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monitoring data could predict the likely breach
of contract in future. For example, if QoS data is
showing a trend that the service is overloading
(which might be due to growing data set sizes, or
increasing numbers of concurrent users, or other
factors) then at some point the service will no
longer meet the criteria specified within the SLA.
In order to ensure the compliance with agreed QoS
constraints, the capacity management is charged to
ensure that additional capacity is added in advance
(additional CPUs, more memory, new database
indexing) so that the trend lines are reset and the
service will remain within the specified perfor-
mance range. In other words, if the provisioning
resource can not guarantee the QoS of a service,
the resource should automatically scale. More
will be discussed in next section “On-demand
Resource Provisioning”.
large numbers of users may participate in a single
instance, and are typically able to join or leave at
any time. Thus ROIA application has extremely
dynamic distributed workloads, making it dif-
ficult to host them efficiently (Ploß et al., 2009).
In this project, we developed a service-oriented
infrastructure with enhanced security features to
support a business model where multiple indepen-
dent hosters can cooperate seamlessly to provide
QoS assured ROIA service to customers, hence
maximize the benefits.
In EU-funded IRMOS project (http://www.
irmosproject.eu/), it introduced an Intelligent Ser-
vice Oriented Network Infrastructure (INSONI)
to address the on-demand resource provisioning
(http://www.it-tude.com/isoni_whitepaper.html.
Access date: 22 Sept., 2010). The ISONI is an
infrastructure, consisting of a network of resources
(e.g. CPU, storage, networking and software) man-
aged and controlled by an ISONI middleware that
allows resource sharing among multiple services.
The general idea is to provide a service-oriented
infrastructure for SOA components and services.
A service is usually composed of several smaller
and simpler services known as Service Compo-
nents (SC). For SCs orchestrated into a complete
service, a virtual machine will be provisioned,
although it will still be possible to place several
SCs in one virtual machine. ISONI ensures to
provide the best resources for these SCs to be
executed whatever these SCs are. Links between
SCs will be provided as needed. There are three
tasks involved in the ISONI. (i) To completely
separate the management of all hardware resources
distributed in a network from that of deployed
services and their associated service components.
Thus the actual status and distribution of resources
are hidden from the service developer's view. (ii)
To deploy and instantiate service on the ISONI.
The ISONI will be able to accomplish this task
automatically and autonomously, which is the main
goal of the ISONI development. (iii) To monitor
running services and their resource usage. This
On-Demand Resource Provisioning
On-demand resource provisioning is one of key
features of Cloud scalability. When the pro-
visioning resource (as a service) cannot meet
customer's quality of experience, the resource
should automatically grow its capacity to meet the
defined QoS requirements. This capacity growth
is transparent to the users.
There are several approaches to address these
needs. In this chapter we only introduce two EU
funded research projects, namely Edutain@Grid
project and IRMOS project, showing how they
address the “capacity on demand” issues. The
Edutain@Grid project (http://www.edutaingrid.
eu/) has investigated the open federated Cloud
computing initiative for on-demand resource
provisioning. Edutain@Grid aims to develop a
scalable QoS-enabled business Grid environment
for multi-user Real-time Online Interactive Ap-
plications (ROIA) (Fahringer et al., 2007). ROIA
application (e.g. on-line game) is characterized by
the high rate of interaction between users, requiring
very fast updates of information being passed from
one computer to another (Fahringer et al., 2007). As
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