Real-Time Platforms. Ø Real-Time OS: Linux Ø Real-Time Middleware: TAO

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1 Real-Time Platforms Ø Real-Time OS: Linux Ø Real-Time Middleware: TAO q Event service q Single-processor scheduling q End-to-end scheduling q Aperiodic scheduling Ø Real-Time Virtualization: RT-Xen Ø Real-Time Cloud: RT-OpenStack Ø Real-Time Parallel Computing: RT-OpenMP 1

2 Problems with Current Approaches We increasingly rely on distributed real-,me & embedded (DRE) systems Applications Sensors Applications Controllers Applications Actuators Characteris,cs of DRE Systems Network- centric Stringent quality of service (QoS) demands Resource constrained Mission- cri,cal control Technical limita,ons with today s DRE infrastructure Stovepiped Proprietary Bri>le & non- adap,ve Expensive Vulnerable Operating System Endsystem Networks Operating System Endsystem Networks Operating System Endsystem Utility Utility Curve Broken Works Resources 2

3 Middleware: A More Effective Approach Develop & apply the new generation of distributed object computing (DOC) middleware technologies to 1.simultaneously control multiple QoS properties & 2.improve software development quality, productivity, adaptability, & assurability Applications Sensors Domain-Specific Services Common Services Applications Controllers Domain-Specific Services Common Services INTERNETWORKING ARCH RTP DNS TFTP UDP IP FTP TELNET TCP Fibre Channel HTTP Ethernet ATM FDDI 20 th Century Applications Actuators Domain-Specific Services Common Services MIDDLEWARE ARCH Solaris Middleware Applications Middleware Services Middleware VxWorks Win2K Linux LynxOS 21 st Century Benefits of Middleware Highly scalable QoS Enable new resource management capabilities Support common & open technology bases Leverage & enhance advances in assurance & security Distribution Middleware Infrastructure Middleware Operating System Endsystem Networks Distribution Middleware Infrastructure Middleware Operating System Endsystem Networks Distribution Middleware Infrastructure Middleware Operating System Endsystem Utility Desired Utility Curve Resources Working Range

4 Why Are We Succeeding The past decade has yielded significant progress in QoS- enabled middleware, stemming in large part from the following trends: Years of iteration, The maturation The maturation of refinement, & successful of middleware component middleware use standards frameworks & patterns Component Models (EJB) Real-time CORBA Real-time CCM Web Services CORBA Component Model (CCM) RPC CORBA & DCOM DCE Micro-kernels ARPAnet 1970 Year 2005 Applications Domain-Specific Services Common Services Distribution Middleware Host Infrastructure Middleware Operating Systems & Protocols Hardware NET, J2EE, CCM Real-time CORBA Real-time Java SOAP & Web Services 4

5 Application Example: Avionics Goals Apply COTS & open systems to mission- cri>cal real- >me avionics Key System Characteris,cs Determinis>c & sta>s>cal deadlines ~20 Hz Low latency & jiger ~250 us Periodic & aperiodic processing Complex dependencies Con>nuous plamorm upgrades Key Results Test flown at China Lake NAWS by Boeing OSAT II '98, funded by OS- JTF boeing.html Also used on SOFIA project by Raytheon sofia.arc.nasa.gov First use of Real- >me CORBA in avionics 5 Drove Real- >me CORBA standardiza>on

6 Application Example: Hot Rolling Mills Key SoPware Solu,on Characteris,cs Affordable, flexible, & COTS Product- line architecture Design guided by pagerns & frameworks Goals Control the processing of molten steel moving through a hot rolling mill in real- >me System Characteris,cs Hard real- >me process automa>on requirements i.e., 250 ms real- >me cycles System acquires values represen>ng plant s current state, tracks material flow, calculates new seangs for the rolls & devices, & submits new seangs back to plant Windows NT/2000 Real- >me CORBA 6

7 Application Example: Image Processing Goals Examine glass bogles for defects in real- >me System Characteris,cs Process 20 bogles/sec ~50 ms per bogle Networked configura>on ~10 cameras Key SoPware Solu,on Characteris,cs Affordable, flexible, & COTS Embedded Linux (Lem) Compact PCI bus + Celeron processors Remote booted by DHCP/TFTP Real- >me CORBA 7

8 CORBA Common Object Request Broker Architecture Ø CORBA specifications q OMG is the standards body q Over 800 companies q CORBA defines interfaces, not implementations Ø Object Request Brokers (ORB) allow clients to invoke operations on distributed objects transparently of q Object location q Programming language q Operating system q Communication protocols and interconnect q Hardware 8

9 CORBA Reference Model Ø Client invokes operations on objects. Ø An Object = q An interface specified by an Interface Definition Language (IDL) q Servant(s) that implements the IDL interface 9

10 Stubs and Skeletons Ø Translate between platform-dependent data formats and common data representation. Ø Generated by an IDL compiler based on the IDL interface. Ø Ensure platform/language transparency. 10

11 ORB Core Ø Deliver requests to objects and responses to clients Ø Communicate using a General Inter-ORB Protocol (GIOP) q e.g., Internet Inter-ORB Protocol (IIOP) on TCP Ø Typically a run-time library linked to applications 11

12 Object Adapter Ø Demultiplexes each incoming request to the right servant/operation Ø Make the upcall to the operation 12

13 Limitations of CORBA Ø Lacks QoS specification interfaces to applications q Applications cannot specify rate, deadline or importance Ø Lacks QoS enforcement q Does not map task QoS specification to priorities of threads q Contains significant priority inversion Ø Lacks performance optimization q Poor worst-case and average latency 13

14 Latencies and Priority Inversions 14

15 The ACE ORB (TAO) Open-source Real-Time CORBA >> 1M SLOC 100+ person years of effort Pioneered R&D on DRE middleware design & optimization Source: D.C. Schmidt, 15

16 TAO Overview DII Client IDL STUBS OBJ REF in args operation() out args + return ORB INTERFACE Component (Servant) IDL SKEL Container Object Adapter Services Based on ACE wrapper facades & frameworks Available on Unix, Win32, MVS, QNX, VxWorks, LynxOS, VMS, etc. Thousands of users around the world ORB CORE GIOP/IIOP/ESIOPS Objective Ø Simplify the development of distributed real-time & embedded (DRE) systems Approach Ø Use standard techology, patterns, & frameworks Commercially supported by many companies OCI ( PrismTech ( more coming soon support.html 16

17 I/O Subsystem: Priority Inversions Ø Messages are processed in FIFO order regardless of priorities Ø Kernel has lower priority than real-time priorities q Processing of a high priority message in the kernel can be blocked by a lower priority task at the application level 17

18 I/O Subsystem: Solutions Ø Early demultiplexing Ø Prioritized kernel processing Ø Map task priority to kernel thread Ø Note: This needs kernel support 18

19 ORB Core: Priority Inversions Ø Communication of different tasks shares a same socket connection. Ø Incoming requests are demultiplexed to threads in FIFO order. 19

20 ORB Core Priority-based Concurrency Architecture Ø Server sets model: Each priority is processed by a separate thread. Ø A separate connection is maintained for each priority in the server ORB. q Use buffered connections to reduce run-time overhead. Ø Suitable for fixed priority scheduling. 20

21 Object Adapter: Problems Ø Layered demultiplexing is inefficient in term of q average latency q worst-case latency 21

22 Object Adapter: Solutions Ø Perfect hashing q Generate a hash function offline q Computational complexity O(1) Ø De-layered active demultiplexing q Clients obtain index to (servant, operation) ahead of time 22

23 Reduce Priority Inversion Conventional ORB TAO 23

24 The Evolution of TAO DYNAMIC/STATIC SCHEDULING A/V STREAMING Real-time CORBA 1.0 Sta,c Scheduling (1.0) Rate monotonic analysis Dynamic Scheduling (1.2) Earliest deadline first Minimum laxity first Maximal urgency first Hybrid Dynamic/Sta,c Demo in WSOA Kokyu integrated. A/V Streaming Service QoS mapping QoS monitoring QoS adapta>on ACE QoS API (AQoSA) GQoS/RAPI & DiffServ IntServ integrated with A/V Streaming & QuO DiffServ integrated with ORB 24

25 The Evolution of TAO DYNAMIC/STATIC SCHEDULING A/V STREAMING FT-CORBA & LOAD BALANCING SECURITY Real-time CORBA 1.0 FT- CORBA (DOORS) En>ty redundancy Mul>ple models Cold passive Warm passive IOGR HA/FT integrated. Load Balancing Sta>c & dynamic Integrated in TAO 1.3 De- centralized LB OMG LB specifica>on SSL Support Integrity Confiden>ality Authen>ca>on (limited) Security Service (CSIv2) Authen>ca>on Access control Non- repudia>on Audit 25

26 The Evolution of TAO DYNAMIC/STATIC SCHEDULING A/V STREAMING FT-CORBA & LOAD BALANCING SECURITY Real-time CORBA 1.0 NOTIFICATIONS TRANSACTIONS No,fica,on Service Structured events Event filtering QoS proper>es Priority Expiry >mes Order policy Compa>ble w/events Real-,me No,fica,on Service Object Transac,on Service Encapsulates RDBMs 26

27 Acknowledgement Slides partially borrowed from Doug Schmidt s Real-Time CORBA tutorial. 27