1. S-Cube Learning Package Service Level Agreements: Analysis Operations on SLAs:Detecting and Explaining Conflicting SLAs ISA Group, University of Seville (Spain)C. Mller, O. Martn-Daz, A. Ruiz-Corts, M. Resinas www.s-cube-network.eu

2. Learning Package Categorization S-Cube Quality Definition, Negotiation and Assurance Quality Management and Prediction Analysis Operations on SLAs: Detecting and Explaining Conflicting SLAs ISA Group

3. Learning Package Overview Problem Description Problem Approach Solution Approach Solution Validation Discussion Conclusions ISA Group

4. Problem Description:A Logistic Scenario Package Tracking Provider

5. Problem Description: A Logistic ScenarioTemplate-Offer based mechanism to create SLAs. An example of two van companies offering different QoS Package Tracking Provider

6. Problem Description: Temporal-Aware SLAs in the ScenarioTemporal-Aware SLAs are createdwhen temporal-aware documents are used.In the example two providers sendagreement offers with different QoS indifferent time periods.

7. Problem Description: Detecting Conflicting SLAs Within documents At any SLA lifecycle phase. Is my Offer (for instance, at edition time) Conflict free? Is my Template Conflict free? Is the sent Offer compliant with the Template? Is the received Offer compliant with my Between documents Template? At any SLA lifecycle phase in which documents compliace[Answer for Questions: must be assured. YES or NOT] (for instance, at negotiation time)

8. Problem Description: Explaining Conflicting SLAs Within documents At any SLA lifecycle phase. Why is conflicting (for instance, at edition time) my Offer? Why is conflicting my Template? Why Is the sent Offer non-compliant with the Template? Why is the received Offer non-compliant Between documents with my Template? At any SLA lifecycle phase in which documents compliace[Answer for Questions: must be assured. Conflicts Explanations] (for instance, at negotiation time)

9. Problem Description:WS-Agreement as Case StudyWS-Agreement - Definition: An XML language and a protocol for Advertising the capabilities of service providers in templates Creating agreements based on creational offers and templates I want an agreement * Service Features: * Guarantees:

10. Problem Description:WS-Agreement as Case StudyWS-Agreement Template vs. Offers Differences

11. Problem Description:WS-Agreement as Case StudyWS-Agreement Template vs. Offers Differences Use case An optional Qualifying Condition (QC) may be included to enable/disable guarantees. Methaphor

12. Learning Package Overview Problem Description Problem Approach Solution Approach Solution Validation Discussion Conclusions ISA Group

13. Problem Approach:Temporal-Aware WS-Agreement docs.Temporal-Aware Scenario Mon-Sat (Weekly) From Jan 01/2013 to Dec 31/2013 Sunday (Weekly) From Jan 01/2013 to Dec 31/2013

14. Problem Approach:Temporal-Aware WS-Agreement docs.Temporal-Aware Scenario Mon-Sat (Weekly) From Jan 01/2013 to Dec 31/2013 Sunday (Weekly) From Jan 01/2013 to Dec 31/2013 Mon-Fri (Weekly) From Jan 01/2013 to Dec 31/2013

15. Problem Approach:Temporal-Aware WS-Agreement docs.Temporal-Aware Scenario Mon-Sat (Weekly) From Jan 01/2013 to Dec 31/2013 Sunday (Weekly) From Jan 01/2013 to Dec 31/2013 Mon-Fri (Weekly) From Jan 01/2013 to Dec 31/2013 Mon-Fri (Weekly) From Jan 01/2013 to Dec 31/2013 Sat-Sund (Weekly) From Jan 01/2013 to Dec 31/2013

16. Problem Approach:Kind of Conflicts to Detect & Explain Within documents Inconsistencies: Contradiction between terms, parts of terms, or creation constraints, and all of these amongst themselves; constitute an inconsistency of the WSAgreement document. This means that it is impossible to find a satisfactory assignment to the variables that appear in those terms or creation constraints. The consequence is that the whole document is unusable because it will never be fulfilled regardless of the way the service is provided. Term inconsistencies can be originated by any combination of service description terms, guarantee terms and creation constraints, including such elements with themselves

17. Problem Approach:Kind of Conflicts to Detect & Explain Within documents Inconsistencies: (Sample 1/2) The messenger company impose a cost formula depending on the package weight. But the guarantee term involving the cost is inconsistent with such formula.

18. Problem Approach:Kind of Conflicts to Detect & Explain Within documents Inconsistencies: (Sample 2/2) The messenger company assure a wrong DeliveryTime by mistake.

19. Problem Approach:Kind of Conflicts to Detect & Explain Within documents Dead Terms: This conflict is caused when the condition of a conditional term can never be satisfied in a WSAgreement document. In other words, a dead term is a guarantee term whose qualifying condition has a contradiction with itself or one or more terms and/or creation constraints of the WSAgreement document. Consequently, this kind of conflict makes the term dead because its service level objective (SLO) can never be applied since its precondition never holds.

20. Problem Approach:Kind of Conflicts to Detect & Explain Within documents Dead Terms: (Sample 1/1) The messenger company wanted to assure a maximum delivery time for the express and premium delivery types. But there was a wrong multiple value assignment in the QC, by a mistake while mapping the natural language condition to a WS-Agreement condition. The right condition would be: DeliveryType = Premum OR DeliveryType = Express

21. Problem Approach:Kind of Conflicts to Detect & Explain Within documents Ludicrous Terms: This conflict is caused when a conditional term makes the document inconsistent if its condition holds, which contradicts usual expectations. In other words, a ludicrous term is a guarantee term with the following characteristics: 1. It is not inconsistent 2. Its qualifying condition holds 3. Its SLO does not hold because of a contradiction within itself, with the qualifying condition or with other terms or creation constraints of the WSAgreement document. Consequently, the ludicrous term is one that when the qualifying condition holds, the SLO and, hence, the guarantee term, does not hold.

22. Problem Approach:Kind of Conflicts to Detect & Explain Within documents Ludicrous Terms: (Sample 1/1) The messenger company wanted to assure a maximum cost for deleveries of 1 kg packages and the delivery types express and premium. In this case the QC is correctly defined but when its fulfills the SLO cannot be satisfied due to the cost formula depending on weight.

23. Problem Approach:Kind of Conflicts to Detect & Explain Within Temporal-Aware documents Inconsistencies, dead and ludicrous terms conflicts applies but only if the involved terms or creation constraints are defined in overlapped time periods The sample does not include any conflict because working and home period definitions are nor overlapped (see slide 15)

24. Problem Approach:Kind of Conflicts to Detect & Explain Within Temporal-Aware documents Current sample includes a inconsistency conflict between locating accuracy guarantees because working and Christmas period definitions overlaps as can be seen below

25. Problem Approach:Kind of Conflicts to Detect & Explain Between documents WS-Agreement Compliance definition The same agreement responder and template id in both documents Offer service terms must be compliant with template creation constraints There must be a compliance between the terms of both documents

26. Problem Approach:Kind of Conflicts to Detect & Explain Between documents WS-Agreement Compliance definition In current sample, assuming the same agreement responder and template id, The offer service terms are compliant with template because Cost has a right value assignment considering the template cost creation constraint. But guarantee terms of both documents are not compliant. Then documents are not compliant.

27. Problem Approach:Kind of Conflicts to Detect & Explain Between Temporal-Aware documentsPrevious compliancedefinition applies but only ifthe involved terms or creationconstraints are defined inoverlapped time periodsThe sample does not includeany conflict because workingand home period definitionsare not overlapped(see slide 15)

28. Problem Approach:Kind of Conflicts to Detect & Explain Between Temporal-Aware documentsCurrent sample includes anon-compliance betweendelivery time guarantees atworking period.

29. Problem Approach:Kind of Conflicts to Detect & Explain Between Temporal-Aware documentsCurrent sample includes anon-compliance betweenservice term 1 and thetemplate creation constraints.This situation me beintentional by a try to pay lessfor the delivery service fromthe client who defined theagreement offer.

30. Learning Package Overview Problem Description Problem Approach Solution Approach Solution Validation Discussion Conclusions ISA Group

31. Problem Approach:Automating Analysis of SLAs There are several approaches that can be used to detect and explain conflicts within documents and between documents automatically. For instance, one may think of creating ad-hoc algorithms to detect the different types of conflicts. Or one may think of using an ? Analyser existing paradigm that provides generic algorithms to detect them such as: Description Logics Constraints Satisfaction Problems

32. Problem Approach:Automating Analysis of SLAs In this presentation we focus on the use of constraint satisfaction problems (CSPs) as the paradigm to tackle this problem automatically. The reasons are: The most significant part of an SLA is Constraint a set of constraints that are set on some properties or descriptions of the service and, therefore, CSPs can be ? Satisfaction Problems used to describe this problem in a very natural way. There are a plethora of CSP solvers with efficient algorithms that can be used to detect conflicts automatically. This approach has been used successfully in many related work.

33. Background:Constraint Satisfaction Problems CSPs allow modelling and solving expressive problem models based on constraints and they have been an object of research in Artificial Intelligence over the last few decades. A CSP is a threetuple of the form (V , D, C) where V = is a finite set of variables, D = is a finite set of domains (one for each variable) and C is a set of constraints defined on V. b The solution of the CSP is the value assignments to the set of variables V that satisfy all of the constraints C a S-Cube

34. Background:Constraint Satisfaction Problems For instance, given the CSP: ({a, b}, { [0, 1], [0, 1] }, { a = b }) A solution is whatever valid assignment of all elements in V that satisfies C. b 1 1,1 a, b: integer [0,1] a=b 0,0 0 1 a Operation solve( V, D, C) is the operation of CSP solvers that returns the solutions of a CSP and many heuristics and techniques have been developed to obtain these solutions in an efficient manner. S-Cube

35. Background:Constraint Satisfaction Problems Operation explain (V, D, C) involves providing an explanation when such solution is not possible. This explanation is a minimal set of constraints c C that makes it impossible to find a valid assignment of all elements in V that satisfies c, i.e., that makes solve(V , D, c) = For instance: In the CSP: ({a, b, c}, {[0..2], [0..2], [0..2]}, {a + b < 1, c = 2}) The explantion c = {(a+b