Monitoring, Policing and Trust for Grid-Based Virtual Organisations

1. Monitoring, Policing and Trust for Grid-Based Virtual Organisations Luke Teacy I.A.M Group, ECS University of Southampton, UK

2. Overview • Dynamic Virtual Organisations • Concept • Key Challenges • CONOISE-G • Architecture • Managing the VO Lifecycle • Emphasis on Trust, Monitoring & Policing

3. Virtual Organisations (VOs) • The Grid concept: • “coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organisations” • Foster et al 2001 • Virtual Organisations: • people, resources (hardware/software) • Crossing geographical and organisational boundaries • Keyword: Dynamic • VO membership & operation should be able to change to meet changing circumstances dynamic,

4. CONOISE-G • CONOISE-G aims to support robust and resilient VO formation and operation in open and competitive environments. • Lucy goes to the Olympics — Lucy wants • Video clips • News • Ad-hoc services for her PDA • Dynamically bring together infrastructure and content to meet changing demand • How do we do this?

5. Our Approach: Agents and the Grid • Brawn • Existing Grid Infrastructure • How to integrate services between organisations • Different policies and infrastructures • Robust and Secure • Brains • CONOISE-G: Multi-Agent System • Which services and for what and when? • Decision processes, Negotiation • Brain Meets Brawn: Why Grid and Agents Need Each Other — Foster, Jennings, Kesselman, 2004

6. Agents VO CONOISE-G Grid Services, Globus etc Grid Infra-Structure Our Approach

7. Keys Challenges VO Formation VO Operation • Should contracts be honoured? • Are there better services? • What QoS is being provided? • Who is available? • What QoS will be provided? • Who should be selected? • Where Service Providers: • Can enter and leave the system • Can compete against one another for orders. • Cannot entirely be trusted to honour their promises.

8. SP1 SP2 SPn QA QoSC System Architecture YP CA SP – Service Provider RB VOM – VO Manager YP – Yellow Pages CA – Clearing Agent RB – Reputation Broker PA – Policing Agent QoSC – QoS Consultant QA – Quality Assessor VOM PA

9. VO Lifecycle Market Demand 1) Discover services 2) Obtain bids 3) Select bids 6) Perturbation 4) Form the VO 5) Monitor Services

10. Service Discovery & Obtaining Bids

11. SP1 SPn Discovering Services • For a given service request, discover who can be a potential provider. VOM YP • Publish subscribe model so VOM is constantly informed of new agents

12. Obtaining Bids • VOM calls for Bids based on advertised services • An SP must decide whether/what to offer. • SP uses constraint reification in decision making • See references for details

13. Selecting Bids Trust Assessment Quality Assessment Choosing Winning Bids

14. SP1 Establishing utility for providers QA TC Price SPk Utility Calculator SP1 Choose SP set offering best overall utility CA SPk Selecting Bids (Overview) • Assessing the bids • Conducting an Auction

15. Assessing Bids - QoS • Expectation Based Confidence Assessment of QoS • Given a set of VOM QoS expectations (qi>x)*, how likely is it that those expectations will be met? • Taking into account: • past provision instances with similar expectation only • the statistical relationship between QoS attributes • Operating under time constraints • Tradeoff performance with accuracy • Goal: dynamic, near-instantaneous assessment

16. Assessing Bids - Trust • Trust – How likely is an SP to fulfil its obligations? • Probabilistic Trust Model • Assess the trustworthiness of SPs using: • Internal Trust Component: Based on personal experience • Reputation: Based on opinions of other agents • Reputation Filtering Mechanism

17. Calculating Utility • Estimate probability of successful contract outcome with SP based on Quality & Trust • Calculate Expected Utility • Allocate tasks to SPs using efficient polynomial time algorithm

18. VO Formation Hiring Service Providers Establishing Contracts

19. SP SP RA SP SP Forming VO • Setting up arrangements for service provision to be monitored. • Policing: • Contract management & evaluation • Contract = Service Level Agreement (SLA) VOM QoSC YP Market

20. Contracts Overview • Much work has been done on contracting languages • formal approaches have clear semantics, but often lack useful features. • ad hoc approaches are hard to reason with, but usually very descriptive. • we try to take a middle road. • SWCL (semantic web contracting language) • Based on RDF and SWRL (Semantic Web Rule Language) • Attempts to fulfil the above desiderata.

21. Existing Contract Languages • WS-Agreement • Does not have a way of referring to other agents,contracts and clauses easily. • Expects one to embed an evaluation language within it. • Essentially, a wrapper for a contract outline • LCR • Solid formal approach • Difficulty representing many useful contracting features.

22. Contract Language in CONOISE-G (SWCL) • Can describe things such as • Which parties are involved • Time constraints for agreement start and end times • Representation of actions by agents • Assignment of rewards and penalties • Refer to other agents, contracts and clauses • Example (natural language): • Contract effective from 00:00 31/12/05 for 24hrs • SP1 to provide movie every 3hrs, each 1-2hrs long • SP1 must pay £20 penalty for each 3hr period without movie • All Penalty fees due at contract end time.

23. VO Operation QoS Monitoring Policing Perturbation

24. Operation Overview • Monitor Environment • Adapt VO membership/roles to changing circumstances (Perturbation) • Scenarios • New Service enters market place • Current service fails / breaks contract

25. New Service Perturbation New Service Advertised • SP registers/updates advertisement with YP • YP informs VOM of new service • VOM obtains bid from SP VOM Considers Bid • VOM calculates utility gain of hiring new SP • New SP utility vs. current providers • Penalty clauses in contract Hire new SP Fire old SP(s) • Hire / Fire if necessary

26. Service Recovery Perturbation Monitor Services • Essential for: • Tracking performance to ensure SLA is adhered to • Triggering corrective action by VO • Providing evidence for establishing trust • Challenges • To handle continuous, potentially fast data input • To handle ad-hoc, long-standing monitoring requests • To process the requests with real-time performance

27. Service Recovery Perturbation VOM re-formed Monitor Services • VOM calls for bids for failed service • Excluding failed service provider • Utility assessed for received bids as before • Taking on board quality, trust & price • And penalties • Auction cleared • Hire and fire messages sent

28. Conclusions • The ability to form and operate virtual organisations in grid is important. • We aim to support robust and resilient VO formation and operation. • We have developed technologies for: • Decision making mechanisms during VO formation • Assessing trust & reputation • Policing within VOs • QoS monitoring

29. Future Work • Real-time QoS Prediction • Contracting • We can generate and evaluate simple contracts. • We have not yet formalized its semantics. • Policing • Investigate reasons behind failure • Who should take the blame? • Argumentation-Based Negotiation • Trust updated according to conclusion

30. References • W. T. L Teacy, J. Patel, N. R. Jennings and M. Luck, Coping with Inaccurate Reputation Sources: An Experimental Analysis of a Probabilistic Trust Model. In AAMAS’05, 2005 • N. Oren, A. Preece and T. J. Norman, Service Level Agreements for Semantic Web Agents. 2005 • S. Chalmers, A. Preece, T. J. Norman and P. M. D. Gray, Commitment Management Through Constraint Reification. In AAMAS’04, 2004 • G. Shercliff, P. J. Stockreisser, J Shao, W. A. Gray and N. J. Fiddian, Supporting QoS Assessment and Monitoring in Virtual Organisations. 2005 • All References available at: http://www.conoise.org/

31. Constraint Oriented Negotiation in Open Information Seeking Environments for the Grid Demonstration: 10:30 Welsh e-Science Booth Alun PreeceTim Norman Peter Gray Stuart Chalmers Nir Oren Alex Gray Nick Fiddian Jianhua Shao Gareth ShercliffPatrick Stockreisser Nick Jennings Mike Luck Luke Teacy Jigar Patel Simon Thompson http://www.conoise.org/