1. 1 Adaptive Environments: Essential for Scalable, Survivable, and Secure Multi-Agent Systems March 21, 2007 Dr. John Zinky jzinky@bbn.com Workshop on Large Scale Multi-Agent Architectures

2. 2 1.Target Applications 2.Cougaar Agent Middleware 3.Adaptive Environments 4.Open Research Topics Outline

3. John Zinky LaSMAA07 03/07 BBN Copyright 2007 3 Extreme Applications Realtime distributed P2P applications with severe resource constraints and with Scalability, Survivability, Security (S3) requirements Examples of Extreme Applications Information Assurance Surveillance on UAV mobile sensor platforms Proactive content distribution Global network management and optimization Mission Management Management Plane Management Plane Data Processing Plane

4. John Zinky LaSMAA07 03/07 BBN Copyright 2007 4 Properties of Extreme Applications Application Functional Requirements (addressed at programming/development phase) 1.Communication: client/server vs. P2P 2.Development cycle: waterfall vs. adaptive 3.Process during operational lifespan: fixed vs. evolving 4.Human participation level: none vs. sensor vs. model vs. cognitive 5.Cross-cyber resource load CPU vs. network vs. storage vs. all System Resource Constraints (exhibited during runtime) 1.Distributedness of cyber resources: centralized vs. LAN vs. WAN 2.Data plane speed: batch vs. online vs. realtime (superhuman) 3.Survivability (reliability & performance): non-crucial vs. exigent 4.Security adversary level: trust all vs. compartmentalized trust vs. malicious vs. insider threat 5.Scalability (hosts): 10s vs. 100s vs. 1000s vs. >10,000 Business Environment (Organizational constraints) 1.Market share: large vs. medium vs. small 2.Integration environment: standalone vs. stovepipe vs. new functionality w/ legacy system integration Business System Application

5. John Zinky LaSMAA07 03/07 BBN Copyright 2007 5 Abstract Architecture for Extreme Applications Sensor-Based Control Loop Model-Based Control Loop Cognitive Control Loop Model updatespolicysituation inference rules days to hourssecs to msecs network Disk hours to minutes management planedata plane Sensor Proxy Agents Sensor Proxy Agents Real-time Optimizer Agents Real-time Optimizer Agents processing status coordination resource status coordination resource trends coordination Cognitive Learner Agents Cognitive Learner Agents processing. trends coordination Situation Predictor Agents Situation Predictor Agents processing pattern coordination resource pattern coordination Sensor Proxy Agents Sensor Proxy Agents Processing Units Processing Units Processing Units CPU Environment Application

6. 6 1.Target Applications 2.Cougaar Agent Middleware 3.Adaptive Environments 4.Open Research Topics Outline

7. John Zinky LaSMAA07 03/07 BBN Copyright 2007 7 Cougaar Agent Reference Model component servic e BB Behavior effector coordinator sensor component service component library Agent BB Behavior effector coordinator sensor component service library Agent Abstracted Environment Local Behavior (plugin) State (BB) Pub/Sub Black Board (BB) API Environment Distributed Services Components Imported libraries Service oriented API Agent/Env. API sensor effector coordinator active API Agents Application domain specific System specific Infrastructure Cyber Resource Physical Elastic Boundary

8. John Zinky LaSMAA07 03/07 BBN Copyright 2007 8 Separation of Application from Environment Agents handle Application Behavior Environment handles Systemic Adaptation Agents and Environment can be independently developed, tested, and configured, but run together Host IP Node Process MTS Agent Coordination BB Behavior BB Behavior Network

9. John Zinky LaSMAA07 03/07 BBN Copyright 2007 9 Integration with Legacy Systems … Application n embedded devices scheduling scientific comp. web Services … Application k Application j ftp, telnet, ssh embedded control … … CPU disk wire/fiber/ radio wire/fiber/ radio CPU disk wire/fiber/ radio wire/fiber/ radio CPU disk wire/fiber/ radio wire/fiber/ radio C o u g a a r runtime MPI Library JESS processes/threads Corba/RMI web services enterprise service bus enterprise service bus TCP/UDP network stack TCP/UDP network stack C o u g a a r runtime SQL DB services OWL knowledge base OWL knowledge base files C o u g a a r runtime semantic tagging banking/airlines word processing Application m grid-based systemsmessage-based systemsDB-based systems Main Cougaar architectural feature: imported libraries and component wrappers

10. John Zinky LaSMAA07 03/07 BBN Copyright 2007 10 Application 1.Functional modules (oval shaped) 2.Underlying distributed environment 3.Sensor to control loop coordination 4.Evolving degree of human involvement Cougaar 1.Agent societies 2.Cougaar environment 3.Agent coordinations 4.Transitioning of control loops human to automation architectural mapping Sensor-Based Control Loop Model-Based Control Loop Cognitive Control Loop Modelpolicysituation inference rules days to minutessecs to msecs network Disk minutes to sec management planedata plane Sensor Proxy Agents Sensor Proxy Agents Real-time Optimizer Agents Real-time Optimizer Agents processing status coordination resource status coordination resource trends coordination Cognitive Learner Agents Cognitive Learner Agents processing. trends coordination Situation Predictor Agents Situation Predictor Agents processing pattern coordination resource pattern coordination Sensor Proxy Agents Sensor Proxy Agents Processing Units CPU Architectural Mapping

11. 11 1.Target Applications 2.Cougaar Agent Middleware 3.Adaptive Environments 4.Open Research Topics Outline

12. John Zinky LaSMAA07 03/07 BBN Copyright 2007 12 Adaptation Adaptation picks the best implementation which meets the application QoS requirements within the resource constraints To make this tradeoff: adaptive systems must have: –Multiple implementations –Characterization of each implementation based requirement and constraint conditions –A mechanism for detecting the system’s conditions –A policy for choosing which implementation given the conditions. –A mechanism for enabling the implementation Algorithm Implementation Application Loads Resource Capacities Utilization/Cost Quality of Service

13. John Zinky LaSMAA07 03/07 BBN Copyright 2007 13 Impl Static Design vs. Adaptation Static Design strives for a simple, elegant, efficient solution to a single situation. Outside of that situation the design is useless Adaptation strives to just survive in a constantly changing situation. Adaptation is continuously making design decisions Requirements Design Implement Test Water Fall Design Process Adaptive Control Loop Implementation Loads Capacity Cost QoS Adaptive Control Policy Conditions

14. John Zinky LaSMAA07 03/07 BBN Copyright 2007 14 Example Adaptive Environment Services 1.Support for Adaptive Life Cycle allows multiple hooks adding adaptive code 2.Coordination Service allows agents to interact via the environment 3.Knowledge Representation (KR) manages inference and change notification of agent’s internal state 4.Programming Model enables developers to decompose application and systems issues Cougaar examples of how to make adaptive environment services.

15. John Zinky LaSMAA07 03/07 BBN Copyright 2007 15 Supporting Adaptation in the System Life Cycle Development Phase AgentEnvironment ProgramData Driven Blackboard Knowledge Rep Event Driven SOA ConfigurePluginsComponents Binders/Aspects DeploySociety Configuration Rules Environment Configuration Rules RunAgent Services Coordination Metric Service Management Society IDE Application Plugins Deploy Rules Spec Tool Run Server Cougaar Middleware Society Monitor

16. John Zinky LaSMAA07 03/07 BBN Copyright 2007 16 Component Aspect Object QoS State QoS Services Work-flow between stations Component Aspect Object QoS State QoS Services Aspect Delegates Aspects Cross-Cutting Functionality

17. John Zinky LaSMAA07 03/07 BBN Copyright 2007 17 Example: Status Dissemination Overlay Network Probe Agents –Collects real time data Client Proxy Agents –Access control, security enforcement, flow-control Dissemination Agents (forms a mesh) –Floods Status Records toward subscribers Baseline Agents –Holds default ontology and system configuration Management Agents –Mesh topology creation –Society monitoring and control –Agent restart and move DD D D DD D D P P C C P P B B C v12.2 Coordinations Task/Allocation Relays

18. John Zinky LaSMAA07 03/07 BBN Copyright 2007 18 Agent Future: Support for Coordination Artifacts Coordination Artifact (CA) Agent Defines roles Agent Coordination Artifacts: CAs –Are first-class entities in MAS –Define explicit roles for role-players –Offer shared state between the role-player & the CA –Coordinate behavior among role-players –Have distributed implementation Role-players Shared state

19. John Zinky LaSMAA07 03/07 BBN Copyright 2007 19 QoS-Adaptive Translation Changes the Translation Mechanics to Match the Situation Host Process Object Method Class Method capacity Latency= Load / Capacity Load Object Latency QoS-Adaptive Translation Deltas Change Reconstruction Translation should take into account –Structure of starting and ending data structures –Probability and frequency that structures will change –The constraints of the transfer path Change Detection Transfer Constraints

20. John Zinky LaSMAA07 03/07 BBN Copyright 2007 20 FrameSet Knowledge Representation Host Process Object Class Java Objects are code generated –Frames and relationships defined using XML –Support multiple Java interfaces Cougaar Blackboard, JESS Shadow Facts, Java Beans Web Server Slot inference (Real-time) –Type (is-a) –Containment (has-a) –Visitor Pattern (composed-of) –Aggregation (summary-of) Relationships are also Frames –Benefits from Frame inheritance Meta-data tags –Defined at compile-time Slots, frames, framesets –Example Slot meta-data Type, default-value, units, path, doc, member, warn, immutable, notify-blackboard, notify-listeners, transient Thing Equip Appl Frame name value Relationship parent-name value child-name value Containment inheritance Type inheritance

21. John Zinky LaSMAA07 03/07 BBN Copyright 2007 21 Future: OWL-RDF Graph Support on BB Nodes are defined by URIs Links are defined by OWL Statements. –(Subject, Predicate Object) OWL statements are merged from multiples sources –Redundant probes –Different time horizons –Status Calculus/policies define the merge procedure. Modifying an OWL Statement can: –Add an object instance –Change an attribute’s value –Assert general relationships between entities Queries return a “subgraph”, i.e. linked set of OWL statements OWL Statement (“WI”, “IsA”,”State”) OWL Statement (“WI”, “IsA”,”State”) OWL Statement (“http://bbn.com/CommGear/STU-III-Phone#703-555-1212”, “serialNumber”, ” 43123154562”) OWL Statement (“http://bbn.com/CommGear/STU-III-Phone#703-555-1212”, “serialNumber”, ” 43123154562”)

22. John Zinky LaSMAA07 03/07 BBN Copyright 2007 22 Characteristics of Programming Models Programming Model Ops per Second IsolationThreadCallCrosscutCougaar usage Method ~10 7 noneCallerSyncAOPLibraries Service ~10 6 Bind to service CallerSyncBinder Aspects Core Services Event Listener ~10 5 Bind to publisher PublisherSyncMultiple Listeners FrameSet Enterprise Service Bus ~10 ? Bind to TopicIndependentAsyncMultiple Listeners Message transport Service Cougaar Blackboard ~10 4 Independent AsyncMultiple subscriptions LDM FrameSet OWL Inference Engine ~10 4 IndependentSingleAsyncMultiple rules FrameSet OWL The programming model for interaction between components, should allow a range of flexibility vs efficiency tradeoffs

23. John Zinky LaSMAA07 03/07 BBN Copyright 2007 23 Future: Multiple Knowledge Processing Frameworks Partitioned Blackboard LHS Patterns Real-Time Knowledge Feeds RHS Trigger Assert Retract Domain Processing Domain Routines Domain Objects Code Libraries Agent Domain Processing Facts from multiple Partitions Coordination with External Systems Coordination with Physical Environment Coordination with Peer Agents Blackboard Partitions managed by Coordination Artifacts Agents Concentrate on domain processing Procedural codeRule code

24. 24 1.Target Applications 2.Cougaar Agent Middleware 3.Adaptive Environments 4.Open Research Topics Outline

25. John Zinky LaSMAA07 03/07 BBN Copyright 2007 25 Open Systems Research Problems Adaptive Knowledge Sharing –How to automatically and efficiently translate knowledge betweens heterogeneous agents? –How can we merge domain ontologies and system constraints ontologies? Coordination –How do we make coordination first class? –How to formally specify coordination, in order to reason about at runtime? High-level agent Programming Abstraction –How to give agents richer and domain-customized programming support? Societies Composition –How to merge multiple societies to perform a higher level task? –How to partition societies into federations to reduce complexity? Reuse –How to define and create libraries of reusable coordinations? –What common set of services to standardize in order to simplify agent implementation? –Which reusable generic set of agents to offer for specific services?

26. John Zinky LaSMAA07 03/07 BBN Copyright 2007 26 Open Source Cougaar Release 12.2 in March 12, 2007 ~2000 downloads 12.0 release 30 downloads rel 12.2 (1 week) 46 active hosted projects (~10 BBN) ~1400 active users www.cougaar.org