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service providers for various services in the composition. Z.Xu and al [21], focused on
the discovery of Web service based on Qos. They have proposed a model of reputation-
enhanced Qos based web services discovery that combines an augmented Universal
Description Discovery and Integration (UDDI) registry to publish the Qos information
and a reputation manager to assign reputation scores to the services based on customer
feedback of their performance. Z. Su and al [22], have proposed a framework of
semantic web service discovery based on fuzzy logic and multi-phase matching, which
exploits domain ontology, fuzzy logic and linguistic variable to present web service
capability and vague information in formal description and implements proximal rea-
soning. In addition, K. Sycara and al [23], have proposed an approach for semantic web
services that combines the growing web services architecture and the semantic web. In
additional, they have proposed DAML-S as prototypical example of an ontology for
describing semantic web services. J. M. García and al [24], have found solution for
services discovery based on SPARQL queries and ontological language OWL-S. Fatma
Siala and al [25], have proposed a framework that deals with the selection of composite
web services on the base of Multi-Agents negotiation. José A. García Coria and al [26],
propose a model based on MAS for construction of the intelligent business processes.
Most of these works have focused only on the discovery of services [21], [22],
[23], [24] and some of them on the composition of services [20] and [25]. In [26], the
authors have focused on the construction of business process. In [25], the authors
have overloaded their MAS by representing every web service of the suppliers by an
agent (e.g. for ten services of provider (X), we have ten agents). Therefore, their ap-
proach is going to take a long-time to communicate with all agents of the different
suppliers. In [26] and [27], the authors have focused on the capture of users require-
ments using only the functional properties (they have not taken into consideration the
non-functional properties (Qos)). In [26], the classification of similar services to
choose the best services for the construction of business processes has not been taken
into consideration.
In our work, we have developed a new approach by: (1) Minimizing the response
time between the agents by representing all services of each supplier by one agent
(e.g. for any services of provider (X), we have one agent). (2) The capture of user
requirements based on both functional and non-functional properties. (3) Proposing
the discovery of all similar services and making their classification according to their
degrees of Qos.
5
Conclusion
In the last years, the cloud computing has become a media phenomenon. This burge-
oning technology allows companies to have the infrastructure and software packages
directly accessible through the internet. Many companies aim to construct their
business processes from existing services and propose it as a service. In this article,
we have introduced a new methodology for constructing business processes from
existing services in using the cloud services and MAS. This methodology contains
three phases: BP description, BP discovery and BP construction). In the first phase,
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