QoS-Oriented Service Computing - Advanced Design Approaches to Emerging Software Systems - page 276

is business-oriented, it has also been proved to
be an effective approach that can be employed in
e-Science to develop modern cyberinfrastructure
to facilitate the scientific research and discovery.
More recently, the emergence of Cloud com-
puting has brought new dimensions of applying
IT and computing technologies to businesses
and scientific research, which results in a new
computing paradigm, where service provider
dose not have to own any physical infrastructure
but instead outsource to dedicated infrastructure
providers. This computing paradigm can provide
a scalable IT infrastructure, QoS-assured services
and customizable computing environment. How-
ever, the current service computing technologies
can not always meet the requirements of this
computing paradigm, and there are several issues
arose: (i) QoS-assured service delivery: while re-
lationship between customer and service provider
is inherently a “Customer - Service Provider”
relationship, the service provider and infrastruc-
ture provider have also established a “Customer
- Service Provider” relationship. As in this model
the service provider faces both customer side
and infrastructure provider side, the guarantee
of the delivery of QoS-assured service becomes
increasingly critical. (ii) Green service. How to
provide QoS assured service to serve customers
with minimized resource consumption cost and
meet customer's satisfaction, while also to guar-
antee the maximization of the business objectives
(e.g. margin profit) to service provider and infra-
structure provider within certain constraints. (iii)
Service discovery: One service can have several
service providers with different service prices.
Even the same service provider can provide a
service with different Service Level Objectives
(SLO) which incurs different cost. How custom-
ers can find appropriate services they want. (iv)
Service metering, which plays a fundamental role
in service computing as QoS-assured service and
green service all require metered services to be
delivered. This involves creating a generic metric
model which can be used in different service occa-

sions. (v) On-demand resource provisioning. How
to elastically provision resources on-demand?
Currently, service computing / service engi-
neering mainly concerns about the service mod-
eling, creation, deployment and service quality
assessment during its lifecycle, known as Method-
ology of Service Engineering (MSE). For example,
the discipline of service engineering, which was
first proposed in the mid 90's in Germany and
Israel (Bullinger, 2003; Mandelbaum, 1998),
is concerned with the systematic development
of services using suitable models, methods and
tools. Service engineering promotes an integrated
service by adopting technological methods and
employing existing engineering know-how to
maximize efficiency (Tomiyama, 2001; Bullinger
et al., 2003). Product service co-design and service
modeling claim that traditional engineering meth-
ods and tools in applied science can be borrowed
for service design and development (Ganz et al.,
2004). Service CAD argues that computer-based
tools can be used to design services, just as CAD
can be used to facilitate the design of products and
simulation of their behaviors under various cir-
cumstances (Tomiyama, 2003). The driver for the
emergence of New Service Development (NSD)
is that the product development paradigm fails
to address the unique characteristics inherent in
services, such as customers as a participant in the
service process, intangibility, and heterogeneity
of customer demand (Fitzsimmons et al., 2000).
Life cycle oriented service design (Aurich et al.,
2004) argued that Life Cycle Engineering (LCE)
(Jeswiet, 2003) can be adopted for the design of
service.
However, these static service computing tech-
nologies mainly concern the modeling, creation
and deployment of separate services. They can
not well resolve issues occurring at the stage of
service discovery, service outsourcing, and service
usage. In order to address these issues in service
computing, we proposed “QoS-oriented Service
Computing” to accommodate needs for service
computing in the context of Cloud environment.