Selection of Services for Data-Centric Cloud
Applications: A QoS Based Approach
Amit Kr Mandal, Suvamoy Changder, Anirban Sarkar
Department of Computer Applications, National Institute of Technology, Durgapur, INDIA
{amitmandal.nitdgp@gmail.com, suvamoy.nitdgp@gmail.com, sarkar.anirban@gmail.com}
Abstract— In recent days, the numbers of services deployed on the cloud are growing at a dramatic pace. At the same time, a cloud can host very large number of services with the similar functionality, provided by different providers. Moreover, many applications may use the same service to perform a specific type of task. Therefore, it is essential to select appropriate cloud service as per the applications requirements from a large pool of available services. Thus, selection of services for cloud based software applications is a challenging task and demand high level of research attention. From the computational perspective, the service selection mechanism is required to be optimum enough in order to increase the overall performance of the cloud. In this paper, a novel service selection mechanism has been proposed which is based on the “quality of service” (QoS) parameters of the cloud services. Beside the multi-objective optimization, the proposed algorithm is capable to explore multiple cloud services based on user specified QoS values.
Keywords— cloud computing, cloud service selection, QoS parameters, range searching.
I. INTRODUCTION
The shift from traditional software models to the internet
based services has steadily gained momentum now a day, with
the advancement of cloud computing paradigm. Software as a
service (SaaS) is a new software development and deployment
model over the cloud. It offers Information Technology
services dynamically as “on-demand” basis [1]. These
characteristics fueled the large scale growth in SaaS based
applications. The increasing number of services offers great
opportunity for the consumers to find the best service and best
pricing. However, on the other hand this growing number of
services makes it difficult for the users to select the best
suitable solutions from a large pool of available services with
same functionality. This necessitates the use of tools and
techniques to search the suitable services available over the
web. Therefore, the effective service selection mechanism is a
major research challenge as the requester is involved in the
selection process may have a wide variety of requirements.
In order to select a SaaS based service from a large pool of
similar type of available services it is important to differentiate
the services provided by different service providers. In this
context the “quality of service” (QoS) parameters can be taken
as a decisive factor for distinguishing functionally similar
services [2]. QoS describes the capabilities of a product or
service to meet the user requirements. It serves as a benchmark
to differentiate the services as well as the service providers.
Usually for data centric cloud services, a massive volume of data are involved and the services required accessing these data
in order to generate responses for client requests. For such
services the essential invariant is the information exchange
between systems and its components. It describes the exchange
in terms of data model, data producer and consumer of data.
Therefore for the data centric cloud applications, response
time, throughput, reliability, security and cost are considered as
most important quality parameters [3] for service selection.
These can be defined as, (i) the response time is the elapsed
time between a request and response; (ii) throughput is
measured as the maximum number of requests which are
successfully executed per unit time; (iii) reliability is the
probability that a request successfully invoked the service; (iv)
security is the ability to ensure nonrepudiation in data exchange
as well as confidentiality and authentication of concerned user;
and (v) cost defines the economic condition of using a service.
In literature, various selection techniques for cloud services
have been proposed by many researchers. Majority have
discussed the issues related with the service selection in cloud
environment with the high level of abstraction. Only few of
them explore the cloud service selection problem in depth.
Moreover, several brokerage based conceptual cloud service
selection frameworks also have been proposed by the
researchers in recent literatures. Gartner [4] has proposed
different types of cloud brokerage including arbitrage,
aggregation and intermediation. Others [5, 6] have discussed
possible responsibilities of cloud brokers. These literatures are
only described, why service selection is important instead of
how to select a service. However, few QoS based approaches
are studied in literature. Bao et al. [2] used finite state machine
(FSM) to prescribe the legal invocation orders of these web
services. It also proposed a tree-pruning-based algorithm for
the web service composition. But the efficiency of this method
decreases when the number of services increased.
Sundareswaran et al. [7] proposed a brokerage-based
architecture in the cloud. In particular it described the design of
an indexing technique for managing the information of cloud
service providers. But in this approach the requester cannot be
able to specify the order of preference for the QoS parameters.
Cavalcante et al. [8] proposed a mechanism which excludes
coincident services in the calculations. But this approach
required running an additional algorithm for identifying the
coincident services, which in turn increases the execution time.
In Yang et al. [9] and Yu et al. [10] a QoS constraint dynamic
resource selection algorithm for combined resources has been
proposed. In this framework, the indexing service is created based on the most recently measured resource information. 2013 Second International Conference on Advanced Computing, Networking and Security
978-0-7695-5127-2/13 $31.00 © 2013 IEEEDOI 10.1109/ADCONS.2013.31102
