1. Adaptive & Reflective Middleware for Large-scale Distributed Real-time & Embedded Systems Dr. Douglas C. Schmidt dschmidt@uci.edu www.ece.uci.edu/~schmidt/

2. 2 Accomplishments & New Directions Productivity & quality gains from higher-level abstraction mechanisms Partially automated solutions for limited domains Analysis Generation Characteristics of DRE Systems Mission-critical control Resource constrained Stringent simultaneous QoS demands Network-centric & large-scale Dynamic operating conditions Characteristics of DRE Systems Mission-critical control Resource constrained Stringent simultaneous QoS demands Network-centric & large-scale Dynamic operating conditions Distributed real-time & embedded (DRE) systems are increasingly pervasive & essential

3. 3 Current Challenges & Limitations Distributed Active Control: Vibration Damping on Delta-4 Rocket Payload Fairing (1,000 nodes) Gossamer Space Antenna (1,000,000 nodes) Noiseless sonar on submarines to provide camouflage (3,000 nodes) Distributed Network of embedded sensor motes for environment monitoring, tracking, & surveillance (10,000 nodes) Emerging Trends Large-scale DRE system requirements are increasingly more Dynamic Diverse Demanding 1000 – 1,000,000 node fusion of physical & information systems

4. 4 Applications Endsystem Networks Operating System Applications Endsystem Operating System Applications Endsystem Operating System Networks Technology Problems Today’s DRE systems are: Stovepiped Proprietary Brittle & non-adaptive Expensive Vulnerable SensorsActuatorsControllers Utility Resources Utility “Curve” “Broken” “Works” Cultural Problems Existing research approaches do not scale to address key technology problems Non-appreciation of the importance of DRE software Emerging Trends Large-scale DRE system requirements are increasingly more Dynamic Diverse Demanding Current Challenges & Limitations

5. 5 CPUs & networks have increased by 3-7 orders of magnitude in the past decade 2,400 bits/sec to 1 Gigabits/sec 10 Megahertz to 1 Gigahertz These advances stem largely from standardizing hardware & software APIs and protocols, e.g.: Lessons from IT History TCP/IP, ATM POSIX & JVMs Middleware & components Intel x86 & Power PC chipsets Quality of service aspects Extrapolating this trend to 2010 yields ~100 Gigahertz desktops ~100 Gigabits/sec LANs ~100 Megabits/sec wireless ~10 Terabits/sec Internet backbone DRE software has not improved as rapidly or as effectively as hardware & networks

6. 6 Applications Endsystem Networks Operating System Sensors Applications Endsystem Operating System Applications Endsystem Operating System Actuators Networks Controllers The Road Ahead for DRE Systems We need to create the new generation of open DRE system middleware technologies to 1.Simultaneously control multiple QoS properties & 2.Improve software development quality, productivity, & assurability Common Services Distribution Middleware Infrastructure Middleware Domain-Specific Services Applications Endsystem Networks Operating System Sensors Applications Endsystem Operating System Applications Endsystem Operating System Actuators Networks Controllers Common Services Distribution Middleware Infrastructure Middleware Domain-Specific Services Common Services Distribution Middleware Infrastructure Middleware Domain-Specific Services Win2KLinuxLynxOS Solaris VxWorks Middleware Services Middleware Applications MIDDLEWARE ARCH RTP DNS HTTP UDPTCP IP TELNET EthernetATMFDDI Fibre Channel FTP INTERNETWORKING ARCH TFTP 21 st Century 20 th Century Benefits of Middleware Highly scalable QoS Enable new resource management capabilities Support common & open technology bases Leverage & enhance advances in assurance & security Benefits of Middleware Highly scalable QoS Enable new resource management capabilities Support common & open technology bases Leverage & enhance advances in assurance & security Resources Utility Desired Utility Curve “Working Range”

7. 7 Technical Challenge: Real-time Control of Distributed Resources Ship-wide QoS Doctrine & Readiness Display Distributed resource management Allocation/reservations, caching, scheduling, monitoring, & load balancing Distributed security Distributed fault tolerance Network latency & bandwidth Workload & Replicas CPU & memory Connections & priority bands Network latency & bandwidth Workload & Replicas CPU & memory Connections & priority bands Control Vars. } Local middleware QoS TBMD Application AAW Application Control Algorithm Control Algorithm Control Algorithm Control Algorithm Control Algorithm Control Algorithm Requested QoS Measured QoS Global Middleware Network latency & bandwidth Workload & Replicas CPU & memory Connections & priority bands Goal: Create new generation of middleware to simultaneously control multiple QoS properties Hardware Middleware OS & Protocols Applications

8. 8 Solution Approach Doctrine-driven middleware to support multi-level management of DRE resources i.e., dynamic, dependable, & scalable resource analysis, scheduling, allocation, monitoring & balancing Guided by online reflective QoS models & empirical evaluation Solution Approach Doctrine-driven middleware to support multi-level management of DRE resources i.e., dynamic, dependable, & scalable resource analysis, scheduling, allocation, monitoring & balancing Guided by online reflective QoS models & empirical evaluation Research Challenge Devise middleware to formally specify QoS- constrained global resource management plans; model, reason about and refine them; & monitor/enforce these plans automatically at run- time Problem Multiple technology bases make it hard to analyze & control the QoS of distributed resources at multiple system levels dynamically, dependably, & securely IntServ + Diffserv RTOS + RT Java RT/DP CORBA + DRTSJ Load Balancer FT CORBA Measured QoS QoS TBMD Application AAW Application Control Algorithm Control Algorithm Control Algorithm Control Algorithm Control Algorithm Control Algorithm Requested QoS Network latency & bandwidth Workload & Replicas CPU & memory Connections & priority bands QoS Hard Problem 1: Secure Multi-level Distributed Resource Management

9. 9 Data Parallel CORBA bridges the gap between traditional CORBA applications & high-performance embedded parallel processing applications as follows: Enable CORBA applications over clusters of computers No change required in software technologies, methodologies, or tools Enable massively parallel applications to integrate easily with distributed systems Allow parallel applications to benefit from distributed object methodologies, technologies, & tools Add parallelism & data distribution to the transparencies offered by CORBA Enable a new class of applications e.g., financial, industrial, medical, aerospace, multimedia, and military domains Client on parallel ORB Parallel ObjectComputing Grid Part 1 Part 2 Part 3 Airborne HPEC Distributed shipboard clusters CONUS supercomputers … Data reorganization strategies Example: Data Parallel CORBA

10. 10 Hard Problem 2: Meta-programmable DRE Middleware Frameworks Endsystem Applications MiddlewareMiddleware Applications Mechanism & Property Managers Sys Cond Interceptor Local Resource Managers Sys Cond { } QoS Contract Network latency & bandwidth Workload & Replicas CPU & memory Connections & priority bands Network latency & bandwidth Workload & Replicas CPU & memory Connections & priority bands Local Resource Managers Problem Existing DRE systems are rigidly designed with fixed QoS parameters that limit their utility for new operations Research Challenges Assuring dynamic flexibility and QoS simultaneously Solution Approach Meta-programming techniques that Decouple functional & QoS paths to allow more degrees of freedom Specify QoS doctrine declaratively Support dynamic QoS adaptation & optimizations Solution Approach Meta-programming techniques that Decouple functional & QoS paths to allow more degrees of freedom Specify QoS doctrine declaratively Support dynamic QoS adaptation & optimizations

11. 11 Example: Meta-programmed Distributed QoS Aspects Mission Requirements Fidelity Highest fidelity frames must be delivered Timeliness Maintain an out-of-the-window view of imagery Importance Frames must be dropped in reverse order of importance... P BB P BB P BB II I I DATA FILTERING Condition: Excessive Network or CPU load Action: Drop selective frames IMAGE MANIPULATION Condition: Excessive Network load Action: Scale image to smaller size LOAD BALANCING Condition: Excessive CPU load Action: Migrate distributor to a lightly loaded host X X I P B I I I I I I I I P P P P P P P P P P B B B B B B B BB B B B B B B B BB B B B B B B B B B B B B B B B B B B B B B BBBBBBBBBBBBBB B BBB BBBBBBBBBBBBBBBBBBBBBBBBBBBB P P P P P P P P P P I BB P BB P BB P BB P BB P BB I BB P B NETWORK RESERVATION Condition: Excessive Network load Action: Use IntServ & DiffServ to reserve bandwidth QoS Contracts www.dist-systems.bbn.com/tech www.cs.wustl.edu/~schmidt

12. 12 Hard Problem 3: DRE Middleware Generation & Optimization Tools Research Challenge Minimizing footprint & customizing standard DRE middleware capabilities without sacrificing key QoS properties t START t2t2 t4t4 t5t5 t6t6 t7t7 t9t9 t 10 t 12 t 13 t 14 t 15 t 16 t 17 t 18 t 11 t 19 t REQ’D t3t3 t8t8 Impl 1 Application Requirements Impl 2 Impl 1 Common Semantic Rep. Plat 2 Plat 2.pd Plat 3 Plat 3.pd Plat 1 Plat 1.pd Middleware Generator DRE Applications Optimized & verified DRE middleware Common Middleware Tools Problems COTS middleware is often unsuited for DRE systems due to insufficient QoS specification & enforcement Time/space optimizations Flexibility & customizability However, conventional DRE development techniques are Tedious Proprietary Manual & ad hoc Solution Approach Develop Model Driven Architecture (MDA) tools to reflectively auto-generate, optimize, & verify custom implementations of standard DRE middleware from higher- level specifications Solution Approach Develop Model Driven Architecture (MDA) tools to reflectively auto-generate, optimize, & verify custom implementations of standard DRE middleware from higher- level specifications Network latency & bandwidth Workload & Replicas CPU & memory Connections & priority bands Network latency & bandwidth Workload & Replicas CPU & memory Connections & priority bands

13. 13 Early compilers required Separate internal representations hand-written for each programming language & Separate hand-written optimizers for each target backend Developing, verifying, validating, & evolving all these components separately is costly, time-consuming, tedious, & error-prone The problem only gets worse as more languages & target backends emerge C Compiler Internal Rep. Ix86 Opt. Ix86 VAX Opt. VAX 68K Opt. 68K C Program To illustrate the benefits of reflection as an optimization technique, consider the evolution of compiler technology: Example: Applying Reflection as Compiler Optimization

14. 14 Early compilers required Separate internal representations hand-written for each programming language and Separate hand-written optimizers for each target backend Developing, verifying, validating, & evolving all these components separately is costly, time-consuming, tedious, & error-prone The problem only gets worse as more languages & target backends emerge C Compiler Internal Rep. Ix86 Opt. Ix86 VAX Opt. VAX 68K Opt. 68K C Program To illustrate the benefits of reflection as an optimization technique, consider the evolution of compiler technology: C++ Compiler Internal Rep. PPC Opt. MIPS Opt. 88K Opt. PPCMIPS88K C++ Program Ada Compiler Internal Rep. 1751 Opt. 32K Opt. HPPA Opt. 175132KHPPA Ada Program Example: Applying Reflection as Compiler Optimization

15. 15 C/C++/Ada Compiler Common Internal Rep. Ix86 Opt. PPC Opt. 68K Opt. C/C++/Ada Programs Ix86.md PPC.md 68K.md Modern compilers, such as GNU GCC, support A common internal representation (still hand-written) for each programming language Based on generalizing the language semantics 1. Read the target machine description Optimizer Generator 2. Use discrimination network to analyze the optimization rules & opportunities 3. Generate an optimizer that is customized for the particular platform/language A synthesized compiler optimizer that is customized automatically for each target backend Based on reflective assessment of algebraic target machine description Key Benefit of Reflective Optimization New targets can be supported by writing a new machine description, rather than writing a new code generator/optimizer Example: Applying Reflection as Compiler Optimization

16. 16 Developing, verifying, validating, & evolving all these components separately is costly, time- consuming, tedious, & error-prone Moreover, it is even harder to hand-configure support for dynamic platform variations & complex application use-cases The problem only gets worse as more middleware, target platforms, & complex applications emerge Separate hand-written & hand-optimized implementations for each embedded target platform e.g., various OS/network/HW configurations Conventional middleware require Separate tools and interfaces hand-written for each ORB middleware specification e.g., CORBA, Java RMI, COM+ CORBA ORB & Assorted Tools CORBA Application Conventional middleware for embedded systems is developed & optimized in a manner similar to early compiler technologies: WinNT Impl LynxOS Impl VxWorks Impl New Approach : Applying Reflection to Optimize DRE Middleware

17. 17 Developing, verifying, validating, & evolving all these components separately is costly, time- consuming, tedious, & error-prone Moreover, it is even harder to hand-configure support for dynamic platform variations & complex application use-cases The problem only gets worse as more middleware, target platforms, & complex applications emerge Separate hand-written & hand-optimized implementations for each embedded target platform e.g., various OS/network/HW configurations Conventional middleware require Separate tools and interfaces hand-written for each ORB middleware specification e.g., CORBA, Java RMI, COM+ Java RMI & Assorted Tools Win2KSolaris Linux Java Application Win2K Impl Solaris Impl Linux Impl COM+ ORB & Assorted Tools WinNTWin98 WinCE COM+ Application WinNT Impl Win98 Impl WinCE Impl CORBA ORB & Assorted Tools CORBA Application Conventional middleware for embedded systems is developed & optimized in a manner similar to early compiler technologies: WinNT Impl LynxOS Impl VxWorks Impl New Approach : Applying Reflection to Optimize DRE Middleware

18. 18 Common ORB + Assorted Tools Common Semantic Representation Plat 1 Impl The functional and QoS-related properties of embedded systems middleware can be improved greatly by advanced R&D on the following topics: A common internal representation (ideally auto- generated) for each middleware specification Based on generalizing the middleware semantics Middleware Generator 2. Use discrimination network to analyze the optimization rules & opportunities 3. Generate middleware that is customized for a particular platform & application use-case A synthesized middleware implementation that is optimized automatically for each target platform & application use-case Based on reflective assessment of platform descriptions & application use-case Plat 2.pd Plat 2 Impl Plat 3 Impl 1. Read the target platform description & application requirements Application Requirements CORBA/Java/COM+ Applications Plat 3.pd Plat 1.pd New Approach : Applying Reflection to Optimize DRE Middleware

19. 19 DARPA DRE Software R&D Focus Comparable & Customizable Frameworks & Intelligent Middleware Patterns & Pattern Languages Model-based Software Development & Domain-specific Languages GPSIFFFLIR Object Request Broker Air Frame APNavWTS Event Channel Replication Service Synchronization Persistence Fault Tolerance Memory Management Cross-cutting Concerns Multi-faceted Software Development Collaborative Software Development Environments Applications to Embedded Systems