control & computing in embedded systems
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Control & Computing in Embedded Systems. Moonju Park. Challenges: Embedded Systems Design. Time to market puts pressure on design time The increased complexity (# of components/lines of code, hetereogeneity , distributed/networked) demands increased system design productivity - PowerPoint PPT PresentationTRANSCRIPT
Control & Computing in Embedded Systems
Moonju Park
Challenges: Embedded Systems Design
• Time to market puts pressure on design time• The increased complexity (# of components/lines of code,
hetereogeneity, distributed/networked) demands in-creased system design productivity
• Quality of new predictable, dependable designs has to improve.
• Moving from feasible to optimal systems requires new radical design processes and tools.
Increasing cost of quality and declining product prices
12.5%
8.2%
10.4%
3.0%
5.0%
9.1%
4.3%
2.6%
0%
5%
10%
15%
2003 2004 2005 2006
Mp3PlasmaDVDOther CE
73.9%
6.2%
15.2%1.5%
3.2%
100%
0%
20%
40%
60%
80%
100%
Revenue COGS R&D Other SGA CoQ Profit
2006 Company Operating Expense
While CoQ to Sales is increasing for innovative products, those same products are becoming a larger portion of the product mix
Failure to aggressively manage Cost of Quality can lead to a reduction in already-slim profit margins
Cost of Quality (CoQ) as Percent of Revenue
Innovative products that are fueling growth in CE are often more expensive to fix than traditional products
Rapid price erosion is outpacing reductions in CoQ, resulting in a projected increase in the CoQ/Sales ratio for CE manufacturersSource: IBM Analysis
Consumer Electronics Example
Service Industrialization of Manufacturing
• Manufacturing to services shift– IT leads the change
Value creation
R&DManufacturing
Service
Environment is changing: Networked Embedded Systems
• Embedded systems are becoming increasingly networked– Controller-area-networks
(CAN) bus in automobiles– Services in large build-
ings are now run across networks
• e.g. heating, lighting, security
So, what service?
ANOTHER BEERPLEASE HAL…
I’M SORRY DAVE, ICAN’T DO THAT. THEBATHROOM SCALES
AND THE HALL MIRRORARE REPORTING
DISTURBING FLAB ANOMALIES
Cyber-Physical System (CPS)
Definition: Integrations of computation and physical pro-cesses
Defining characteristics Cyber capability in every physical component Networked at multiple & extreme scales Complex at multiple temporal & spatial scales Dynamically reorganizing/reconfiguring High degrees of automation Unconventional computational & physical substrates Operation must be dependable
Goals Integrated physical and cyber design New science for future engineered systems (10~20 year per-
spective)
Current status ofreal-time systems
• Success stories– Spaceships in NASA– Military applications– Application to embedded systems
• Voices from outer-community– Unrealistic: model does not fit to many.– Low utilization– Expensive to implement– High-performance will do– We cannot find any real-time application around.
A CPS Example: Electric power grid
• Current– Equipment protec-
tion devices trip lo-cally
– Cascading failure• Future?
– Real-time coopera-tive control of pro-tection devices
– Self-healing
Another view from Another perspective:A DDDAS Model
(Dynamic, Data-Driven Application Systems)
S p e c t r u m of P h y s i c a l S y s t e m s
Humans3 Hz.
Cosmological:10e-20 Hz.
Subatomic:10e+20 Hz.
ComputationalInfrastructure(grids, perhaps?)
Models
Computations
Discover, Ingest, Interact
Discover,Ingest,Interact
sensors & actuators s & a
A DDDAS Example: Forest Fires
Kirk Complex Fire. U.S.F.S. photo
FireFighters
Policy,Planning,Response
AtmosphericModel
Fire Prop.Model
CombustionModel
Societal Challenge• How can we provide people and society with
cyber-physical systems they can bet their lives on?– Expectations: 24/7 availability, 100% reliability,
100% connectivity, instantaneous response, store anything and everything forever, ...
– Classes: young to old, able and disabled, rich and poor, literate and illiterate, …
– Numbers: individual cliques acquaintances social networks cultures populations
Cyber-Physical Systems will be everywhere, used by everyone, for everything
Technical Challenge• (How) can we build systems that interface be-
tween the cyber world and the physical world? Ideally, with predictable, or at least adaptable behavior.
• Why this is hard:– We cannot easily draw the boundaries.– Boundaries are always changing.– There are limits to digitizing the continuous world by
abstractions.– Complex systems are unpredictable.
Fundamental Scientific Chal-lenges
• Co-existence of Booleans and Re-als– Discrete systems in a continuous
world• Reasoning about uncertainty
– Human, Nature, …
• Understanding complex systems– Emergent behavior, tipping points, …– Chaos theory, randomness, ...
Needs• Services in heterogeneous environ-
ment– Adoption of open standards– Use of web services
• Real-time & Reactive– Not only in embedded systems, but also
in servers
Reactive real-time system• Reactive
– Consisting of many tasks which are exe-cuted in reaction to some external events, or to some other tasks
• Real-time– Tasks must implement the correct func-
tionality, and be executed in a timely manner
Example of reactive real-time sys-tems
• Signal processing– Digital signal processing application for
multimedia (dataflow system)
Conversion from CD audio to DAT audioCD 44.1KHz 88.2KHz 117.6KHzDAT 48KHz
Application of control to computing systems
• Web-based applications– Web Application Server or HTTP server
provides services upon requests from network
– Users expect real-time response from server
Conventional approach• Generation of static schedule
– Problem• High complexity – longer design time• Longer response time• Hard to use in general-purpose computers
• Use of periodic task model– Problem
• Low utilization due to polling• Complexity in programming due to resource
scheduling
Feedback control system• Applying control theory to scheduling
e.g. PID control
Feedback Controlled EDF
Problem: Only applicable to control relative delay
Control of dynamic system
• Implementation: Apache server on Linux (AMD-based PC), HTTP 1.1
From “Schedulability Analysis and Utilization Bounds for Highly Scalable Real-Time Services” by T.F. Abdelzaher and C. Lu,presented at RTAS 2001
Utilization bound for non-periodic tasks:
Application of computing to control
• Networked Control System (NCS)– Feedback control
system wherein the control loops are closed through RTN
– Aviation system, automotive system, surveillance sys-tem, etc
Application of computing to control- Example: Control in the Tunnel
Scenario• Control over sensor network
– Localization and navigation of mobile robot over sensor network
• Control of sensor network resources– feedback-based adjustment of radio transmit
power in sensor network nodes• Self-organizing middleware
– Mobile robot acting as a mobile radio gateway
Physical network reconfigura-tion
• Partition of network due to failure of sensor nodes
Unreachable nodes
Physical network reconfigura-tion
• Use mobile agents to restore the communication
Future Outlook • Extend constituency and application scope • Multidisciplinary integration!• Possible themes:
– Computing• Parallelisation & programmability, methodologies and tools,
system analysis– System Design
• Theory and methods, components and tools for platform-based design
– Engineering of Complex, Distributed Systems• Scalability, control, plug & play architectures, large-scale
deployment,…