Infosphere:
A Midterm Update on Infopipes
Calton Pu
Professor and John P. Imlay, Jr. Chair in Software
Georgia Institute of Technology
 2003 Calton Pu and Georgia Institute of Technology
Infosphere
Ubiquitous Computing
Plenty of computers (Moore’s Law)
 Are everywhere, all connected, almost free
 Know Everything
 5 IT Expeditions in 1999 (e.g., MIT’s Oxygen)
Information is where value is
 Paying distributed applications (DL, EC)
 Cheap disks connected by cheap bandwidth
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Problem: too many sources,
too much information
Internet:
Information Jungle
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Infopipes
Clean, Reliable,
Timely Information,
Anywhere
Digital
Earth
Personalized
Filtering &
Info. Delivery
Sensors
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• Freeway Surveillance
• 80+ PTZ Cameras
• 500+ VDS Cams
• Many info sources
• Potential direct input
• Instrumented cars
• Trucks and others
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RT Traffic Optimization
Central traffic control scenario
 Car navigational system registers route
 Control sends back detailed traffic info/estimate
 When rerouting: register the new route
Peer-to-peer scenarios
 Taxi/delivery trucks exchange information
 Opposite direction cars know what’s ahead
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Emergency Response
Increasing importance after 9/11, Iraque
Proactive planning, handling, response
 Hurricanes, tornados, presidents, etc
 Real-time observation and forecasting of exact
route for “big events”
 Get out of harm’s way, get back to help
 A few minutes can make a big difference
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Infopipes: Backbone of Infosphere
Active
Control
High
Bandwidth
Long Latency
Infopipe
Composition
Personalized
Filtering
survivable
Quality
Annotations
 Syntax, semantics, QoS
?
 Property preserving
Preserved
Information
Quality
composition of Infopipes
 Timely delivery of high
quality fresh information
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Infopipe Abstraction
Syntax, semantics, QoS requirements
Component Infopipes
 Ends: Typespec, property specifications
 Middle: processing, buffering, active
Composition of Infopipes
 End-to-end QoS property preservation
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Goals for ISL/ISG
 ISL – Infopipe Specification Language




Simple description for Infopipes
Support datatypes
Support serial composition
QoS requirements
 ISG – Infopipe Stub Generator
 Generate datatypes, communication stubs
 Support multiple communication layers
 Support multiple implementation languages
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Infopipe Internals
Information flow driven
 Middle method by hand
 ISG generates the rest
XML
parser
Stub
Consumer-end
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XML
$a $b
Infopipe
XML
Middle
method
void
func (a, b) {
…
c = a + b;
}
Stub
XML
XML
generator
Producer-end
XML
$c
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Infopipe Software Architecture
ISL Spec
GUI
XIP Spec
ECho
Multi-stage translators
Java RMI
Sockets
CORBA
A/V Stream
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Multi-Stage Translation
XIP Spec
XIP + build
Fill Repository
Repository
Custom Translators
<build>
commands
XIP assembly
XIP+
XSLT Translators
Templates
Apply templates
XIP
+
code (w/jpt)
Aspects
Execut.
Source
AXpect weaver
XIP
+
woven code
XSLT Translators
Write Files
C ECho
Java Sockets
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C Sockets
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Demo Scenario
Big-picture image stream
UAV video
UAV video
Subsample
Color
Reduction
Window
Filter
Reduce
Rate – 2x
UAV video
Subsample
Color
Reduction
Team video
Reduce
Rate – 10x
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Mobile Command
Receiver controls signals
through remote data reduction
Window
Filter
Reduce
Rate – 2x
Team video
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Demo Application – Sensor Streams in
Wired and Wireless Environments
Multiple
Wireless
Media
Command Post
Wired Media
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Ptolemy Design Tool
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UAV: datatype, filter, pipe
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XML description
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Ptolemy => ISL/XIP
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XIP => Gen code
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Multiple Language/API Bindings
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Generating Multiple Languages
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Code Generation
& Compilation
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UAV Sender
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UAV Receiver: Adaptation + Control Interface
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Scaling Filter
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Scaling + B/W
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Encryption (Symmetric)
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JPEG (factor of 1/25)
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Infopipe and Software Eng.
QoS/QoI support implemented with AOP
 QoS dimensions: performance, security, etc
 Performance monitoring, recording, adjusting
Feedback-based QoS maintenance
 Monitoring at each stage of information flow
 Make adjustments when QoS exception raised
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XIP Benefits
 Extensible XML intermediate representation
 Several abstract machines, custom code
 Datatypes, Filters, Pipes, Serial composition
 Easy addition of AXpect
 Good XML software tools
 XSLT Modularity (xsl:include)
 Meta programming through templates
 Leveraging future XML tool development
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An Aspect
Pointcut: selects joinpoint in XIP from generated code
Joinpoint: Added in aspect, or
from generated code
<xsl:template
match="//filledTemplate[@name=$pipename][@inside=$inside]//jpt:pipe-middle">
struct timeval base;
struct timeval end;
<jpt:time-process>
// take timing here
gettimeofday(&amp;base,NULL);
<xsl:copy>
<xsl:apply-templates select="@*|node()"/>
</xsl:copy>
gettimeofday(&amp;end,NULL);
usec_to_process = (end.tv_sec - base.tv_sec )*1e6+(end.tv_usec - base.tv_usec);
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fprintf(stdout,"Time to process: %ld\n", usec_to_process);
</jpt:time-process>
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</xsl:template>
AXpect Weaver
Aspect
XIP
Code
Generation
WSLA
Aspect
Weaver
Source
Code
ISG
 XIP specification has apply-aspect commands
 Aspects are XSLT, operate on XIP + generated code
 Aspects can refer to outside XML (e.g. WSLA) for
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
Source code: C, C++, Java
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An AOP Experiment
 Infopipe: Image stream sender to receiver
 Receiver has CPU usage limits
 Aspects build on top of other aspects (e.g. CPU usage
computation requires timing info)
 Rate control aspect governs receiver CPU usage through
sender rate adjustment
 Aspect code accounts for 348 of 1135 NCLOC (31%)
 Aspects affect 9 of 14 generated files
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Specialization of Infopipes
Specialization of Infopipes
 Tools: Tempo-C and Java partial evaluator
 Goal: reduce interpretation of data (2nd
example later)
Producers
PBIO/XML
parser
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Consumer
Stub
Middle
Method 1
Stub
PBIO/XML
parser
Producer
PBIO/XML
PBIO/XML
generator
parser
Stub
Middle
Middle
Method 1
Method 2
Consumers
Stub
Stub
Middle
Method 2
Stub
PBIO/XML
generator
PBIO/XML
generator
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Infopipe Further Details
Connector Stub Port Middle Port Stub Connector
• Middle : Pipe’s processing module
• Port : Communication endpoint abstraction
• Stub : Data marshalling
• Connector : Communication runtime, Handles
connection info
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Pipe Connectors
… Middle Port Stub Connector
Connector Stub Port Middle
…
 Each port can be plugged with different
types of stubs and connectors
 Currently we have 3 types
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 Socket connector
 IPC(unix pipe) connector
 Function connector
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Replugging (Same Machine)
Middle
Port
Socket Socket
Stub Connector
IPC
IPC
Stub Connector
Socket Socket
Port
Connector Stub
Middle
IPC
IPC
Connector Stub
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Replugging (Same Process)
Pipe 1
… Middle1 Port
IPC
IPC
Stub Connector
…
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Pipe 2
Middle1 Port
IPC
IPC
Port Middle2 …
Connector Stub
Function
Middle2
Stub
…
•Pipe 1, 2 are collapsed into one pipe
•Pipe 1 loads Pipe 2’s middle code dynamically
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Port Code Example
Same Interface: pipeSource->outPorts[“out1”]->push(item);
Port::push(item)
{
lock(stub); // for replugging synchronization
stub->push(item);
unlock(stub);
}
StubSocket::push(item)
{ marshal(item, buf);
conn->send(buf);
}
ConnSocket::send(buf)
{ send(sock, buf);
}
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StubIPC::push(item)
{ marshal(item, buf);
conn->send(buf);
}
ConnIPC::send(arg)
{ write(pipe_fd, arg);
}
StubFunction::push(item)
{
nextPipe->middle
->process(item);
}
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Benchmark Results
 Send 8 byte data
(in the same machine)
Socket
IPC
Function
41.7 us
12.6 us
1.8 us
 (Manually specialized)
Specialization cost
Socket->IPC
1127.6 us
IPC->Function
1045.7 us
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Project Summary
Infopipe: Distributed information flows
 ISL, GUI, XIP
ISG and software engineering tools
 AOP and AXpect
 Specialization of Infopipes
End-to-end QoS properties
 Performance, maintainability, scalability
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Fresh Information
On the World
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