
    Language (PICML), a DSML for modeling CCM
    applications
  • QoS Mapping using Graph Rewriting and
    Transformation (GReAT) model transformation tool
  • Customized Bogor model-checker to define new
    types and primitives to validate QoS options
  • Uses model interpreters to automate generation of
    system specification in Bogor

9
10
QUICKER concepts Transformation of QoS
policies(1/2)
  • Representation of application QoS policies
  • Platform-independent semantics closely follow
    application QoS requirements
  • Representation of policies at component- or
    assembly-level
  • Representation of QoS options
  • Component QoS Modeling Language (CQML) captures
    CCM-specific QoS configuration options

RequirementProxy can be per component or assembly
instance
11
QUICKER concepts Transformations of QoS
policies(2/2)
  • Translation of policies into QoS options
  • Semantic translation rules specified in terms of
    input (PICML) and output (CQML) type graph
  • QUICKER Transformation engine performs mapping of
    QoS policies (in PICML) to QoS configuration
    options (in CQML)

11
12
QUICKER concepts Validation of QoS options(1/2)
  • Representation of middleware QoS options in Bogor
  • Bogor extensions allow representing domain-level
    concepts of system model
  • QUICKER defines new Bogor extension for QoS
    options
  • Uses Bogor Input Representation (BIR) at a higher
    level of abstraction
  • e.g., Component, lane, band etc. data types
    defined in QoS extensions
  • Reduces size of the system model by avoiding
    (redundant) auxiliary variables in specification

13
QUICKER concepts Validation of QoS options(2/2)
  • Representation of properties (that a system
    should satisfy) in Bogor
  • BIR primitives define language constructs to
    access manipulate domain-level data types
  • Used to define rules that validate options and
    check if property is satisfied
  • Used to construct dependency structure of
    components which is needed for validation of
    connected components
  • Automatic generation of BIR specification from
    CQML models

Rule determines if ThreadPool priorities at Comm
match with priority bands at Analysis
13
14
Resolving Challenge 1 Translating policies to
options (1/2)
  • Expressing QoS policies
  • Allow modeling application-level QoS policies at
    high-level of abstraction
  • e.g., Multiple service levels support for Comm
    component, service execution at varying priority
    for Analysis component
  • Reduces modeling effort ( 25 QoS policy elements
    for MMS mission)

15
Resolving Challenge 1 Translating policies to
options (2/2)
  • Mapping policies to options
  • Model transformations automate the tedious
    error-prone translatation process
  • Reduced development time
  • Transformations generate QoS configuration
    options as CQML models
  • Allow further analysis/transformation by other
    tools
  • Traceability in development process

15
16
Resolving Challenges 2 3 Ensuring validity of
QoS options
  • Model interpreter used to generate BIR
    specification from CQML models
  • BIR primitives used to check whether a given set
    of QoS options satisfies a system property
  • e.g., fixed priority service execution, a
    property of Comm component
  • Supports iterative validation of QoS options
    during QoS configuration process

17
Resolving Challenge 4 Resolving QoS options
dependencies
  • Use dependency structure to track dependencies
    between QoS options of connected (e.g., Comm and
    Analysis) or dependent (e.g., Comm and Gizmo)

Detect mismatch if either values change
  • Change(s) in
  • QoS options of
  • dependent component(s) causes detection of
    potential mismatches
  • e.g, dependency between gizmo invocation priority
    and Comm lane priority values
  • Dependencies resolved at design time

18
Related Work
  • Functional Specification Analysis Tools
  • Hatcliff, J. et. al. (2003). Cadena
  • QoS Adaptation Modeling Tools
  • Ye, J. et. al. (2004). DQME
  • Zinky, J., (1997). QuO
  • QoS Specification Tools
  • Ritter, T. et. al. (2003). CCM QoS MetaModel
  • Ahluwalia, J. et. al. (2005). Model-based
    Run-time
  • Monitoring
  • Frolund, S. et. al. (1998). QML
  • Schedulability Analysis Tools
  • Madl, G. et. al. (2004). Automatic
    Component-based system verification
  • Kodase, S. et. al. (2003). AIRES

18
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Concluding Remarks
  • QUICKER
  • Model-Driven Engineering (MDE)-based approach
  • Maps application-level QoS policies to
    middleware-specific QoS configuration options
  • Model transformations automatically generate QoS
    options
  • Model-checking extensions ensure validity of QoS
    options at component- and application-level

Available as Open-Source tools http//www.dre.vand
erbilt.edu/CoSMIC
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