Enabling Trustworthy Systems with the DDS Quality of Service Modeling Language

April 21, 2023 Joe Hoffert, Aniruddha Gokhale, Doug Schmidt

Enabling Trustworthy Systems with the DDS Quality of Service

Modeling Language

Joe Hoffert, Aniruddha Gokhale, Doug Schmidt{joseph.w.hoffert,a.gokhale,d.schmidt}@vanderbilt.edu


Outline• Trustworthy Systems via Model Driven

Engineering (MDE)• Use Case: Data Distribution Service (DDS)• DDS QoS Modeling Language (DQML)• DQML Metamodel Overview• DQML Application: DDS Benchmark

Environment (DBE)• DBE Interpreter• DQML Demonstration• Future Work


Trustworthy Systems (1/2)

• Security Technology– Software Security

• Software design– specification languages, methods, and tools

supporting security by design• Static code verification via:

– security-friendly APIs– disciplined styles of programming– automated tools for lightweight static checking

– Trusted Platforms• Understanding composition• Evaluating security and vulnerability• Examining minimal configurations

(hardware & software) that provide trusted platforms

• Systems Science– Model-Based Integration of Secure Systems

• model-based design• model transformation technology • Quality of Service (QoS)-enabled component

middleware

TRUST Goals for Enterprise Publish/Subscribe DRE Systems


• Manage inherent complexity– Scope models to area/level of concern– Compose larger scope using modeling

artifacts (e.g., application infrastructure/framework, higher level tools)

– Understand composition via separation of concerns

– Simplify vulnerability, provability analysis

Trustworthy Systems (2/2)

• Reduce accidental complexity– Increase confidence, reuse via MDE

tools– Close security loopholes via misused

tools, software, and configurations

Facilitation of TRUST Goals via Model Driven Engineering (MDE)


• Coupling of business logic, infrastructure, QoS configuration (i.e., all crafted in handwritten code)

• Intermixing of concerns/areas of focus• Lack of composition understanding• “Provability” via testing• Potential loopholes in untested code paths• Unintended functionality (i.e., design !=

implementation)

Non-Trustworthy Systems

Vulnerability, Lack of Confidence/Provability


Use Case: The OMG Data Distribution Service (DDS)

Application

Application

Application

Application

ApplicationLogical Data Store

read

read

read

write

write

write write

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 – same as 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• 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 …

• Implications for Trustworthiness


DDS QoS PoliciesInteractions of QoS Policies have implications for:

• Consistency/Validitye.g., Deadline period < TimeBasedFilter minimum separation (for a DataReader)

• Compatibility/Connectivitye.g., best-effort communication offered (by DataWriter), reliable communication requested (by DataReader)

DataWriter

Durability-Volatile

Durability-Transient

Reliability- Best EffortReliability-

Reliable

Deadline-10ms

Deadline-20ms

Liveliness-Manual By Topic

Liveliness-Automatic

Topic

Will Settings Be Consistent?Or Will QoS Settings Need Updating?

Timebased-15ms

DataWriter

DataReader

Will Data Flow?Or Will QoS Settings Need Updating?

DataReader


DDS Trustworthiness Needs (1/2)• Compatibility and Consistency of QoS Settings

– Data needs to flow as intended• Close software loopholes that might be maliciously exploited

– Fixing at code time untenable• Implies long turn-around times• Code, compile, run, check status, iterate• Introduces accidental complexity

• DDS QoS Modeling Language (DQML) models QoS configurations and allows checking at design/modeling time– Supports quick and easy fixes by “sharing” QoS policies– Supports correct-by-construction configurations

– Fixing at run-time untenable• Updating QoS settings on the fly• Introduces inherent complexity• Unacceptable for certain systems (e.g., RT,

mission critical, provable properties)


DDS Trustworthiness Needs (2/2)

• QoS configurations generated automatically– Eliminate accidental complexities

• Close configuration loopholes for malicious exploitation

– Decouple configurations from implementations• Refinement of configuration separate from

refinement of code

• DQML generates QoS settings files for DDS Applications– Creates consistent configurations– Promotes separation of concerns

• Configuration changes orthogonal to business logic changes

– Increases confidence

QoS Settings


DDS Application Development• Business logic/application code mixed with QoS

configuration code– Accidental complexity– Obfuscation of configuration concerns

• DQML decouples QoS configuration from business logic– Facilitates configuration

analysis– Reduces accidental

complexity

DataWriter QoS configuration & datawriter creation

QoS configuration & publisher creation

QoS Configuration Business logic

=Higher confidence DDS application


DQML Design Decisions

No Abortive Errors• User can ignore constraint errors• Useful for developing pieces of a

distributed application• Initially focused on flexibility

QoS Associations vs. Containment

• Entities and QoS Policies associated via connections rather than containment

• Provides flexibility, reusability• Eases resolution of constraint

violations


DQML Application: DDS Benchmark Environment (DBE)

• Part of Real-Time DDS Examination & Evaluation Project (RT-DEEP)

• http://www.dre.vanderbilt.edu/DDS

DataReader

DataReader

DataReader

DataWriter

DataWriter DataWriter

DataWriter

QoSQoS

QoS

QoSQoS

QoS

QoS

DataReader

QoS

• Developed by DRE Group at ISIS

• DBE runs Perl scripts to deploy DataReaders and DataWriters onto nodes

• Passes QoS settings files (generated by hand)

• Requirement for testing and evaluating non-trivial QoS configurations

http://www.dre.vanderbilt.edu/DDS




DBE Interpreter

Model the DesiredQoS Policies via DQML

Compicon.icoInvoke the DBEInterpreter

Generates One QoS Settings File for Each DBEDataReader and DataWriter to Use

DBE

QoS Settings

QoS Settings

DataReader

DataWriter

Have DBE Launch DataReadersand DataWriters with Generated

QoS Settings Files

No Manual Intervention


DQML Demonstration

• Create DDS entities, QoS policies, and connections

• Run constraint checking

• consistency check

• compatibility check

• fix at design time

• Invoke DBE Interpreter

• automatically generate QoS settings files


Future Work

• Incorporate into Larger Scale Tool Chains– e.g., Deployment and

Configuration Engine (DAnCE) in CoSMIC Tool Chain

• Incorporate with TRUST Trustworthy Systems– Combine QoS polices and patterns to provide higher level

services• Build on DDS patterns1

– Continuous data, state data, alarm/event data, hot-swap and failover, controlled data access, filtered by data content

1 Gordon Hunt, OMG Workshop Presentation, 10-13 July, 2006

• Fault-tolerance service (e.g., using ownership/ownership strength, durability policies, multiple readers and writers, hot-swap and failover pattern)

• Security service (e.g., using time based filter, liveliness policies, controlled data access pattern)

• Real-time data service (e.g., using deadline, transport priority, latency budget policies, continuous data pattern)


Backup Slides


DDS Domains & Domain Participants

1

2

31

2

3

1

1

DomainParticipant

Node

Domain 1

Domain 2 Domain 3

Node

NodeNodeNode

Node

• The Domain is the basic construct used to bind individual applications together for communication

• Like a VPN


DCPS EntitiesDCPS Entities include

– Topics

• Typed data

– Publishers

• Contain DataWriters

– Subscribers

• Contain DataReaders

– DomainParticipants

• Entry points

• Data can be accessed in two ways

– Wait-based (synchronous calls)

– Listener-based (asynchronous callbacks)

• Sophisticated support for filtering

– e.g., Topic, Content-FilteredTopic, or MultiTopic

• Configurable via (many) QoS policies

Topic Topic Topic

Data Reader

Data Writer

Data Writer

Data Reader

Data Reader

Data Writer

Subscriber PublisherPublisher Subscriber

Data Domain

Domain Participant

Documents

Enabling Trustworthy Systems with the DDS Quality of Service Modeling Language