model driven techniques for evaluating qos of middleware configurations arvind s. krishna, emre...
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Model Driven Techniques for Evaluating Model Driven Techniques for Evaluating QoS of Middleware ConfigurationsQoS of Middleware Configurations
Arvind S. Krishna, Emre TurkayAndy Gokhale, & Douglas C. Schmidt
Institute for Software IntegratedSystems (ISIS)
Vanderbilt UniversityNashville, TN 37203
Real-time Application Symposium (RTAS 2005)
San Francisco, California
Presentation SummaryComponent middleware technologies
• Focus on business logic
• Automates the plumbing code to configure & deploy middleware
• Component encapsulate business logic
• Difficulty in provisioning & deploying
• Error prone task of handcrafting XML
Model Driven Generative Technologies (MDD)
• Focus is on
• Modeling – System composition technique
• Validating – Correct by construction
• Generating – Deployment, configuration info
multiple layers of middleware
• Supports configuring, provisioning, & deploying quality of Service (QoS)-enabled middleware
This presentation addresses key configuration & QoS evaluation challenges of middleware for DRE applications
Motivating DRE Application
Robot Assembly Application• Human Machine Interface (HMI) Component – human accepts/rejects watch
• Management Work Instructions (MWI) Component – decide what action to perform on the watch, e.g. set the appropriate time
• Watch Setting Manager (WSM) Component– Executes action on every watch
Goal• Increase number of
items processed by minimizing end-to-end latency
• Palette Conveyor Manager (PCM) Component – Watch Assembly line that moves watches from source to destination
• Robot Manager Component – Robotic Arm that moves the watches
Robot Assembly Challenges (1/2)Configuration Challenges • Map component level features & requirements to middleware configurations• WSM component interacts with HMI & Pallet Manager Component
• Configuring component properties• Configuring package properties • Configuring underlying middleware
Hook for the concurrency strategy
Hook for the request demuxing strategyHook for
marshaling strategy
Hook for the connection management strategy
Hook for the underlying transport strategy
Hook for the event demuxing strategy
Robot Assembly Challenges (2/2)
Configuration Evaluation Challenges
• How do we make sure chosen middleware configurations lead to overall goal of the system
• Minimizing end-to-end latency of the overall system
• What configuration of middleware hosting HMI & WSM components lead to best end-to-end latency
HumanMachineInterface
ManagementWork
Instructions
WatchSettingManager
RobotManager
PalletConveyorManager
Critical Flow Path
Research Challenges
CoSMIC
packaging
asse
mbl
y
specification
configuration
plan
ning
feedback
Component Developer
Component
ResourceRequirements
Impl
Impl
Impl
Properties
(1) d
evel
ops
Component Assembler
Component Assembly
Component Component
Component Component
(2) assembles
www.dre.vanderbilt.edu/cosmic
Component Package
Component Assembly
Component Component
Component Component
Component Assembly
Component Component
Component Component
Component packager
(3) packages
Component configurator(4
) con
figur
es
Component deployer
(5) deployment planningAssembly
DeploymentApplication
Assembly
Assembly
(7) feedback to
configuration &
planning
Analysis & Benchmarking
systemanalyzer
(6) analysis & benchmarking
Ensuring syntactically &
semantically valid middleware
configurations
Understanding consequences of
deployment decisions on overall QoS
Alleviating accidental complexities in evaluating/
benchmarking QoS
Resolving Configuration Challenges (1/2)Context
•Different middleware implementations provide different configuration mechanisms to configure the middleware
• CIAO provides service configuration options to tune middleware performance
• www.dre.vanderbilt.edu/ CIAO.html
ProblemThis approach is error prone since:•Need to know the syntax•Need to remember names of strategies•Need to know compatible strategies
Solution
•Developed a domain-specific modeling language for TAO/CIAO called Options Configuration Modeling Language (OCML)
•OCML ensures syntactic & semantic validity of middleware configurations•Detect error at model construction time
•OCML is used by
•Middleware developer to design the configuration model
•Application developer to configure the middleware for a specific application
•OCML metamodel is platform-independent
•OCML models are platform-specific
• Generates a Wizard to set configuration options and provides documentation for each option
Resolving Configuration Challenges (2/2)
Resolving Evaluation Challenges (1/3)
Context• Component integrators must make appropriate deployment decisions,
including identifying the entities (e.g., CPUs) of the target environment where the packages will be deployed
HumanMachineInterface
WatchSettingManager
PalletConveyorManager
RobotManager
ProblemHow to ensure a particular deployment configuration meets QoS requirements
How do we simulate load & background load for benchmarking?
How do we measure & monitor QoS for a given deployment
How do we measure & monitor QoS for a given deployment
Resolving Evaluation Challenges (2/3)
Solution• Provide a model-driven tool-
suite to empirically evaluate & refine configurations to maximize application QoS
BGML Workflow
1. End-user composes the scenario in the BGML modeling paradigm
2. Associate QoS properties with this scenario, such as latency, throughput or jitter
3. Synthesize the appropriate test code to run the experiment & measure the QoS
4. Feed-back metrics into models to verify if system meets appropriate QoS at design time
Component Interaction
Experimenter
BGML
ModelExperimet
AssociateQoS
Characteristics
Synthesize&
ExecuteFeedback
Test bed
1 2
34
IDL .cpp
Scriptfiles
•The tool enables synthesis of all the scaffolding code required to set up, run, & tear-down the experiment
•Using BGML it is possible to synthesize:• Benchmarking code• Component implementation code• Build & Component IDL files
Resolving Evaluation Challenges (2/3)
• Each configuration option can then be tested to identify the configuration that maximizes the QoS for the scenario
• These empirically refined configurations can be reused across applications that have similar/same application domains
• These configurations can be viewed as Configuration & Customization (C&C) patterns
template <typename T>voidBenchmark_AcceptWorkOrderResponse<T>::svc (void){ ACE_Sample_History history (5000); ACE_hrtime_t test_start = ACE_OS::gethrtime ();
ACE_UINT32 gsf = ACE_High_Res_Timer::global_scale_factor (); for (i = 0; i < 5000; i++) { ACE_hrtime_t start = ACE_OS::gethrtime (); (void) this->remote_ref_-> AcceptWorkOrderResponse (arg0, arg1); ACE_CHECK; ACE_hrtime_t now = ACE_OS::gethrtime (); history.sample (now - start); }}
• BGML allows actual composition of target interaction scenario, auto-generates benchmarking code
Problem• Using each tool in isolation does not provide complete information• OCML does not know about performance • BGML does not know what the configuration is
Need for Tool Integration (MDD Process) (1/2)
Context
• OCML tool resolves accidental complexity in configuring components
• BGML tool resolves accidental complexity in evaluating QoS
OCML Correct Configuration
HumanMachineInterface
BGML Measures critical flow path latency
Need for Tool Integration (MDD Process) (2/2)
Solution MDD ProcessMDD Process leveraging PICML, OCML & BGML
• PICML interaction scenario, Deployment & Component configuration
• OCML Model middleware hosting individual Components
• BGML Capture Evaluation Concerns OCML
PICML
BGML
MDDProcess
Apply MDD process to DRE application scenario to answer:
• How does Middleware Configuration affect QoS?
• How do Deployment decisions affect QoS?
Candidate configuration (s)
Least latency
MDD Process (1/3)
Step 1: PICML Tool• PICML used to generate deployment plan information
Step 2: Middleware Configuration• OCML associated with Implementation Artifacts
• OCML provides a wizard with documentation to configure the artifacts
• Configuration of middleware that hosts the “executors” a.k.a Servants in CORBA 2.0
Virtual nodes
Process Collocation
Mapping
DocumentationPane
Option selection
Artifact
MDD Process (2/3)Step 2 Choosing Configurations
• How best to configure middleware hosting HMI and WSM components to minimize end-to-end latency
• Component roles
•Display component – pure client
•Watch Manager component – “peer role” does not need concurrency
• For each component (Display) narrow down selected configurations
•Fixed part – determined a priori
•Dynamic – cannot determine without testing
HMI Component
WSM Component
Configuration Space
Step 3 Capturing QoS concerns
• Profile & Generate Multiple work-orders exchanged between Watch Manager Component and Human for Acceptance/Rejection
• Use Timers to measure end-to-end critical path latency in the scenario
• Same code can be used to evaluate different combinations of configurations
MDD Process (3/3)
Workspace & Glue Generation
• Create workspace and projects to generate build files for the scenario
Time-stamp send & receive
Load generator for
the accept operation
To enact a scenario, this process automates:• Deployment Plan – XML deployment
information• svc.conf – Configuration for each
component implementation• Benchmark code – source code for
executing benchmarks• IDL & CIDL files• Build Files – MPC files (www.ociweb.com)
workspace { RobotManager WatchSettingManager PalletteConveyorManager HumanMachineInterface ManagementWorkInstructions}
Projects having artifacts
Solution
Experimental Results / Highlights (1/3)
Automation / Code Generation
Experiment Execution
• Totally we conducted 64 experiments for different combinations of Human Machine Interface & Watch Setting Manager Components
• The latency measures were tabulated to look for the configuration that minimized latency
• Corresponding end-to-end measures were also checked
DRE Experimental Scenarios
Total Files/Lines of Code Required
Automated by MDD Process
•Robot Assembly
•Basic SP
•65 files (includes IDL/CIDL) generated files
•54 files (includes IDL/CIDL) generated files
•For Robot Assembly number of files automated 60 (script files not generated yet..)
•For BasicSP 49 files are auto-generated
Automated execution of experiments: scripts used to set-up & tear down experiments
Experimental Results / Highlights (2/3)
Observations
• Similar configurations affected QoS similarly
• For both cases we observed (G1,H1,I2,J2) minimized latency the most
• Both cases showed that G is the most important configuration
• Penalty for not setting G to G1 is ~4 µsecs in BasicSP & ~60 µsecs in RobotAssembly
• Other options are not important, i.e., setting them or leaving to defaults leads to same behavior
• Figure shows a visualization of the configuration space
• Circles represent a point in the configuration space
• Edge represents the distance (performance) degradation from moving from one point to another
Defining operating regions enable setting more important configurations allowing flexibility in others
Experimental Results / Highlights (3/3)
• How does platform affect QoS?
• Providing feedback on deployment plan i.e. Provides Component – Node mappings
• BasicSP scenario
• Tried two combinations as shown in table
• Process
• No changes required from earlier experiment: capture same end-to-end latency
• Change component node mapping to re-generate the deployment plan
• Observe & tabulate latency changes
• Real-time component placement decided a priori software tied to the hardware
• During failure:
• Important to decide where to place components to ensure QoS
•This process aids for making this decision
ACEDOC
TANGO
Ethernet
DisplayAirframe
GPS
ACEDOC
TANGO
Ethernet
GPSAirframe
Display
Concluding Remarks
• MDD process provides a flexible model-based approach for evaluating QoS of middleware configurations
• Auto-generates most of the code required to run the experiment
• OCML does not automatically generate configuration space
• The script for automatically evaluating different configurations was not generated
• Feedback to “Planner” allows refinement of configuration during testing phase
Our Future work:
• EMULab ns style script generation for easy simulation
• Strategies for interfacing with higher level performance monitoring tools
PatternsDatabase
Scoreboard
IdentifyConfiguration
Patterns
Map Features toConfigurations
• Identifying patterns in configuration allows mapping features directly onto middleware configurations
Downloading the Middleware & Tools
•http://www.dre.vanderbilt.edu/cosmic
• Beta & stable releases can be accessed from http://www.dre.vanderbilt.edu/Download.html
OCML & BGML are part of the CoSMIC MDD tool suite