A qos policy modeling language for publish subscribe middleware platforms
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A QoS Policy Modeling Language for Publish/Subscribe Middleware Platforms. Joe Hoffert, Doug Schmidt & Aniruddha Gokhale {jhoffert,schmidt,gokhale}@dre.vanderbilt.edu www.dre.vanderbilt.edu ISIS, Dept. of EECS Vanderbilt University Nashville, Tennessee June 21, 2007

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A qos policy modeling language for publish subscribe middleware platforms

A QoS Policy Modeling Language for Publish/Subscribe Middleware Platforms

Joe Hoffert, Doug Schmidt & Aniruddha Gokhale

{jhoffert,schmidt,gokhale}@dre.vanderbilt.edu

www.dre.vanderbilt.edu

ISIS, Dept. of EECS

Vanderbilt University

Nashville, Tennessee

June 21, 2007

DEBS 2007, Toronto, Canada

www.dre.vanderbilt.edu


Distributed real time embedded dre systems
Distributed Real-time & Embedded (DRE) Systems Middleware Platforms

  • Network-centric and large-scale “systems of systems”

    • e.g., industrial automation, emergency response

  • Different communication semantics

    • e.g., pub-sub

  • Satisfying tradeoffs between multiple (often conflicting) QoS demands

    • e.g., secure, real-time, reliable, etc.

  • Regulating & adapting to (dis)continuous changes in runtime environments

    • e.g., online prognostics, dependable upgrades, keep mission critical tasks operational, dynamic resource mgmt

DRE systems increasingly realized via system composition of services


Challenges in realizing dre systems

  • Variability in the Middleware Platformssolution space (systems integrator role)

  • Diversity in platforms, languages, protocols & tool environments

  • Enormous accidental & inherent complexities

  • Continuous evolution & change

Mapping problem artifacts to solution artifacts is hard

Challenges in Realizing DRE Systems

  • Variability in the problem space (domain expert role)

  • Functional diversity

  • Composition, deployment and configuration diversity

  • QoS requirements diversity


The omg data distribution service dds

Application Middleware Platforms

Application

read

write

write

Logical Data Store

Application

write

write

Application

read

read

Application

The OMG Data Distribution Service (DDS)

  • Provides flexibility, power and modular structure by decoupling:

    • Location – anonymous pub/sub

    • Redundancy – any number of readers & writers

    • Time – asynchronous, time-independent data distribution

    • Platform – similar to CORBA middleware

  • Architecturally Broken into:

  • Data Centric Publish/Subscribe (DCPS)

    • Lower layer APIs to exchange topic data based on QoS policies

  • Data Local Reconstruction Layer (DLRL)

    • Upper layer APIs that make topic data appear local


Qos policies supported by dds
QoS Policies Supported by DDS Middleware Platforms

  • DCPS entities (e.g., topics, data readers/writers) configurable via QoS policies

  • QoS tailored to data distribution in tactical information systems

  • Request/offered compatibility checked by DDS at Runtime

  • Consistency checked by DDS at Runtime

  • DEADLINE

    • Establishes contract regarding rate at which periodic data is refreshed

  • LATENCY_BUDGET

    • Establishes guidelines for acceptable end-to-end delays

  • TIME_BASED_FILTER

    • Mediates exchanges between slow consumers & fast producers

  • RESOURCE_LIMITS

    • Controls resources utilized by service

  • RELIABILITY (BEST_EFFORT, RELIABLE)

    • Enables use of real-time transports for data

  • HISTORY (KEEP_LAST, KEEP_ALL)

    • Controls which (of multiple) data values are delivered

  • DURABILITY (VOLATILE, TRANSIENT, PERSISTENT)

    • Determines if data outlives time when they are written

  • … and 15 more …


Qos policy configuration challenges

Reliable data transfer requested Middleware Platforms

Best effort data transfer offered

Data will not be transferred

X

Deadline’s period = 5 ms.

Time based filter’s minimum separation = 10 ms.

X

QoS policies will not be set

QoS Policy Configuration Challenges

  • QoS Policy Compatibility

    • QoS policies for the communicating entities must be compatible between what’s requested and offered

  • QoS Policy Consistency

    • QoS policies for any one entity must be consistent with each other

Need to flag errors earlier in the developmental lifecycle


Dds qos modeling language dqml 1 of 2
DDS QoS Modeling Language (DQML 1 of 2) Middleware Platforms

Focus on “correct by construction” – check for errors at design-time

  • Models relevant DDS entities

  • Models DDS QoS polices as first class entities

  • Models relationships between entities and QoS policies


Dds qos modeling language dqml 2 of 2

QoS Settings Middleware Platforms

QoS Settings

DataReader

DataWriter

DDS QoS Modeling Language (DQML 2 of 2)

  • Supports QoS compatibility and consistency constraint checking

  • Generates implementation artifacts (currently for DDS Benchmarking Environment (DBE))

DBE

Interpreter

DBE


Ongoing work dqml service orchestration
Ongoing Work: DQML + Service Orchestration Middleware Platforms

Work supported by DARPA PCES & ARMS Programs

  • CoSMIC tools e.g., PICML used to model application components, CQML for QoS

  • Captures the data model of the OMG D&C specification

  • Synthesis of static deployment plans for DRE systems

  • Capabilities being added for QoS provisioning (real-time, fault tolerance, security)

CoSMIC can be downloaded at www.dre.vanderbilt.edu/cosmic


Concluding remarks

QoS Settings Middleware Platforms

QoS Settings

Invoke the DBE

Interpreter

DBE

DataReader

DataWriter

Concluding Remarks

  • QoS configuration management is a significant challenge for pub-sub systems

  • Need design-time tools to automate the QoS configuration management

  • Need tools to assure “correct-by-construction” systems

  • Model-driven Engineering is a promising approach


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