reasoning about the behavior of semantic web services with concurrent transaction logic

ReasoningReasoning about the Behavior of Semantic Web about the Behavior of Semantic Web Services with Concurrent Transaction LogicServices with Concurrent Transaction Logic

Presented By Dumitru Roman, Michael Kifer

University of Innsbruk, State University of New York

2008-01-04

Summerized By Sungchan Park

Copyright 2008 by CEBT

OverviewOverview

Improve the authors’ previous works on Web Service modeling

Concurrent Transaction Logic(CTR)

– Logic based Modeling and Analysis of Workflows. 1998

– A Logical Framework for Scheduling Workflows under Resource Allocation Constraints. 2002

– CTR-S: A Logic for Specifying Contracts in Semantic Web Services. 2004

Reasoning about behavior about WS

– Contracting, Enactment

Improvement

– Conditional control, data flow

– More general constraints

– Simpler logic than CTR-S

Center for E-Business Technology


Modeling & Reasoning about Service Modeling & Reasoning about Service BehaviorBehavior



Modeling & Reasoning about Service Behavior: Modeling & Reasoning about Service Behavior: ExampleExample



The Basics of CTRThe Basics of CTR

Atomic formula

P(t1, t2, …, tn)

– P : predicate

– ti : function term

Complex formulas are built using connectives and quantifiers

Informal Sematics

Database states

– Eg. s1, s2, …, sn

Paths( sequences of states)

– Eg. <s1>, <s1, s2>, …

– Truth value of CTR formula is determined over path

– Formula a is true over a path <s1, s2, …, sn> iff a can “excute” starting at state s1, change to s2, s3, … etc. Will terminate at state sn.



The Basics of CTR, Cont.The Basics of CTR, Cont.

CTR Connectives

a ⊗ b

– execute athen execute b

a | b

– a and bmust both execute concurrently in an interleaved fashion.

a ᴧ b

– a and b must both execute along the same path

– Constraints

a ᴠ b

– execute a or execute b non-deterministically

¬a

– execute in any way, provided that this will not be a valid execution of a

⊙a

– execute a in isolation execution i.e., without interleaving with other concurrently running activities



Concurrent-Horn subset of CTRConcurrent-Horn subset of CTR

Concurrent-Horn rule

p ← q

– Means “if q can execute along path <s1, … , sn>, then so p can

do”

– p : atomic formula

– q : concurrent horn goal

Atomic formula

a ⊗ b, a | b, a V b when a and b are concurrent horn goals

⊙a when a is concurrent horn goal

Examples

– Process ← a ⊗ ( b | Subproc ) ⊗ g

– Subproc ← ( c ⊗ ( d v ( e ⊗ f )))



Concurrent-Horn subset of CTR, Cont.Concurrent-Horn subset of CTR, Cont.

Can use SLD-like proof procedure

In previous work, G ᴧ C can be transformed into horn goal by limiting class of constraints

In present work, however, the extended proof theory of CTR overcomes the limitation of constraints



Modeling Services with CTR: Control Modeling Services with CTR: Control FlowFlow



Modeling Services with CTR: Modeling Services with CTR: ConstraintsConstraints

Unlike previous works, we use predicates with variables—not just propositions—to represent control and data flow.

Constraints Algebra

Event

– e = ∃DataFlowVar eventName(DataFlowVar)

Primitive

– ∇e : Event e must happen = path ⊗ e ⊗ path

– ¬ ∇e : Event e must not happen

Immediate serial constraints

– ∇ ⊙(e1 ⊗ … ⊗ en) : e1, …, en happen next to each other with no other event in-between

Serial constraints

– ∇ (e1 ⊗ … ⊗ en) : e1, …, en excute in that order with possible interleaving

Complex constraints

– C1 ∧ C2, C1 ∨C2



Modeling Services with CTR: Constraints, Cont.Modeling Services with CTR: Constraints, Cont.

Expression Examples Events e and f must both occur (in any order)

– ∇e ∧ ∇f

It is not possible for e and f to happen together– ¬ ∇e ∧ ¬ ∇f

If event e occurs, then f must also occur (before or after e)– ∇e → ∇f

If event e occurs, then f must occur later– ∇e → (∇e ⊗ ∇f)

If event f has occurred, then event e must have occurred some time prior to that– ∇f → (∇e ⊗ ∇f)

If both e and f occur, then e must come before f– (∇e ∧ ∇f) → (∇e ⊗ ∇f)

If event e occurs, then f must occur right after e with no event in-between– ∇e → ∇ ⊙(e ⊗ f)

If k and d both occur then d must happen right after k with no other event in-between– (∇k ∧ ∇d) → ∇ ⊙(k ⊗ d)



Modeling Services with CTR: Constraints, Cont.Modeling Services with CTR: Constraints, Cont.



Modeling Services with CTR: Modeling Services with CTR: Data Flow and Conditional Control FlowData Flow and Conditional Control Flow

Data flows imply constraints



Modeling Services with CTR: Modeling Services with CTR: Data Flow and Conditional Control FlowData Flow and Conditional Control Flow

Conditions in control flow are checked ahead and unsatisfiable branches are eliminated



Reasoning about Choreography and Reasoning about Choreography and ContractsContracts

Contracting

Determine if contracting for the service is possible

– Find out if there is an execution of the CTR formula G ∧ C given the set of service choreography definition R

– Check that there is a path s1, s2, …, such that

R, s1, …, sk ㅑ G ∧ C

Enactment

Find a constructive proof that

– R, s1, …, sk ㅑ G ∧ C for some paht s1, …, sk

– Each proof is a way to execute the choreography so that all constraints are satisfied



Reasoning about Choreography and Contracts, Reasoning about Choreography and Contracts, Cont.Cont.

Phase 1

Transform to normal form

– From G ∧ C to ∨i(Gi ∧j serialConstrij)

Gi is a concurrent-Horn goal and SerialConstrij is either an immediate serial constr. or a serial constr.

– NP-Complete in the size of largest number of disjuncts in C

Phase 2

Find the proof using inference rules

– If proof is found, them enactment of the service is possible

– Linear in the size of the execution path



Reasoning about Choreography and Contracts, Reasoning about Choreography and Contracts, Phase 1Phase 1

Transformation rules

Applying Complex Constraints

Applying Primitive Constraints

If the result is ¬path, then enactment is not possible

Otherwise, the result is a formula of the form ∨i(Gi ∧j serialConstrij)



Reasoning about Choreography and Contracts, Reasoning about Choreography and Contracts, Phase 2Phase 2

Phase 2 has two step

1. Check constraints for internal consistency and eliminate redundancy

2. Apply inference rules



Reasoning about Choreography and Contracts,Reasoning about Choreography and Contracts,Phase 2:Step 1Phase 2:Step 1

Check inconsistency

Inconsistent patterns

Eliminate redundancy

Examples



Reasoning about Choreography and Contracts,Reasoning about Choreography and Contracts,Phase 2:Step 2Phase 2:Step 2

Extended Inference System

hot(Ψ)

– “ready to be excute”

1. hot(Ψ) = Ψ , if Ψ is atomic formula

2. hot(Ψ ⊗ Ф) = hot(Ψ)

3. hot(Ψ | Ф) = hot(Ψ) | hot(Ф)

4. hot(Ψ ∨ Ф) = hot(Ψ) ∨ hot(Ф)

enabled(C)

– The set of enabled component of a set of constraints C is as follows: enabled(C) = {x | x is a root node of C or x is not in C}

eligible(Ψ)

– x, if x ∈ hot(Ψ) ∩ enabled(C) and x is and exclusive node in C

– hot(Ψ) enabled(C), otherwise eligible(Ψ) ⊆ hot(Ψ)



Reasoning about Choreography and Contracts,Reasoning about Choreography and Contracts,Phase 2:Step 2, Cont.Phase 2:Step 2, Cont.

Inference rules

1. Applying transactional definitions

– If b ← β be a rule in P and assume that its variables have been renamed so that none are shared with Ψ. If a and b unify with the most general unifier σ then then,

– Ψ’ is Ψ with some occurrence replaced with b

– C’ is C after deleting a and splicing edges adjacent on a

2. Querying the database

– If (∃)aσ is true in D and aσ and G’σ share no var. then,

– Ψ’ is Ψ with some occurrence of a deleted




Inference rules, cont.

3. Executing elementary updates

– If aσ is an elementary state transition from state D1 to D2 then


– C’ is C with after deleting some nodes

4. Executing atomic transactions

– If ⊙α is hot component in then,





Difference with previous CTR inference system

1. Rule 3 operates on eligible occurrence of atomic formula, while previous one did on a larger set of hot occurrence

2. Rule 1 and 3 also modify the set of constraints



Bird’s Eye View of the ApproachBird’s Eye View of the Approach

The Web service designer starts to build Web service choreography by drawing a control flow graph, a data flow graph, and specifying service policy using a GUI tool.

The logical representations can be constructed automatically from an appropriately instrumented GUI tool.

The designer then uses the algorithm to find un-enactable parts of the control flow graph.

The designer uses the CTR reasoner-based algorithm to make sure that the control graph is consistent with the service policies.

The client submits the contract requirements to verify that a contract is possible. As before, verification is done using the CTR.



Related WorkRelated Work

Service contracting Existing work focuses on defining frameworks, models, and architectures

different aspects and phases of e-contracting (negotiation, enforcement, violation detection, monitoring, legal aspects)

We provide a simple yet realistic and useful framework for e-contracting– Solve a concrete problem in establishing of contracts and enacting Web services

Workflow/process modeling Many languages for process modeling, e.g. YAWL, DecSerFlow

Ours is as expressive as DecSerFlow, and additionally integrates with conditional control flows, data flows, provides reasoning mechanisms

Process verification Most of the existing approaches use model checking for verification

– Complexity exponential in the size of the control graph

CTR’s integrates several process modeling paradigms: conditional control flows, data flows, hierarchical modeling, constraints– Complexity polynomial in the size of the control graph and exponential in the size of

the constraints (due to better structuring of the problem)



ConclusionConclusion

Formulated the problems of choreography, contracting, and enactment for semantic Web services using Concurrent Transaction Logic

complex set of constraints

data flow and conditional process controls

extended CTR proof theory

Presented reasoning techniques for

deciding if automatic contracting for a service is possible

finding a choreography that obeys the policy of the service and the user requirements of the contract

enacting the service

Can be extended to multi-party contracts

Possible extensions

more expressive interaction patterns, e.g. loops

subsets of constraints for which the verification problem has a better complexity


reasoning about the behavior of semantic web services with concurrent transaction logic

Documents

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ebusiness technologycenter

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cebtmodeling services

cebtmodeling reasoning

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