SEKE 2012 Proceedings - Knowledge Systems Institute

Towards Autonomic Business Process Models
Karolyne Oliveira, Jaelson Castro
Centro de Informática
Universidade Federal de Pernambuco
Recife, Brazil
{kmao, jbc}@cin.ufpe.br
Abstract - In many organizations business process models (BPM)
play a central role by capturing the way activities are
performed. However, in the dynamic circumstances often
encountered in today's business world, the processes are
becoming increasingly complex and heterogeneous.
Unfortunately, most of the current approaches to BPM are too
inflexible and unresponsive to change. This calls for Autonomic
Business Process (ABP) aimed at self-management and selfadaptation
in dynamic environments. However, a key challenge
is to keep the models understandable and scalable in
increasingly complex scenarios. In our work we rely on the
principle of separation of concerns and modularization in order
to properly represent autonomic features in Business Process
Models. We argue that Communication Analysis can help to
indicate mission-critical activities that must be treated in
autonomic manner. We outline a process that helps to define the
granularity of the Business Process Models, indicating where the
system needs to be instrumented. This novel approach provides
four well-defined levels of abstraction: Communicational Level,
Technological Level, Operational Level and Service Level. A
real example is used to illustrate our proposal.
Keywords - Business Process Modeling; Autonomic Computing;
Self-Adaptation; Communication Analysis
I. INTRODUCTION
Analysts and researchers in Information Technology and
Communication (ITC) management have forecasted an
unavoidable collapse, imposed by the sheer scale and complexity
of the new systems. Hence, complexity and size have driven ITC
management to consider less human-dependent solutions, such
as Autonomic Computing (AC), aimed at developing computer
systems capable of self-management [1].
An autonomic system must know itself, be able to selfconfigure
and recon figure when faced with unforeseen
circumstances. Moreover, it s hould look for optimizations,
to be able to self-heal as well as to self-recover from critical
failures and protect itself. Hence, it must understand the
environment and the context around the activities.
In our work, we are co ncerned about the use of
principles of autonomic computing in the management of
business processes. Our goal is to help organizations to
survive in d ynamics environments. More specifically we
want to face an open challenge which is to promote
Sergio España, Oscar Pastor
Centro de Investigación en Métodos de Producción de
Software
Universitat Politècnica de València
Valencia, Spain
{sergio.espana, opastor}@pros.upv.es
modularization and separation of concerns (SoC) in
Autonomic Business Process Models [2].
The paper proposes a proce ss that exploits the high
variability in service-oriented system environment by the
use of contexts and autonomic adaptations by
operationalizations of Non-Functional Requirements (NFR).
In order to im prove modularity and promote the use of
different levels of abstractions in Autonomic Business
Process we investigate the use of Communication Analysis
Principles. The benefits are manifold and include addressing
scalability problems and improving the understandability of
ABP in complex scenarios [3].
A MAPE cycle (Monitor-Analyze-Plan-Execute), was
utilized considering both as pects: system (self) and t he
instrumented BPM (context).
In order t o illustrate our proposal we describe a real
example which presents mission-critical activities often
managed through BPM.
In the next sections, we present concepts related to this
work, our approach and conclusions respectively.
II. BACKGROUND AND RELATED WORKS
In this section, we introduce self-adaptation and the use
of business process modeling as well some relevant work on
using these models to provide autonomic computing
characteristics to software.
A. Autonomic Computing / Self-Adaptation
Self-adaptive software is expected to fulfill its
requirements at run-time in response to changes. This
objective can be achieved through monitoring the software
system (self) and its environment (context) to detect changes,
make appropriate decisions, and act accordingly. Certain
characteristics, known as self-* properties are expected: (i)
Self-configuration; (ii) Self-healing; (iii) Self-optimizing;
and, (iv) Self-Protecting [4], [5]. Figure 1 shows the
hierarchy of the self-* properties according [6].
Figure 1. Hierarchy of the Self-* Properties, adapted from [6]
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