1. Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Chapter 22: Building SOC Applications
Service-Oriented Computing: Semantics, Processes, Agents – Munindar P. Singh and Michael N. Huhns, Wiley, 2005
© Singh & Huhns

2. Highlights of this Chapter
Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Highlights of this Chapter
Elements of SOC Design
Self study: Quality of Service
Self study: How to Create an Ontology
Self study: How to Create a Process Model
How to Construct Agent-Based Systems
How to Engineer Composed Services
Exception Handling
Self study: Knowledge Management
Self study: eBusiness
Supply-Chain Automation
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns

3. Elements of Service-Oriented Architectures
Loose coupling: focus should be on high-level contractual relationships
Implementation neutrality: the interface is what should matter
Flexible configurability: late binding of components
Long lifetime: components should exist long enough to be discovered, to be relied upon, and to engender trust in their behavior
Granularity: interactions and dependencies should occur at as high a level as possible
Teams: computation in open systems should be conceptualized as business partners working as a team
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

4. Goals for Multiagent Control
Develop techniques for
Locating and allocating capabilities and resources that are dispersed in the environment
Predicting, avoiding, or resolving contentions over capabilities and resources
Mediating among more agents, with more heterogeneity and more complex interactions
Maintaining stability, coherence, and effectiveness
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

5. Control Challenges: Agents
Control gets harder as agents become more:
Numerous
Complex individually (e.g., more versatile)
Heterogeneous (in capabilities, representations, languages)
quantity
complexity
heterogeneity
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

6. Control Challenges: Problems
Control gets harder as the problems agents solve become more
Interrelated
Rapidly changing, or pursued in an uncertain and changing world
Unforgiving of control failures (e.g., involving irreversible actions)
degree of interaction
volatility
severity of failure
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

7. Control Challenges: Solutions
Control gets harder as solutions to agent problems are required to be more
Efficient
Robust to changing circumstances
Cheaper or faster to develop individually and in concert
quality / efficiency
robustness
low overhead
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

8. Techniques for Agent Control
Broker-based
Matchmaker-based
Market-based; auctions
BDI and commitment based
Decision theoretic
Workflow (procedure) based
Standard operating procedures
Learning
Coordinated planning
Conventions
Protocols
Stochastic or physics-based
Organizations: teams and coalitions
Constraint satisfaction or optimization
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

9. Dimensions of Control Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

10. Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

11. Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

12. Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Task Decomposition
Divide-and-conquer to reduce complexity: smaller subtasks require less capable agents and fewer resources
Task decomposition must consider the resources and capabilities of the agents, and potential conflicts among tasks and agents
The designer decides what operators to decompose over
The system decides among alternative decompositions, if available
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns

13. Task Decomposition Methods
Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Task Decomposition Methods
Inherent (free!): the representation of the problem contains its decomposition, as in an AND-OR graph
Composition designer (human does it): decomposition is programmed during implementation. (There are few principles for automatically decomposing tasks)
Hierarchical planning (agents implementing the services do it): decomposition again depends heavily on task and operator representation
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns

14. Task Decomposition Examples
Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Task Decomposition Examples
Spatial decomposition: service is info source or decision point:
Functional decomposition: service offers specialized expertise:
Agent 1
Agent 3
Agent 2
Pediatrician
Neurologist
Internist
Cardiologist
Psychologist
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns

15. Task Distribution Criteria
Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Task Distribution Criteria
Avoid overloading critical resources
Engage services on tasks where expertise matches
Make an agent with a wide view assign tasks to other agents
Assign overlapping responsibilities to agents to achieve coherence
Assign highly interdependent tasks to agents in spatial or semantic proximity. This minimizes communication and synchronization costs
Reassign tasks if necessary for completing urgent tasks
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns

16. Task Distribution Mechanisms
Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Task Distribution Mechanisms
Market mechanisms: tasks are matched to agents by generalized agreement or mutual selection (analogous to pricing commodities)
Contract net: announce, bid, and award cycles
Multiagent planning: planning agents have the responsibility for task assignment
Organizational structure: agents have fixed responsibilities for particular tasks
Recursive allocation: responsible agent may further decompose task and allocate the resultant subtasks
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns

17. JADE Behavior for CNP Initiator Role
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

18. Two Patterns for Engineering Service Applications
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

19. Agents for Collaboration
Each Business Collaboration is handled by an autonomous software entity (agent)
On forming a Collaboration, automatically generate ebXML-compliant agents
The “Agent Generator,” when integrated with the BSI, has static knowledge about local constraints and dynamic knowledge from the current CPA
The software agents exchange ebXML messages to perform the selected Business Collaboration
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

20. Why this Approach?
Issues regarding transport, messaging, security constraints are to be handled for each Collaboration
Business collaborations are becoming increasingly complex
The system will be dealing with multiple collaborations at a given time
If the transactions are legally bound or even otherwise, the non-repudiation condition MAY have to be satisfied
There is always a possibility of unpredictable situations (exceptions)
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

21. Agent-Based Coordination Methodology
BOD Semantics
Robust
Agent
Skeleton
Dooley
Graph
Agent
Skeleton
Participants
Enact B2B
Interaction
Agents
Create
Agent-Based
B2B
Transaction
State Machine
Participants
Develop B2B
Interaction
Diagrams
Identify B2B
Conversations
Augment
B2B
Transaction
State Machine
Generic B2B Use-Case and Class Models
Exception-Augmented Transaction Templates
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

22. Ford Interoperability Scenario
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

23. Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Conversation Analysis Based on Mutual Understanding (Bipartite Conversation Graph)
Sender
Receiver
Ford1
1Jarvis
Ford2
2Lubetec
Ford3
3Eff.Logistics
Jarvis4
4Ford
Lubetec5
5Ford
The arcs above help identify the roles of the participants in the B2B transactions. The notation Ford1 indicates that message 1 (to Jarvis) is being sent by Ford; the notation 4Ford indicates that message 4 (sent by Jarvis) is being received by Ford. This graphical technique is the basis for constructing collaboration diagrams.
Explanation: The arc from Ford1 to 4Ford indicates that Jarvis in message 4 is replying to Ford’s message 1 (ProcessPO). The arc from Lubetec6 to 2Lubetec indicates that message 6 (ShowShipment) resolves Ford’s message 2 (ProcessPO). The arc from Ford2 to 7Ford indicates that message 7 completes intermediate messages 5, which, in turn, resolves message 2. The semantics of respond, reply, resolve, and complete can be found in [Singh 2000] and [Parunak 96].
[Singh 2000] Munidar P. Singh, “Synthesizing Coordination Requirements for Heterogeneous Autonomous Agents,” Autonomous Agents and Multi-Agent Systems, no. 3, 2000, pp
[Parunak 1996] H. Van Dyke Parunak, “Visualizing Agent Conversations: Using Enhanced Dooley Graphs for Agent Design and Analysis, International Conference on Multi-Agent Systems, ICMAS-1996, pp
Lubetec6
6Ford
Lubetec7
7Ford
Jarvis8
8Ford
Jarvis9
9Ford
Ford10
10Greenfield
Greenfield11
11Ford
Greenfield12
12Ford
Greenfield13
13Ford
Eff.Logistics14
14Ford
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns

24. Transaction Skeletons for Agent Enactment
Supplier
Warehouse
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

25. Augmented Transaction Skeletons for Agent-Based Exception Handling
Ignore Exceptions
Consider Exceptions
Order Complete
Order Complete
Receive( payment ) ^send("Thank you")
Receive( payment ) ^send("Thank you")
exceeded( Deadline ) ^send(ReminderInvoice)
Waiting for
Waiting for
Payment
Payment
^send(ProcessInvoice)
Set Deadline
Alarm
Start
^send(ProcessInvoice)
Start
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

26. Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Chapter 22 Summary
Success of service-oriented computing solutions depends upon
How ontologies and process models are constructed
How a system is designed so that desired behaviors ensue
How abstractions for interaction are fleshed out
How the above are related to software engineering approaches
Chapter 22
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns