TY - JOUR
T1 - A survey of autonomic computing methods in digital service ecosystems
AU - Abeywickrama, Dhaminda B.
AU - Ovaska, Eila
N1 - Funding Information:
This work was carried out during the tenure of an ERCIM "Alain Bensoussan" Fellowship Programme. This research has also been supported by a grant from Tekes?the Finnish funding agency for technology and innovation, and VTT as part of the Digital Health Revolution Programme.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - autonomous systems
KW - digital ecosystems
KW - service engineering
KW - self- features
KW - quality attributes
UR - http://www.scopus.com/inward/record.url?scp=84997638332&partnerID=8YFLogxK
U2 - 10.1007/s11761-016-0203-8
DO - 10.1007/s11761-016-0203-8
M3 - Article
VL - 11
SP - 1
EP - 31
JO - Service Oriented Computing and Applications
JF - Service Oriented Computing and Applications
SN - 1863-2386
IS - 1
ER -