TOWARDS PREDICTIVE SELF-ADAPTATION IN SOC

A Value-based Perspective

Patrício Alencar and Hans Weigand

Department of Information Management, Tilburg University, P.O.Box 90153, 5000 Le Tilburg, The Netherlands

Keywords: Service Oriented Computing, Self-Adaptation, Value Models.

Abstract: Self-adaptation represents one of the main research challenges in Service Oriented Computing. More

specifically, predictive self-adaptation attempts to anticipate actions for reacting to potential changes in a

system, over time. Nevertheless, the execution of different adaptation strategies on the operational level can

produce an unexpected impact on the organizational level. Predicting this impact, mainly in terms of time

and cost involved in the adaptation, might be useful to enhance the decision-making process in a business

strategic/tactic context. This paper presents some of the challenges in predicting the impact of adaptation

strategies in a service provisioning scenario, from a value-based perspective.

1 INTRODUCTION

The increasing interest in self-* properties

Service Oriented Computing (SOC) has heightened

the need for reconciliation between technology and

methods towards autonomy in service management

(Papazoglou et al., 2007). Of particular interest and

complexity is the self-adaptation of services,

observed from a predictive perspective, which

involves prospecting the impact of future multi-

domain changes on the business strategy level, and

thereby taking decisions to minimize possible

negative return following them. There have been

several investigations into available requirements,

strategies and implementation techniques for self-

adaptation in SOC (Benbernou, 2008).

These aspects rely upon monitoring mechanisms

for change detection. The articulation of adaptation

strategies typically complies with intra and inter-

organizational rules and/or policies (Gordijn et al.,

2008). The scope of these rules can range from the

IT level to the corporate levels, setting the rules of

the game, which constitutes the core of the service

governance process (Marks, 2008).

Although considerable research has been devoted

to service monitoring and adap-tation, rather less

Self-configuration, self-adaptation, self-healing, self-

optimization, self-protecting are commonly referred to

as self-* properties in computer systems in general.

attention has been paid to investigate and measure

the impact of an adaptation strategy (or a

combination of strategies) on the organizational

level. In other words, the service adaptation process

can be followed by a reconfiguration of

organizational stakeholders. Paraphrasing Meadows’

philosophy (Meadows, 1999) and Chaos Theory

(Poincaré, ca. 1900 and Lorenz, 1960), even a small

shift produced by a strategic intervention within a

complex system can produce significant changes in

its whole structure. Conversely, the degree of

freedom of a system is defined by its own rules, and

the power over these rules constitutes the

fundamentals of a governance process. However, if

these rules are somehow flexible, it implies

dynamism in the rearrangement made on the

adaptation strategy level. In this paper we report on

some of the challenges around the specification and

deployment of predictive and self-adaptive services.

These challenges comprise not only technical issues,

such as checking whether the resulting adaptation

complies with technical and corporate rules or not

(Verhoef, 2007), but also attempting to forecast the

profitability produced by a possible selected

strategy. Reduction of the cost and time involved in

the required decision-making process (by

minimizing human intervention) might be

particularly important to react rapidly in highly

dynamic and competitive markets, and thus,

represents the central motivation of this research.

Thus, to cope with this issue, the goal of this re-

429

Alencar P. and Weigand H. (2009).

TOWARDS PREDICTIVE SELF-ADAPTATION IN SOC - A Value-based Perspective.

In Proceedings of the 4th International Conference on Software and Data Technologies, pages 429-436

DOI: 10.5220/0002326204290436

 SciTePress

search is to provide a framework to guide the

decision-making process on the adapta-tion

strategies set, whereby the organizational

stakeholders could be reconfigured, preserving a

value-based perspective goal (i.e. to maximize

profitability for all the organizational actors

involved).

The plan of this paper is outlined as follows. Section

2 presents the considered problem space, by means

of interrelated research questions. In Section 3 it is

proposed a set of candidate approaches and methods

that compose the solution space to be deployed. In

Section 4, it is discussed potential applications of

this work in two case studies. Some related work is

presented in Section 5. Last, Section 6 brings some

discussion and outlook for this research.

2 PROBLEM DEFINITION

The following research questions outline the

problem space in focus. They are decomposed into

sub-problems, enumerated in ascending order of

relevance, according to the purpose of this work.

Research Question 1. What are the adaptation

requirements for multi-supplier IT services?

Assumptions: for the purpose of this study, the term

“adaptation requirements” may be defined as a set of

properties that the adaptive service application

should satisfy (Benbernou, 2007). Besides, “IT

services” are defined as infrastructure services

configured from a business value model perspective

(Gordijn, 2002) (Gordijn et al., 2007).

Problem Decomposition. What are the "change"

patterns in service management? How these changes

are monitored? Which of these change patterns

allow automated solutions? What "action patterns"

follow these change patterns? What policies govern

these action patterns? Which are the most relevant

changes in terms of impact produced (e.g. in terms

of cost and time)?

Potential answers for these questions can be

classified according multiple dimensions, including:

What? (Rules/Policies and Governance);

Where? (Physical and logical layers);

When? (Temporal reasoning);

How? (Causality-effect and correlation analysis);

Who? (System automation or human

intervention)

These same dimensions will also be applied to

classify the outcomes from the next questions.

Research Question 2a. How to monitor a value

constellation and its coordination processes?

Assumptions: a “value constellation” can be

defined as a collection of enterprises that jointly

satisfy complex consumer needs (Gordijn, 2002).

Problem Decomposition. What is the purpose of the

monitoring task? What kind of monitoring

information has to be gathered? How can the

monitoring information be specified? What

implementation methods and techniques are

currently available for monitoring of SOA-based

applications? How can the monitoring information

be integrated?

Research Question 2b. How to adapt a value

constellation and its coordination processes

automatically?

Assumptions: the degree of automation here is

strictly dependent on the outcomes of the research

question 1. It is still not clear to what extent should

we minimize the human intervention in business-

related decision. As soon as new adaptation

problems arise, new solution patterns can be

discovered, mined from human knowledge input in

combination with existing solution patterns.

Problem Decomposition. What rules/policies

govern the adaptation process? What are the

organizational goals behind the rules? How can

these rules be specified? Who defines these rules?

What methods and techniques exist for implementing

self-adaptive services? How can these rules be

specified and configured from a business value

perspective?

Research Question 3. How to coordinate the

reconfiguration of a provisioned IT service bundle

offered by a constellation?

Assumptions: “organizational stakeholders” can

have conflicting or convergent goals, observed from

different perspectives. For instance, in the intra-

organizational level, competitions can represent a

source of emergent behaviour, weakening efforts to

reach a common goal. Conversely, collaborations

might potentially produce the opposite effect. The

same applies for the inter-organizational level,

where different organizations play a win-win game,

in which collaboration and competition are blurred

by high level system goals that include survival,

resilience, differentiation and evolution (Meadows,

1999).

Problem Decomposition. What is the extent and

impact of the adaptation process on organizational

level? How can this impact be measured? Does this

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process require reconfiguration of stakeholders

(design for players or "tactical design") or

reconfiguration of the rules (changing the whole

game or "strategy design")? What theoretical

approaches exist for organizational modelling, and

more specifically for strategy reasoning and

decision-making processes in multi-parties service

provisioning? To what extent are these approaches

currently evaluated? What practical issues and

enabling technologies are required in their

corresponding implementation? How to ensure that

the chosen adaptation strategy/tactic complies with

intra and inter-organizational governance rules?

3 RESEARCH DIRECTIONS

The following research directions outline our

approach to deal with the before mentioned

problems. They include some expected results and

validation techniques.

Solution Direction 1: research question 1 will be

addressed both conceptually and empirically. The

conceptual part will be based on a systematic

literature review on self-adaptive services. The

objective is to identify the most impacting sources of

change as well as its corresponding adaptation

strategies, and which of those allow automated

solutions. Causality, effect, cost, propagation over

the time and correlations can represent some of the

dimensions whereby the impact can be measured.

Qualitative reasoning (QR) can be used to explicitly

model causal dependencies between quantities

(Bredeweg and Struss, 2004). QR also includes the

use of ontologies for expressing and formalizing

relationships between concepts. Ontologies can

easily be adopted as artifacts in the implementation

architecture. This represents a practical advantage

over pure mathematical expressions which, although

may provide more accurate and unambiguous

descriptions of the problem in question, can imply

additional cost, concerning the refinement

operations necessary to map it into the

implementation layer. Regarding technical aspects,

recent work has been done on investigating the use

of the Web Ontology Language (OWL)

on solving

qualitative reasoning problems (Liem, 2005). In

spite of some limitations of expressiveness

(expected to be improved in the upcoming OWL2

specification), a model developed in OWL allows

searching and sharing of knowledge on the Web,

http://www.w3.org/2004/OWL

whereby corporate business intelligence can be

improved.

The empirical part will be performed by quantitative

analysis of data retrieved from the practical

experiences in the case studies and from a survey

sampling.

Expected Result: an ontology of change patterns

and adaptation strategies (in composite services

realizing a value constellation), and a ranking of the

most relevant ones.

Validation: can be achieved by means of

intersection of research methods (in this case, a

combination of surveys, structured interviews, a

systematic literature overview and a proof-of-

concept tool to be applied in the case studies).

Solution Direction 2a/b: research question 2a and

2b will be addressed jointly, considering that service

monitoring and adaptation are closely related.

Ordinarily, these tasks are linked by adaptation rules

or policies that specify what should be done under

which condition. Current research suggests some

kind of Event-Condition- Action (ECA) rules for

specifying these policies (Paschke and Bichler,

2008), but they are typically specified on a rather

low level (i.e., close to the programming code). On

the other hand, recent work has been done on

specifying methods to support business analysts in

designing controls against opportunistic behaviour in

network organizations, from a value-based

perspective. This approach, named e

control

(Kartseva, 2008), can be considered as a starting

point in this study to define high-level rules and

policies for service governance. A possible solution

to connect these two worlds can be an extension of

the referred value-based control approach toward the

ECA rules level, by specifying intermediate layers,

in different abstraction levels and a set of refinement

operations to integrate them. This should make the

rules easier to design, maintain and reuse.

A monitoring strategy should be done in order to

collect external events and information produced in

the service execution environment. Performance

checking, failure reporting and analysis of the

compliance with Service Level Agreements (SLA)

are the outcomes of this task. Several approaches

have been identified for monitoring different

operational layers in service-based applications.

These layers can include monitoring of web services

and service compositions, Business Activity

Monitoring (BAM), Process Mining and Grid

Monitoring (Benbernou, 2008). The monitoring

information collected from these layers must be

integrated to produce a consistent view on the

TOWARDS PREDICTIVE SELF-ADAPTATION IN SOC - A Value-based Perspective

431

overall system performance. To date, proposed

industrial standards in the Web Service Management

area include Web Services Distributed Management

(Wilson and Sedukhin, 2006) and Web Service

Level Agreement (Ludwig et al., 2003). The former

provides some mechanisms to guarantee consistency

of service compositions, and deliver status

notifications when a particular activity is completed

or a decision condition is reached. The latter

provides a description of IT-level and business

process-level parameters (e.g. response time and

throughput), the quality of service agreed to be

delivered by the service provider, besides some

penalties to be applied in case of depreciation or

failure to meet these requirements.

Expected Result: a rule-based system for self-

management of value constellations.

Validation: by means of an experimental prototype.

Solution Direction 3: there are several possible

ways of handling the problems around research

question 3. Methods, models and theories from the

field of organizational modelling have been

proposed to deal with change management in

general. The Management and Business

Encyclopedia

have classified these approaches

along 12 disciplines. For the purpose of this

research, six of them were selected to classify

potential candidates to be considered the solution

space, as follows: Organizational Change,

Communication Aspects, Value-Based Decision-

Making, Intangible Knowledge, Strategy and Supply

Chain Quality. None of the existing approaches

cover all of these aspects. Theoretically, merging

them might result in a more complete solution.

Practically, the high level of complexity involved on

implementing such a combination may represent an

additional problem not subsumed in the scope of this

research. Consequently, one of these theories will be

applied. Approximate matches include: Chaos

Theory (Poincaré, ca. 1900 and Lorenz, 1960),

Game Theory (Nash, 1950), Contingency Theory

(Vroom and Yetton, 1963), Action Learning

(Revans, 1969), Strategy Map, originally referred to

as Balanced Scorecard (Kaplan and Norton, 1992)

and Value Mapping (Jack, 2001).

Expected Result: a formal framework for

reconfiguration of service bundles.

Validation: validation can be achieved by

formalization and proof. Feasibility can be checked

by means of experiments in the case studies.

http://www.12manage.com

4 CASE STUDIES: MUSIC AND

ENERGY INDUSTRIES

It is important to highlight the case studies in which

this research is currently being applied. The

following description includes who they are, their

attributions, future scenarios and particular interest

in this research.

SENA

is an Intellectual Property Rights Society

(IPR), appointed by the Ministry of Justice of the

Netherlands, designated to execute the

Neighbouring Rights Act in the music sector. It

states that formally a user of music must obtain

permission from the right holders (the creators of

music) to play it in public. By virtue of the Copyright

Act and the Neighbouring Rights Act the creators of

music have assigned their right to grant permission

for the use of their music to SENA (performers and

producers) and to Buma/Stemra

(lyricists and

composers).This permission, called a license, is

issued by both organizations on condition that the

user of music pays remuneration for this. The rate

depends on the nature of the use and the space in

which the music is played

Although SENA pricing strategy considers

statistics taken from the 20 biggest radio stations in

the Netherlands, emergent complaints from IPR users

(i.e. cafes, clubs, restaurants, supermarkets etc.) have

revealed that these users are interested in paying only

for the tracks they use (i.e. pay-per-play scenario).

Consequently, a counting and monitoring mechanism

should be deployed in order to charge each IPR user

more accurately.

According to the current SENA requirements, a

new business model was designed. The business

model is based on the e

value methodology

(Gordijn, 2002). It includes the main actors and the

objects of value they exchange to each other. The

main organizational actors in this scenario comprise:

Receivers: they represent the starting point in the

value-object exchange. A receiver is an actor who

wants to satisfy a need (in this case, to broadcast

background music). Thus, since receivers want to use

music to get benefits of it, they are also IPR users.

Background Music Providers: they provide

specialized background music. In this sense, whenever

an actor requires specific background music, a BMP

can exchange background music for a fee.

http://www.sena.nl

http://www.bumastemra.nl

Statement on Music Licenses and Remunerations.

Source: SENA Annual Report 2007 (minor editing).

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Intellectual Property Right Societies: IPR

Societies are entities performing mainly two roles:

collect fees from each played or copied track and

partitioning of these fees to the IPR owners. Thus,

on one hand, whenever a track is played or copied, a

fee must be also paid. This fee is related with the

public use of music (tracks). Thence, if an actor

publically provides music, it has to pay for the right

of providing music (i.e. making profits by exploiting

IPR). The way in which actors get that right is

paying fees to IPR Societies for each played or

copied track. On the other hand, IPR societies

partition fees to the IPR owners according to

collected fees. This partition of fees is based also on

track's features (i.e. who the owners are and how

many times the track was played or copied).

Right Owners: they constitute the set of actors

who perform a specific track. In this sense,

“performing” is not only related to playing tracks, but

also encompasses tasks like writing lyrics, producing

and publishing a track.

Once described the main actors and their roles, the

interaction between them can be specified. As

mentioned before, the receivers constitute the starting

point, as they request for broadcasting background

music which is provided by the background music

providers. This relationship is summarized as follows:

a receiver gives a fee to a BMP and gets in return

background music.

A BMP could provide background music in two

ways: by delivering hard copies or a stream of

tracks. In this sense, hard copies can be considered

as physical devices in which the receivers store

tracks provided by the BMPs, whereas a stream is a

flow of tracks that the BMP delivers to the receivers

using internet-based technology. Thus, the main

difference between these two ways of providing

music is either allowing storing tracks at the

receivers’ side or not.

This main difference has generated two similar value

models. If the BMP delivers hard copies, it must pay to

IPR Societies which collect fees about replicating music,

thus making copies of tracks. On the other hand, when

providing streams, the BMP must pay to IPR Societies

which collect fees related with making a stream available

to the public (Figure 1).

Receivers have to pay also IPR Societies for

providing music to the public. Thence, they pay mainly

two distinct IPR Societies (although it does not mean

they pay twice). Paying BUMA/Stemra is about the

hold, whereas paying SENA is related to the rights of

the performing artists and producers. All the process

described above is associated to collecting fees.

Therefore the next step is to partition all those fees. As

it can be observed in Fig. 1, the IPR societies partition

fees to a set of right owners. This set of right owners is

composed mainly by artists, producers, music

publishers, composers and lyricists. However, there is a

clear division about who partition fees to whom. Again,

SENA only partitions fees between artists and

producers, whereas BUMA/Stemra does the same for

publishers, composers and lyricists.

Finally, since receivers’ claim is about pay-per-

play, both models (the model for hard copies is

similar to the model depicted in Fig. 1) introduce a

new activity that must be performed to allow pay-per-

play service. This new activity is about logging each

track the receivers play. Consequently, to have access

to the pay-per-play scheme, receivers must provide a

log with the tracks they had already played.

Regarding the trust aspect, security mechanisms will

be further specified.

From a technical perspective, if the Key

Performance Indicators (KPIs) in the provisioning of

streaming audio drop below the Key Quality

Indicators required by the receiver (e.g. availability,

audio quality and response time), some service

adaptation should be done in order to optimize the

overall network performance (Toktar et al., 2007),

(Dalal et al., 2007).

From a business perspective, the music industry has

been dramatically changed as far as new technologies

for use and distribution of digital music scatter

throughout the Internet. New digital music

retailers/providers have to play a wild game to adapt

themselves to this new market and offer value-added

services for distribution of digital music. Therefore,

new business and technology strategies become

essential for the sake of profitability whereby survival

in this wild game might be guaranteed. It is crucial the

enforcement of Intellectual Properties restrictions, and

to promulgate effective copyrights and licensing for

music distribution, and organizations involved in this

initiative must consider new technologies and

strategies for monitoring piracy (Bockstedt,

Kauffman and Riggins, 2006).

The second case study is ECN

(Energy Research

Centre of Netherlands). This organization develops

knowledge and technology for a sustainable energy

system and transfers it to the market, which

costumers include the Dutch government, European

Union and industry (national and international).

ECN envisions a scenario when the houses of the

future will not only be energy-neutral, they will

generate energy which can be used elsewhere

http://www.ecn.nl

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433

Figure 1: Value model for the Music Industry: the stream value exchanging case.

effectively, through the efficient exchange of

electricity and heat. This will require intelligent and

self-managing electricity grids

. It means bringing

the electricity service to a market with new small

players (e.g. households and small scale generators).

This requires a portfolio of such households and

generators that could be easily reconfigured, not

only in terms of balancing services, but also

supporting services (e.g. communication, processing

power services, etc.), besides prediction over the

results from the profitability analysis of this new

scenario. The design of a new business model for

this scenario is part of future steps of this research.

5 RELATED WORK

The four pillars sustaining this research are: service

monitoring, service adaptation, organizational

modelling and governance (IT, SOA and Corporate).

Several approaches have been identified for

monitoring of service-based systems (Benbernou,

2008). They encompass basically mechanisms for

Monitoring Web Services and Service

Constructing a Sustainable Future. ECN Annual Report

2007 (minor editing).

Compositions, Business Activity Monitoring

(BAM), Process Mining and Grid Monitoring. It

would seem, nevertheless, that further investigations

are needed so as to integrate available

methodologies and technologies across all the

service-based application layers. WSDM (Wilson

and Sedukhin, 2006) and WSLA (Ludwig et al.,

2003) represent some of the recent standards

proposed to fulfil technical needs for the integration

of the monitoring information.

Regarding the adaptation process, among several

research directions, some approaches have

emphasized the provisioning of correctness criteria

to check system integrity after an adaptation strategy

is executed, from a technical perspective (Weigand,

van-den Heuvel and Hiel, 2008). In the opposite

way, adaptation in the business collaborations has

also been addressed (Orriëns, 2008). Still, cross-

layer dependencies of adaptation strategies remain

as open issues.

Concerning the before mentioned organizational

modelling theories, recent work has focused on

implementing them in service-based scenarios. The

following initiatives comprehend some of them:

enterprise strategy management using chaos theory

(Levy, 1994), (Hao et al., 2008), (Zhao and Li,

2005), application of game theory in business

process reengineering (Zhang et al., 2008), (Li,

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434

Chen, and Cui, 2008), contingency theory in IT

strategy plans (Lee, Miranda and Kim, 2004),

(Croteau and Raymond, 2004), modelling of virtual

communities under the perspective of action

learning (Parenthöen, Buche and Tisseau, 2008), (de

Moor and Weigand, 2007), and the inclusion of the

stakeholder value perspective in the configuration of

strategic business initiatives, using strategic maps

(Sahu, 2004), (Chien-Chih, 2007) and value

mapping (Moore, 2008). Nonetheless, their scope is

still restricted to distinct abstraction layers, stressing

the need for an integrated approach.

Last, recent contributions have been acknowledged

in the field of service governance. They range from

value-based controlling mechanisms over

organizational networks (Kartseva, 2008) to

quantification analysis of governance rules in the IT

level (Verhoef, 2007). Challenges in this area include

the development of a unified model for SOA policies

that could integrate business process, technology,

design, and runtime policies. Such a model could be

implemented as governance collaboration tools to

explore collective intelligence.

In short, these four pillars still lack a common

ground of integration and interoperability, which

sets the perspective orienting this research.

6 CONCLUSIONS

The purpose of this paper was to identify some of

the gaps in self-adaptive services research. Its

outcome comprised our research design and

proposal, hereafter focused on investigating the

impact of service adaptation strategies on the

organizational level, where the crucial decisions are

carefully analyzed. The urgent need for solution

alternatives to be applied in real world applications

(e.g. the Music Industry and the Energy

Management Sector), reinforces the motivation for

realizing this research.

This work in on its early stage and the prototype

to be produced for addressing the first research

question is currently under development. Future

steps include combining ontology engineering and

qualitative reasoning techniques to specify and

analyze causality/effect and correlations between

change and adaptation patterns in service bundling.

These patterns are currently being catalogued and

will be contrasted with empirical data extracted from

the case studies.

ACKNOWLEDGEMENTS

This work is supported by the Value-IT Project,

funded by the Joint Academic and Commercial

Quality Research & Development (JACQUARD),

part of the Netherlands Organization for Scientific

Research (NWO).

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