Paper Info
Title
Model-Based Self-Managing Systems Engineering
Abstract
For many years, the vision of smart computing where systems can function and/or manage themselves independently-from human intervention has provided numerous theoretical challenges to research communities ranging from intelligent systems and cybernetics to AI communities. These research trends have now heen further fuelled by the IBM autonomic computing initiative, where biologically inspired concepts inform the development of systems that can adapt autonomously to their users' requirements and environments. This paper considers the extent to which well-established general systems concepts might be valuable in the design of autonomic systems. The main two approaches considered are Checkland's Soft Systems Methodology (SSM) and Beer's Viable Systems Model (VSM). The paper summarizes the relevant aspects of each approach and demonstrates their potential through the provision of an illustrative case study. Moreover, the paper illustrates how SSM and VSM approaches facilitate autonomic systems engineering by the capture of functional and non-functional application requirements such as lifetime self-management policies and operational tolerances.
Year
DOI
Venue
2005
10.1109/DEXA.2005.137
SIXTEENTH INTERNATIONAL WORKSHOP ON DATABASE AND EXPERT SYSTEMS APPLICATIONS, PROCEEDINGS
Keywords
Field
DocType
soft systems meth- odology,autonomic computing,system design,viable systems model.,cybernetics,management system,intelligent systems,soft system methodology,artificial intelligence,software engineering,viable system model,systems analysis
IBM,Autonomic computing,Soft systems methodology,Systems engineering,Intelligent decision support system,Computer science,Viable system model,Systems analysis,Systems design,Cybernetics
Conference
Citations 
PageRank 
References 
8
0.69
6
Authors
5
Name
Order
Citations
PageRank
A. Taleb-Bendiab138348.64
David W. Bustard220333.27
Sterritt, Roy371768.34
A. G. Laws491.40
Frank Keenan56812.89