Abstract
Service engineering of digital service ecosystems can be
associated with several challenges, such as change
and evolution of requirements; gathering of quality
requirements and assessment; and uncertainty caused by
dynamic
nature and unknown deployment environment, composition
and users. Therefore, the complexity and dynamics in
which these digital services are deployed call for
solutions to make them autonomic. Until now there has
been no upto-date review of the scientific literature on
the application of the autonomic computing initiative in
the digital service
ecosystems domain. This article presents a review and
comparison of autonomic computing methods in digital
service
ecosystems from the perspective of service engineering,
i.e., requirements engineering and architecting of
services. The
review is based on systematic queries in four leading
scientific databases and Google Scholar, and it is
organized in
four thematic research areas. A comparison framework has
been defined which can be used as a guide for comparing
the different methods selected. The goal is to discover
which methods are suitable for the service engineering of
digital
service ecosystems with autonomic computing capabilities,
highlight what the shortcomings of the methods are, and
identify which research activities need to be conducted
in order to overcome these shortcomings. The comparison
reveals that none of the existing methods entirely
fulfills the requirements that are defined in the
comparison framework.
Original language | English |
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Pages (from-to) | 1-31 |
Journal | Service Oriented Computing and Applications |
Volume | 11 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2017 |
MoE publication type | A1 Journal article-refereed |
Keywords
- autonomous systems
- digital ecosystems
- service engineering
- self- features
- quality attributes