Specification of Policies for Web Service Negotiations Steffen Lamparter and Sudhir Agarwal Semantic...

Specification of Policies for Web Service Negotiations

Steffen Lamparter and Sudhir Agarwal

Semantic Web and Policy WorkshopGalway, November 7th

University of Karlsruhe (TH)

SWPW – November 7th, 2005

Outline

Motivation Modeling preferences: Utility theory Preferences and Policies

– Policy Ontology– Preference Modeling

Conclusion Open problems / Outlook


Motivation

“I need a service with encryption key ≥ 128 bits, response time < 10s andprice < ´5 Euro”

encryption key ≤ 512 bits response time = 5sprice = 3 Euro

Web services are highly configurable products

Attribute value pairs are insufficient to describe offers and requests

Agent

WS Provider I

encryption key = 128 bits response time = 3sprice = 4 Euro WS Provider II

Automatic selection as well as negotiation requires: Preference information within the valid range Cardinal preferences to make multi-attributive decisions


Representing Preferences

Multi-attribute utility theory – Scoring function maps attribute values to a numerical measure– This measure is comparable and can be aggregated

Classical optimization algorithms can be used

Allows realizing trade-offs (good & expensive vs. bad & cheap)

– Allows weighting of attributes– Allows aggregation and weighting of preference functions for

one attribute


Policies vs. Utility Functions

Policies express preferences! Policies specify the allowed attribute range (e.g.

encryption key < 512 bits)

Which attribute value is preferred (e.g. 128 bits or 512 bits)? u(x)

bits

1

128 512

-∞

128 ≤ encryption key ≤ 512longer keys are preferred

128 ≤ encryption key ≤ 512

u(x)

bits

1

128 512

-∞


DOLCE-based Policy Framework

-subclassof DnS:Description-Age of Information-Information Source

Policy Description

-

OoP:Task

-subclassof. DnS:Parameter

Attribute

-subclassof DnS:Role

Object

-subclassof: DnS:Role

Agent DnS:attitudetowards

DnS:requisite for

DnS:anakasticduty towards

DnS:definesDnS: defines

DnS:defines

DnS:defines

DnS:valued by

Policy Value

DnS:requisite forDnS:requisite for

-subclassof DnS:Situation

Policy Enforcement Situation

DnS:satisfies

DnS:setting

Situation Value

-subclassof Dolce:Region

Attribute Value

DOLCE used as modeling basis– Reuse of modules Description and Situation, Ontology of Plans,

Ontology of Information Objects

Privacy Policy WS Provider store Private data

Storage Duration

{1,2,…,14}{7}WS Invocation


-subclassof OIO:Information Object

Satisfiability

Policy Value

Situation Value


YL

-subclassof Dolce:Abstract Region

µ


R_[0,1]

yl

degreepv

satisfiesα

-subclassof DnS:Description-Age of Information-Information Source

Policy Description

-

OoP:Task

-subclassof. DnS:Parameter

Attribute

-subclassof DnS:Role

Object

-subclassof: DnS:Role

AgentDnS:obliged-to

DnS:requisite for

DnS:anakasticduty towards

DnS:definesDnS: defines

DnS:defines

DnS:defines

DnS:valued by

Policy Value

DnS:requisite forDnS:requisite for

-subclassof DnS:Situation

Policy Enforcement Situation

DnS:satisfies

DnS:setting

Situation Value


Attribute Value

Modeling Utility Information

Adding primitives for utility modeling degree


µ


R_[0,1]


Satisfiability


YL

yl

pv

Situation Value Policy Value


Modeling Utility Information

represents the points (x,y) that form the utility function

Change Policy Value to a subclass of restricted to piecewise linear functions

Satisfiability defines the degree a Situation Value satisfies the Policy Value

YL contains an instance for each line in the function


Satisfiability

Policy Value

Situation Value


YL


µ


R_[0,1]

yl

degreepv

satisfiesα

u(x)


Policy Evaluation

Aggregation functions such as SUM, MIN, MAX, etc. are required Ontology formalism ALC() [Baader,Sattler 03]

Deriving utility for a concrete Situation Value

P=(satisfies ± degree, yl ±

u(x)

bits

1

128 512

-∞ 256

0.33

satisfies

degree

0.33

256

yl yl yl

0 00.33


Satisfiability

Policy Value

Situation Value


YL


µ


R_[0,1]

yl

degreepv

satisfiesα


Policy Evaluation

Calculation of the overall utility according to

1. Weighted degree of satisfaction (wds) is calculated by

P*(wds ± degree, satisfies ± degree , ij)

True iff wds ± degree = (satisfies ± degree) * weight holds

2. wds of attributes are aggregated to the overall utility

P=(degree, aj ± wds ± degree)

GoodService v Service u 9 >(0.7,degree)


Conclusion

Bringing together two powerful paradigms: Policy-based computing and utility theory Enables automated selection of services and negotiation of

service parameters

Preference information is modeled using DL Facilitates interoperability in open and heterogeneous

environments Reuse of existing DL-reasoners Preference information can be used within the reasoning

process


Open Problems / Outlook

Checking for satisfiability and subsumption in ALC()

may lead to undecidability [Baader,Sattler 03]

Specifying policies gets even harder…– Approximate preferences from existing policies

[Lamparter et. al. 05]

– There are 30 years of work in the field of decision analysis and

preference elicitation [Keeney, Raiffa 76]

Support policy specification by reusing of existing preference

elicitation techniques


References

[Baader, Sattler 03] Franz Baader, Ulrike Sattler: Description logics with aggregates and concrete domains. Information Systems 28(8): 979-1004 (2003)

[Keeney, Raiffa 76] Keeney, R.L. & Raiffa, H.Decisions with Multiple Objectives: Preferences and Value Tradeoffs. J. Wiley, New York, 1976

[Lamparter et. al. 05] Lamparter, S., Eberhart, A., Oberle, D.: Approximating service utility from policies and value function patterns. In: 6th IEEE Int. Workshop on Policies for Distributed Systems and Networks, IEEE Computer Society (2005)


Thank you!

Specification of Policies for Web Service Negotiations Steffen Lamparter and Sudhir Agarwal Semantic...

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