CoAX Technology Contributions TTCP Meeting - Malvern - September 2000 AFRL Rome, AIAI, Boeing,...

CoAX Technology ContributionsCoAX Technology ContributionsTTCP Meeting - Malvern - September 2000TTCP Meeting - Malvern - September 2000

AFRL Rome, AIAI, Boeing, Dartmouth, DERA Malvern, Lockheed AFRL Rome, AIAI, Boeing, Dartmouth, DERA Malvern, Lockheed Martin ATL, Michigan, MIT Sloan, Stanford, USC/ISI, UWF/IHMCMartin ATL, Michigan, MIT Sloan, Stanford, USC/ISI, UWF/IHMC

Support from BBN, GITI, ISX, MITRE, SchaferSupport from BBN, GITI, ISX, MITRE, Schafer

Coalition Agents eXperiment (CoAX)Coalition Agents eXperiment (CoAX)http://www.aiai.ed.ac.uk/project/coax/http://www.aiai.ed.ac.uk/project/coax/

DARPADARPA

DARPADARPA

CoAX /Tech Briefing - 3

Technical ContributionsTechnical Contributions

GITI - CoABS Grid InfrastructureGITI - CoABS Grid Infrastructure Boeing and UWF/IHMC- KAoS Domain ManagementBoeing and UWF/IHMC- KAoS Domain Management AIAI Process Panel - Task and Process ManagementAIAI Process Panel - Task and Process Management DERA Master Battle PlanningDERA Master Battle Planning LM ATL EMAA/CAST AODB - Restricted Data Base AccessLM ATL EMAA/CAST AODB - Restricted Data Base Access AFRL/BBN/GITI CAMPS - Air Logistics Support ToolAFRL/BBN/GITI CAMPS - Air Logistics Support Tool USC/ISI Ariadne - Open Information AccessUSC/ISI Ariadne - Open Information Access UWF/IHMC - NOMADS safe and secure mobile agentsUWF/IHMC - NOMADS safe and secure mobile agents Stand alone demonstrations at 9 months:Stand alone demonstrations at 9 months:

MIT Robustness ServicesMIT Robustness Services Stanford Incentives ManagementStanford Incentives Management Dartmouth Observer AgentDartmouth Observer Agent Michigan Coordination Planning AidMichigan Coordination Planning Aid


GITI/ISXGITI/ISXThe CoABS GridThe CoABS Grid

J iniLookupS ervice

D iscover ,J oin,

L ookup

Regist erCapabilit ies

Rout eS ent inel

I nf or mat ionM ediat or

A gentCommunity 2

L E I FA pplicat ion

L E I FA pplicat ion

A gentCommunity

3

D ist r ibut edO bj ect

A gentCommunity 1

Gr id S ervice H elper

Gr id I nf r ast r uct ur e S er vicesA r iadne

W ebT rader

EGents

Gr id A gent H elper

D ist r ibut edO bj ect



S endM essage

S ear ch

S ear ch



Gr id A gent H elperGr id S ervice H elper




USC/IS IARIADNE

USC/IS ITheseus

USC/IS ITEAMCORE

SRI Maestro

SRI Multi-Modal Map SRI W eather

Agent

SRI F lightAgent

OGIQuickSet

OGI AAA

CMUExPressCMU Route

P lanner CMUMessenger

CMU FlightAgent BBN/Kestrel

CAMPS

OBJSMBNLI

OBJSW ebTrader

Grid A wareS ervices

The CoABS/Infrastructure code provides a framework for integrating diverse agent-based systems, and provides additional common services.

The Grid allows agents to find services and other agents so that agent teams can be dynamically formed to solve context-based tasks.

The Grid is built using JiniTM technology. Direct agent communication is provided using message queues built on JAVA RMI. Grid Logging Markup Language based on XML.


Prototype Grid ArchitecturePrototype Grid Architecture

Java Platform: RMI, Jini™

Grid Core Services

Grid Agent Helper

Grid Service Helper ServiceRep Registry

AgentRepMessage

Queue

Logging

Visualization

Admin

Events Security

Object

RETSINAProxy Agent

OAAProxy Agent

Grid Ready Components

Grid Aware ServicesInformation

Retrieval AgentsAuction/Trader

Agentse-mail

Proxi Agents

Matchmaker MobilityEvent

Messaging

Instrument-ation

0 Interoperability of distributed, heterogeneous objects, services, and multi-agent systems.

0 Registration and advertisement of capabilities.

0 Discovery of relevant participants, and flexible run-time communications.

0 Current Grid services include: Logging, Visualization, Security, Instrumentation, Communication, Registration, and Event Services.


Boeing/UWF - Agent DomainsBoeing/UWF - Agent Domains

A

A

AAA

AA

AA

A

A

AA DM

An agent domain consists of one or more agents registered with a common Domain Manager which provides for

common administration and enforcement of domain-wide, platform-specific, and agent-specific policies.


Agent Domain Agent Domain Management in CoAXManagement in CoAX

Broadens typical distributed security concerns to include:Broadens typical distributed security concerns to include: Communication and access management: Who can Communication and access management: Who can

communicate with whom for what services?communicate with whom for what services? Registration management: Who can join the domain Registration management: Who can join the domain

under what circumstances?under what circumstances? Resource management: Who can have which kind and Resource management: Who can have which kind and

how much of a given computing resource?how much of a given computing resource? Mobility management: Who can move where under what Mobility management: Who can move where under what

circumstances?circumstances? Conversation management: What constraints govern Conversation management: What constraints govern

interaction between conversing agents? interaction between conversing agents? Obligation management: Who is not meeting Obligation management: Who is not meeting

commitments?commitments?Initial capability shown in six-month demoInitial capability slated for nine-month demoInitial capability slated for 2001-2002 demos


NativeMech

NativeMech

OtherOther

GuardGuard

Policy Management Framework

Policy Management Framework

PolicyAdminTool

PolicyAdminTool

Java VMJava VM

Guard

Aroma VMAroma VM

GuardGuard

ServletServletRMI KAoS

DomainManager

KAoSDomainManager

HTTP

Agent

Policy DirectoryPolicy Directory

Agent

Agent

Agent

AgentAgent

RMIJNDI

Guard is responsible for:1. Interpreting policy2. Enforcing with appropriate native mechanism

1. Abstract, mechanism- neutral representation/XML syntax (DAML collaboration)2. Distributed networked availability3. Secure

1. Ensures policy consistency at all levels2. Stores policy changes3. Notifies guards

Authorized user makes changes over the Web

Event-driven policy changes


KAoS Policy Admin Tool


AIAI I-X Process PanelAIAI I-X Process Panel Initially maintains an overview of the current status the Initially maintains an overview of the current status the

coalition C2 processes in accessible shared military coalition C2 processes in accessible shared military terms.terms.

Later adds the ability to monitor, plan and control the Later adds the ability to monitor, plan and control the coalition C2 processes.coalition C2 processes.

Can take on and address “issues” in the C2 process.Can take on and address “issues” in the C2 process. Links to and assists with domain management, Links to and assists with domain management,

authority, exception management and other Grid authority, exception management and other Grid management services.management services.

To be packaged as generic task and process To be packaged as generic task and process management facilities that can be made available to management facilities that can be made available to other Grid applications.other Grid applications.


AIAI I-X Process PanelAIAI I-X Process Panel


DERADERAMaster Battle PlannerMaster Battle Planner

Visual planning tool for air operations.Visual planning tool for air operations. Map-based graphical user interface - operator builds Map-based graphical user interface - operator builds

scenario and air missions using simple dialogs and “point scenario and air missions using simple dialogs and “point and click” techniques.and click” techniques.

Analyzes plans (identifying over-tasking, GANTT charts, Analyzes plans (identifying over-tasking, GANTT charts, animated flyout facility)animated flyout facility)

Obtains data on targets and assets from other agents.Obtains data on targets and assets from other agents. Integrates air missions (e.g. air transport) and weather Integrates air missions (e.g. air transport) and weather

forecasts from other agents into the air visualisation.forecasts from other agents into the air visualisation. Informs AIAI’s Process Panel of current planning status.Informs AIAI’s Process Panel of current planning status.


AFRL/GITI/BBNAFRL/GITI/BBNCAMPS Mission PlannerCAMPS Mission Planner

Develops schedules for aircraft to pick up and deliver cargo within specified time windows.

Takes into account a large number of constraints (aircraft & port capabilities, crew availability, work schedule rules)

Can be tasked by other agents.Can be tasked by other agents. Domain-aware agent obtains scheduled air Domain-aware agent obtains scheduled air

transport flights and forwards them to Master transport flights and forwards them to Master Battle Planner for integration into the air Battle Planner for integration into the air visualisation.visualisation.


AFRL/GITI/BBNAFRL/GITI/BBNCAMPS Mission PlannerCAMPS Mission Planner


USC/ISI Ariadne USC/ISI Ariadne Weather AgentWeather Agent


LM ATL EMAA/CAST LM ATL EMAA/CAST AODB Access AgentAODB Access Agent

Provides access to AODB via XML formatted Grid Provides access to AODB via XML formatted Grid messages.messages.

Supports different kinds of queries: one shot, Supports different kinds of queries: one shot, update, and persistent.update, and persistent.

Will be evolving EMAA/CAST technology to create Will be evolving EMAA/CAST technology to create a deliverable generic Grid-aware core agent a deliverable generic Grid-aware core agent engine to other end users. This technology will be engine to other end users. This technology will be configurable and is intended to easily allow configurable and is intended to easily allow access to alternative sources.access to alternative sources.


LM ATL EMAA/CAST LM ATL EMAA/CAST AODB Access AgentAODB Access Agent

DARPACoABS

Grid

Response

Machine B

Machine A

Client

Message Queue

EMAA Server

Controller Agent

Query

1

23

4

5

6

7

1. Client sends the Query via a Grid Data Message.2. Agent Engine receives the Query on it’s Message Queue.3. Agent Engine processes the Query.4. Agent Engine creates a Controller Agent.5. Controller Agent spawns other agents to retrieve data from each of the JDBC sources.6. Controller Agent generates response message and sends it via the Grid to the Client.7. Client receives response for processing.

AgentEngine


Lm ATL EMAA/CAST Lm ATL EMAA/CAST AODB Access AgentAODB Access Agent


USC/ISI Open USC/ISI Open Information AccessInformation Access

Provide real-time access to Web data sourcesProvide real-time access to Web data sources Tools for learning wrappers to extract data for Tools for learning wrappers to extract data for

semi-structured sourcessemi-structured sources Agents learn the structure of data to support:Agents learn the structure of data to support:

Source verificationSource verificationautomatically detect when the source no longer automatically detect when the source no longer

provides correct data (possibly because the provides correct data (possibly because the source has changed)source has changed)

Source reinductionSource reinductionautomatically revise wrapper when site changeautomatically revise wrapper when site change


Resource Control and Resource Control and Security in NOMADSSecurity in NOMADS

Dynamic and fine-grained resource controlDynamic and fine-grained resource control NOMADS enforces security policies specified by the NOMADS enforces security policies specified by the

KAoS domain managerKAoS domain manager Security policies include limits on CPU, disk, and Security policies include limits on CPU, disk, and

network resource usagenetwork resource usage Resource consumption monitoringResource consumption monitoring

NOMADS Guard constantly monitors the resource NOMADS Guard constantly monitors the resource consumption of the GAO agentconsumption of the GAO agent

When the guard detects a potential denial of service, When the guard detects a potential denial of service, the guard reduces the resource limits available to the the guard reduces the resource limits available to the GAO agentGAO agent


Resource Control and Resource Control and Security in NOMADSSecurity in NOMADS

Aroma VM

GAO

Java VM

DAO

Observers Domain

G

KPATDomainManager


Field Observations (Dartmouth)

• Team of soldiers

• PDA’s

• Ad-hoc wireless networking

• Soldiers make observations.

• Ground traffic

• Air traffic

• Personnel and equipment

• Buildings and other structures

• Observations are fed into battle-planning systems (e.g., MBP) through the CoABS Grid.

• In the demo, a team of CoAX soldiers will make observations to correct Gao mis-information.


Observations

Field Observations (Dartmouth)

ObservationAgent

D’Agents API

GridAPI

I see a tank!

ObservationViewer

MBP

(9-month demo - standalone)

(18-month demo - integrated)

Query/Response

Registration/Update Stream


MIT Robustness MIT Robustness ServiceService

The ChallengeThe Challenge Open systems (like coalitions) include unreliable Open systems (like coalitions) include unreliable

agents (bugs, malice) and infrastructuresagents (bugs, malice) and infrastructures The MIT Robustness ServiceThe MIT Robustness Service

Monitors agent ‘health’ via pollingMonitors agent ‘health’ via polling Tracks inter-agent commitmentsTracks inter-agent commitments Controls task cancellation, result caching & task re-Controls task cancellation, result caching & task re-

announcementannouncement Maintains reliability information (failure avoidance)Maintains reliability information (failure avoidance) Informs registry of hung agentsInforms registry of hung agents


Michigan Multilevel Michigan Multilevel Coordinator AgentCoordinator Agent

Analyses the alternative plan spaces of coalition functional Analyses the alternative plan spaces of coalition functional teams that plan independently and act asynchronouslyteams that plan independently and act asynchronously

Works top-down with plans chosen by teams to predict Works top-down with plans chosen by teams to predict unintended interactions (resource contentions; friendly fire).unintended interactions (resource contentions; friendly fire).

Identifies candidate resolutions (timing or action Identifies candidate resolutions (timing or action constraints).constraints).

Notifies process panel of possible plan conflicts and Notifies process panel of possible plan conflicts and computed workarounds.computed workarounds.

Operationalizes/enforces coordination decisions selected.Operationalizes/enforces coordination decisions selected. Given more time, isolates and resolves conflicts more Given more time, isolates and resolves conflicts more

precisely and efficiently.precisely and efficiently. Allows planning and coordination decisions to be postponed Allows planning and coordination decisions to be postponed

until runtime conditions become better known.until runtime conditions become better known. Packaged as a Grid-aware component that can be Packaged as a Grid-aware component that can be

proactively executing and utilized by the AIAI Process Panel.proactively executing and utilized by the AIAI Process Panel.


Michigan Multilevel Michigan Multilevel Coordinator AgentCoordinator Agent


Removed and Spare Removed and Spare SlidesSlides

Old versions and spare slidesOld versions and spare slides


Policy EnforcementProblems and Solutions

Problem: Enforcing policies on unmodified, potentially malicious agents Solution: Platform-based enforcement (e.g., Java 2 security) Problem: Permissions granted statically according to code source (can’t have different permissions for two agent instances from same code base)

Solution: Hack JAAS (Java Authentication and Authorization Service) to allow dynamic permissions and instance-level authentication and authorization

Problem: High-level agent security requirements do not always map to low-level built-in Java security mechanisms

Solution: Lock down permissions of untrusted (agent) code and force agent to use a trusted privileged-code wrapper under control of the guard (eventually to be packaged as domain-aware “grid helper”) to perform selected actions

Problem: Fine-grained resource allocation and control and revocation of permissions in the face of denial-of-service attacks

Solution: Run agent under Java-compatible Aroma VM allowing dynamic fine-grained resource rate and quantity control

Problem: “Obligation policies” cannot be enforced by preventing actions in advance but only by monitoring and after-the-fact sanctions

Solution: Sentinel-based policy enforcement (relevant work in this area by MIT)


Field Observations (Dartmouth)Field Observations (Dartmouth)


Michigan Coalition Michigan Coalition CoordinationCoordination

Coalitions formed in response to emergent needsCoalitions formed in response to emergent needs

Functional teams (firestorm, logistics, etc.) formed with Functional teams (firestorm, logistics, etc.) formed with participants from contributing partnersparticipants from contributing partners

Without prior history, functional teams can possibly act Without prior history, functional teams can possibly act redundantly, counterproductively, or even harmfully redundantly, counterproductively, or even harmfully (e.g., friendly fire)(e.g., friendly fire)

Problem: Supporting (through automation) the Problem: Supporting (through automation) the identification of potential interferences between identification of potential interferences between functional teams at appropriate level(s) of detail, and functional teams at appropriate level(s) of detail, and proposing mitigation strategiesproposing mitigation strategies


Coordination Decisions:• Logistics stays on ground• Combat waits for Logistics to use Epsilon before destroying

Michigan Coalition Michigan Coalition Coordination ExampleCoordination Example

Logistics: Deliver experimental weapon from Alpha to Foxtrot

Alpha

Foxtrot

Gamma

Delta

Combat: Deny airspace Beta; destroy bridge Epsilon

Beta

Epsilon

CoAX Technology Contributions TTCP Meeting - Malvern - September 2000 AFRL Rome, AIAI, Boeing,...

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