On Automated Generation of Web Service Level ... - Semantic Scholar

June, 13th, 2007

On Automated Generation of Web Service Level Agreement Cinzia Cappiello, Marco Comuzzi, Pierluigi Plebani Dipartimento di Elettronica ed Informazione Politecnico di Milano [cappiello, comuzzi, plebani]@elet.polimi.it

So far

2

• Web services adoption is increasing in several environments:  Customer applications  Business applications  B2B applications …

• Most of the interest is focused on the functionalities  What the Web service does

• We need more attention on quality of Web services  How well the Web service works

On Automated Generation of Web SLA

Web Service Level Agreement (SLA)

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• Before invoking a Web service  service providers must be sure that it will get paid by their users  service user must be sure that the invocation will go well

• They need a Service Level Agreements (SLA) we call Web SLA  Defining the quality  Defining the price

• Web SLA is a part of the contract which also includes  Responsibilities  Penalties …

• Web service could establish short-term partnerships, so the Web SLA definition  should be done automatically  should take as less time as possible

On Automated Generation of Web SLA

Goals of the work

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• Quality of service model able to express  Capabilities (provider perspective)  Requirements (user perspective)

• Negotiation model able to automatically generate Web SLA where the quality  Can be supported by the provider  Satisfies the user requirements  Maximizes both user and provider expectations

On Automated Generation of Web SLA

Web SLA Generation

5

User

Provider

defines

Requirements + budget

defines

Matching

Negotiation

Web SLA On Automated Generation of Web SLA

Capabilities

Web SLA Generation

6

User

Provider

defines

Requirements + budget

defines

Matching

Negotiation

Web SLA On Automated Generation of Web SLA

Capabilities

Quality dimension

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• Quality dimension is the building block for defining both requirements and capabilities qdi= < availability, [0..1], sigmoid, {[0..0.3),[0.3..0.5), [0.5..0.6)[0.6..0.7)[0.7,1]} >

eavailability 1 0.8 0.6 0.4 0.2

0

On Automated Generation of Web SLA

0.3 0.5 0.6 0.7

1

Community

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• Quality of Web service is defined by quality dimensions, but:  Quality is subjective: relevant dimensions for providers should be not the same for the users  Comparison requires an objective definition: we can compare capabilities and requirements expressed in the same way

• We need a model for expressing quality of Web service mediating between:  subjectiveness of quality required for definition  objectiveness of quality required for comparison

• We introduce the community as a sort of implicit (sometimes explicit) mediator

On Automated Generation of Web SLA

Quality model User classes

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create

Community

select

defines read

User defines

Require_ ments

On Automated Generation of Web SLA

Quality dimensions

read

Provider defines

Capabilities

Running example

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• Traffic Monitoring Web service • It provides up-to-date information about local traffic across US • Two kinds of quality dimensions:  Technical: availability, response time, encryption  Domain dependent: covered area, routes set, detail level

On Automated Generation of Web SLA

Traffic Monitoring quality dimensions

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eavailability 1 0.8 0.6 0.4 0.2

0

0.3 0.5 0.6 0.7

1

edata_encryption

ecovered_area 1

1

0.66 0.33

AES-128 AES-192 AES-256

On Automated Generation of Web SLA

NE

NW

SE

SW

Expressing capabilities

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qd

offering

price

Availability

[0.5..1.0]

30$+(availability*5$)

Data Encryption

[AES-128; AES-192;AES-256]

500$

Response time

[1..2]

3$*(5$/responsetime)

Covered area

[NE; NW]

5$-NE;3$-NW

Route set

[interstate;local]

5$-interstate;10$-local

Detail level

[detours]

10$

On Automated Generation of Web SLA

Expressing requirements qd

request

13

w

Availability

[0.5..1.0]

0.4

Data Encryption

[AES-192; AES-256]

0.025

Response time

[0.5,1]

0.3

Covered area

[SE; NE]

0.1

Route set

[highways;local]

0.15

Detail level

[jams;detours]

0.025

On Automated Generation of Web SLA

• Weights express the importance of a dimension for a user • Weights are usually defined by the community and are included in the user class definition • Weight assignment is driven by AHP

Web SLA Generation

14

User

Provider

defines

Requirements + budget

defines

Matching

Negotiation

Web SLA On Automated Generation of Web SLA

Capabilities

Matching requirements and capabilities

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edata_encryption

eavailability

1

1 0.8

0.66

0.6 0.4

0.33

0.2

0

0.3 0.5 0.6 0.7

1

ISec=[0.5,1.0]

AES-128 AES-192 AES-256

ISec=[AES-192;AES-256]

• Considering, for each quality dimension, a primitive classes we can define several service levels  availability(0.5,0.6), data_encryption(AES-192)  availability(0.5,0.6), data_encryption(AES-256) … On Automated Generation of Web SLA

Web SLA Generation

16

User

Provider

defines

Requirements + budget

defines

Matching

Negotiation

Web SLA On Automated Generation of Web SLA

Capabilities

Negotiation model 1/2

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• Negotiation process aims at identifying the maximum quality level admissible with respect to the user budget • Negotiation will occur at run-time and automatically • User perspective:  Goal: obtaining the maximum quality with a fixed amount of money  Role: figuring out which is the best service level

• Provider perspective:  Goal: guaranteeing the quality level chosen by the user  Role: expressing the offer configuration

On Automated Generation of Web SLA

Negotiation model 2/2

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• Automatic negotiation is defined by three elements: • Negotiation protocol  Offer configuration: the requestor asks the provider to improve the quality of the service

• Participants decision model. Two approaches:  Vertical strategy  Horizontal strategy

• Negotiation objects  Negotiation can be done on quality dimensions where the evaluation function defines an order between values

On Automated Generation of Web SLA

Negotiation protocol

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• Defining the Basic Service Level (SLbase)  The service level obtaining selecting the primitive classes with lowest quality  e.g., availability(0.5,0.6), data_encr(AES-192), …

• Calculating the price  P(SLbase) = price(availability(0.5,0.6) + data_encr(AES-192))

• Adding the price for non-negotiable quality dimensions  Pnn= price(covered_area)

• Verifies the sustainability calculating the Extra Budget  EB = B - [ P(SLbase) + Pnn ]

• EB < 0 user cannot afford the Web service • EB = 0 SLbase is the Web SLA! • EB > 0 user can try to find something better On Automated Generation of Web SLA

Participants decision model

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• In case of EB > 0 we need to try with a SL with higher quality • Vertical strategy:  Improves the quality of the most important dimension as long as is possible with respect to the budget  Once the maximum quality is reached and part of budget remains then we consider the second highest important dimension

• Horizontal strategy  Slightly improves the quality of the most important dimension considering the next primitive class  If part of budget remains than we slightly improve the second highest important dimension  Objective: splitting EB proportionally to priorities On Automated Generation of Web SLA

Web SLA

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• Continuously iterating the either vertical or horizontal strategy as long as EB > 0 we improve the SL • At the end, the SLA will be the SL which maximize the exploitation of EB, so: • Web SLA will be defined by  Set of quality dimensions  For each negotiable dimension the range of values which must be valid during the invocation obtained after the negotiation  For each non-negotiable dimension the range of values which must be valid during the invocation obtained after the matching  The total price

On Automated Generation of Web SLA

Related work

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• QML, WSOL have inspired our framework for expressing quality of service • WS-Policy can be adopted as an XML language for expressing our documents (dimensions, capabilities, requirements) • WS-Agreement is quite close to our approach but the negotiation is not considered

On Automated Generation of Web SLA

Conclusions & future work

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• We have proposed a framework for on-the-fly generation of SLA based on • In detail, we have introduced:  Quality model  Negotiation model

• We are going to extend  The quality model considering dependencies among quality dimensions  The negotiation model considering a multi-party negotiation

On Automated Generation of Web SLA