Specification of Policies for
Web Service Negotiations
Steffen Lamparter and
Sudhir Agarwal
University of Karlsruhe (TH)
Semantic Web and
Policy Workshop
Galway, November 7th
Outline



Motivation
Modeling preferences: Utility theory
Preferences and Policies
–
–


Policy Ontology
Preference Modeling
Conclusion
Open problems / Outlook
SWPW – November 7th, 2005
Motivation
 Web services are highly configurable products
 Attribute value pairs are insufficient to describe offers and requests
WS Provider I
encryption key ≤ 512 bits
response time = 5s
price = 3 Euro
Agent
“I need a service with
encryption key ≥ 128 bits,
response time < 10s and
price < ´5 Euro”
WS Provider II
encryption key = 128 bits
response time = 3s
price = 4 Euro
Automatic selection as well as negotiation requires:
 Preference information within the valid range
 Cardinal preferences to make multi-attributive decisions
SWPW – November 7th, 2005
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
SWPW – November 7th, 2005
Policies vs. Utility Functions


Policies express preferences!
Policies specify the allowed attribute range (e.g.
encryption key < 512 bits)
u(x)
1
128 ≤ encryption key ≤ 512
128
512
-∞

bits
Which attribute value is preferred (e.g. 128 bits or
512 bits)?
u(x)
128 ≤ encryption key ≤ 512
longer keys are preferred
1
128
-∞
SWPW – November 7th, 2005
512
bits
DOLCE-based Policy Framework
DnS:defines
DnS:defines
DnS: defines
Policy Description
-subclassof DnS:Description
-Age of Information
-Information Source
Agent
-subclassof: DnS:Role
Privacy
Policy
DnS:attitude
towards
WS Provider
OoP:Task
-
store
DnS:anakastic
duty towards
Object
-subclassof DnS:Role
Private data
DnS:requisite for
DnS:requisite for
DnS:
defines
DnS:satisfies
DnS:requisite for
Attribute
-subclassof. DnS:Parameter
Storage Duration
DnS:valued by
DnS:setting
Policy Enforcement Situation
-subclassof DnS:Situation
WS Invocation

Situation Value
{7}
Attribute Value
-subclassof Dolce:Region
Policy Value
{1,2,…,14}
DOLCE used as modeling basis
–
Reuse of modules Description and Situation, Ontology of
Plans, Ontology of Information Objects
SWPW – November 7th, 2005
Modeling Utility Information
DnS:defines
DnS:defines
µ
DnS: defines
-subclassof Dolce:Abstract Region
Policy Description
-subclassof DnS:Description
-Age of Information
-Information Source
Agent
-subclassof: DnS:Role
OoP:Task
-
DnS:obliged-to
Object
-subclassof
DnS:Role
R_[0,1]
Policy Value
DnS:anakastic
duty towards
-subclassof Dolce:Region
DnS:requisite for
DnS:requisite for
degree
DnS:requisite
for
Satisfiability
-subclassof OIO:Information Object
Attribute
satisfies
-subclassof. DnS:Parameter
DnS:
defines
DnS:satisfies
pv
DnS:valued bySituation Value
α
DnS:setting
Situation Value
Policy Enforcement Situation
-subclassof DnS:Situation
yl
Policy Value
Attribute Value
-subclassof Dolce:Region
YL
-subclassof OIO:Information Object
pv
yl
YL
Satisfiability
µ
-subclassof OIO:Information Object
-subclassof Dolce:Abstract Region
R_[0,1]
 Adding primitives for utility modeling
-subclassof OIO:Information Object

-subclassof Dolce:Region
degree
SWPW – November 7th, 2005
Modeling Utility Information
u(x)
µ
-subclassof Dolce:Abstract Region

 represents the points (x,y) that form the
utility function


-subclassof Dolce:Region
pv
Change Policy Value to a subclass of 
 restricted to piecewise linear functions

R_[0,1]
Policy Value
Satisfiability defines the degree a Situation
Value satisfies the Policy Value
YL contains an instance for each line in the
function 
SWPW – November 7th, 2005
degree
Satisfiability
-subclassof OIO:Information Object
satisfies
Situation Value
yl
YL
-subclassof OIO:Information Object
α
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


satisfies
yl
yl
µ
u(x)
256
yl
-subclassof Dolce:Abstract Region
1
-subclassof Dolce:Region
128


0
0.33
R_[0,1]
Policy Value
0.33

degree
0
-∞
512
bits
256
pv
degree
Satisfiability
-subclassof OIO:Information Object
satisfies
0.33
Situation Value
yl
P=(satisfies ± degree,  (yl ± ))
SWPW – November 7th, 2005
YL
-subclassof OIO:Information Object
α
Policy Evaluation

Calculation of the overall utility according to
1.
Weighted degree of satisfaction (wds) is calculated by
P*(wds ± degree, satisfies ± degree , ij)

2.
True iff wds ± degree = (satisfies ± degree) * weight holds
wds of attributes are aggregated to the overall utility
P=(degree,  aj ± wds ± degree)

GoodService v Service u 9 >(0.7,degree)
SWPW – November 7th, 2005
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
SWPW – November 7th, 2005
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
SWPW – November 7th, 2005
References

[Baader, Sattler 03] Franz Baader, Ulrike Sattler: Description logics
with aggregates and concrete domains. Information Systems 28(8): 9791004 (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)
SWPW – November 7th, 2005
Thank you!
SWPW – November 7th, 2005