structured occurrence network for provenance: talk for ipaw12 paper

Modelling provenance usingStructured Occurrence Networks

Paolo Missier, Brian Randell, Maciej KoutnyNewcastle University, UK

IPAW’12Santa Barbara, CA, June 2012

Thursday, June 21, 2012

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Petri Nets and Occurrence Nets

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Historically, Occurrence Nets have been used to define process semantics of Petri Nets [2]

[2] Best, Eike, and Raymond Devillers. “Sequential and concurrent behaviour in Petri net theory.” Theoretical Computer Science 55, no. 1 (1987): 87-136. http://www.sciencedirect.com/science/article/pii/0304397587900909.


http://www.sciencedirect.com/science/article/pii/0304397587900909

http://www.sciencedirect.com/science/article/pii/0304397587900909

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Occurrence Nets

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ON = (C, E, F ) with nodes C E and a flow relation F ⊆ (C ×E)∪(E × C) satisfying the following:(i) for every condition c there is at most one event e such that (e,c) ∈ F, and at most one event f such that (c,f) ∈ F; (ii) for every event e there is at least one condition c such that (c, e) ∈ F , and at least one condition d such that (e,

d) ∈ F ; (iii) ON forms an acyclic graph and F + is a partial order relation (the relation PrecON = (F ◦ F)|C×C is acyclic)

ON is about capturing causal relationships between events and conditions


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Provenance and Occurrence Nets

• "Provenance is defined as a record that describes the people, institutions, entities, and activities involved in producing, influencing, or delivering a piece of data or a thing." [PROV]

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• An Occurrence Net is an abstract record of a single execution of some computing system• Only information about causality and

concurrency between events and visited local states is represented


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Data: The evolution of variable A as a ON:


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Data: The evolution of variable A as a ON:

Agents: The evolution of Bob, the document editor:

readpaper

p1

performed exp.

readpaper

p2

verifiedresults

draftedinternalmemo

ready to

draftptd


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From ON to Structured ONON is an adequate starting point, but extensions are needed to represent the activity of complex systems

• Structured Occurrence Nets provide these extensions as new relationships amongst multiple ONs [2]

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[2] Koutny, M., and B Randell. “Structured Occurrence Nets: A Formalism for Aiding System Failure Prevention and Analysis Techniques.” Fundamenta Informaticae 97 (2009).


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Provenance modelling patterns using SON

• Data is viewed as an evolving system

• Agents are also evolving systems, thus their evolution is also captured

• Uniform representation of Agents / Activity / Data interplay

• Representation of multi-layered Provenance– eg:the provenance of a workflow run is underpinned by system-level provenance– SONs are suitable for modelling at multiple levels of abstraction

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Main goal of this work:to explore the use of Structured Occurrence Nets

as a formal model of provenance

Expected by-product of the investigation:suggest enhancements to the current SON model


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Talk outline• C-SON: ON + communication relation

– a provenance pattern to represent workflow patterns

• T-SON: C-SON + temporal abstraction

• (more abstraction relations omitted in the talk)

• Modelling multi-layered provenance

• Agents as evolving systems

– provenance of agents

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Communication SONs

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• Goal: to capture communication between ONs that otherwise proceed concurrently

• by introducing a Communication relation amongst activities in two ONs– induces a partial order on the states and conditions of the two nets– must result in an acyclic net

e1 cannot have happened after f1

e2, f2 must have happened simultaneously


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C-SON at work - a first provenance pattern

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• Each ON models one variable as a system.

• The composed activity “A:=A+1; A:=A+B; B:=A+B” is represented as a SON composed of a pair of communicating ONs

• The resulting SON captures a (partial) order of possible reads and writes leading to the final result


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Workflow execution traces using C-SON

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f

X

r10 10 r 10

g

Y

w 200 r 200

w 20

Z

w 20

Y:= f(X)

<X,Z> := g(X,Y)

(a)Program

specification

(c)SON representation of

Execution trace

f()

Z = "20"

g()

X= 10

X = 20

Y = "200"

(b)Executioninstance

Program execution


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Temporal SON (T-SON)• Goal: to replace part of an ON with new “atomic” actions

– a form of temporal abstraction– these new actions only appear atomic at one level of abstraction

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T-SON in action: multi-layered provenance • Provenance of computed data naturally comes in layers:

– program execution (incl. workflow controller)• system-level primitives, network protocols

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Program execution

X

r10 10

fX

r10 10

fetch 1010 send

ttt

Program execution

f

get compute

ttt

Temporal abstraction used to hide/reveal lower-level details of both systems and their interaction (i.e., reading from storage)


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T-SON: multi-layered provenance

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Program execution

X

r10 10

f

Serviceexecution

Additional unfolding:- assume f is a service call- reveal details of communication with an underlying service implementation


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T-SON: multi-layered provenance

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msgreceive

msgsend

X

r10 10

fetch 1010 send

ttt

Program execution

f

get msgprep

ttt

msgsend receive

Serviceexecution


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Agents as evolving systems

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Alice and Bob collaborate on document editing

An agent performs activities that account for changes in the state of the data• F is data (a file)• Data and agents are modelled as systems

• Each system is a SON• Communication abstraction used to synchronize events across different systems

• Bob.draft → F.write, F.read → Alice.”read draft” etc.• For example, Bob in the state b2 is unaware of Alice’s feedback• Bob in state b3 has read Alice’s feedback


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Agents as evolving systems• Tracking the state of agents is important

– we know that it is the “version” of Bob that is aware of Alice’s comment that is responsible for the latest edit

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Below: Bob’s edits to the document do not take account of Alice’s comments

F

w f1

draftptd b2

Bob

r f1 w f2 r f2 w f3

edit b4

Alice

readdraft a2a1 leave

comments


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Summary• SONs extend well-known Occurrence Nets

• Simple graphical notation with formal grounding– amenable to various types of analysis

• Appealing for capturing system evolution and inter-system communication

• Accommodates multiple levels of abstraction

• Evolution traces of Data, Agents and Activities provenance queried seamlessly

• Some software tool support (in progress), more work needed here

• Feedback for customizations of the SON model itself!

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18 Martinique, Jan. 2012

Selected References •  V. Khomenko, M. Koutny, A. Yakovlev: Logic Synthesis for Asynchronous

Circuits Based on Petri Net Unfoldings and Incremental SAT. Fundamenta Informaticae 70, 2006.

•  http://www.cs.ncl.ac.uk/publications/inproceedings/papers/749.pdf •  M. Koutny, B. Randell: Structured Occurrence Nets: A Formalism for

Aiding System Failure Prevention and Analysis Techniques. Fundamenta Informaticae 97, 2009.

•  http://www.cs.ncl.ac.uk/publications/trs/papers/1162.pdf •  B. Li, M. Koutny: Verification and Simulation Tool for Communication Structured

Occurrence Nets. CS-TR, Newcastle University, (to appear). •  P.M. Merlin and B. Randell: State Restoration in Distributed Systems. Proc.

FTCS-8, 1978. •  http://www.cs.ncl.ac.uk/publications/inproceedings/papers/347.pdf

•  I. Poliakov, V. Khomenko, A. Yakovlev: Workcraft - A Framework for Interpreted Graph Models. LNCS 5606, 2009.

•  B. Randell, M. Koutny: Failures: Their Definition, Modelling and Analysis. LNCS 4711, 2007.

•  http://www.cs.ncl.ac.uk/publications/trs/papers/994.pdf •  B. Randell, M. Koutny: Structured Occurrence Nets: Incomplete,

Contradictory and Uncertain Failure Evidence. CS-TR 1170, Newcastle University, 2009.

•  http://www.cs.ncl.ac.uk/publications/trs/papers/1170.pdf

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EXTRA material

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SON provenance and PROV

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b2

Bob

f2 r f2 w f3

readfeedback editb3 b4

F

edit f3

Bob_b3

wasGeneratedBy

wasAssociatedWith

f2used

readfeedback

wasGeneratedBy

used

Bob_b2

wasAssociatedWithwasDerivedFrom

r f2

Bob_b4wasDerivedFrom

wasGeneratedBy

(a)

(b)


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T-SON and finite-duration activities

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s e

f

t t t t ttt

[s,e]

duration interval of f

t1 t2 tn

Time

Activity fwith duration [s,e]

c c

In Occurrence Nets, events (activities) are instantaneous.Using temporal abstraction one can add a time duration to activities


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SON -- behavioural abstraction

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• Insight: ‘system’ and ‘state’ are not separate concepts

• The same graph node may be used to represent either a state or a system, at different levels of abstraction

Key idea of Structured Occurrence Nets:

• multiple ONs, each portraying a system/state at some level of abstraction

• associations amongst the ONs are then established by means of new relation types


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B-abstraction in use

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– An application of behavioural abstraction -- state/system duality– Bob’s state b1 expands into a system’s activities (b1)– the expansion provides additional insight into Bob’s “knowledge level” /

“preparedness” prior to drafting the document

Bob’s state as a system


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Finding good abstractions - cuts in ON and SON

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(a)

(b)

(c)

(d)

(e)


structured occurrence network for provenance: talk for ipaw12 paper

Technology

occurrence nets provenance

modelling provenance

provenance pattern

occurrence netson

relation f c ee c

provenance modelling

condition c

acyclic ipaw