Today, with the exponential rise in the use of the internet, the trend of the massive use of mobile devices (tablets, laptops, computers, iPads etc...) the user has become inseparable from his smartphone, which facilitates the use of several services in different fields (work, research, commerce, etc.). Besides, with the proliferation of data, the needs of consumers are becoming increasingly complex. So the composition of web services remains a necessary process allowing to combine several atomic services aggregating different functionalities to answer a complex request. Several techniques in the literature like, AI planning, work flow, Agent, Mathematics and Semantic. These techniques are mainly involved in the automation and improvement of the composition process. In this article, we will survey several context aware web service composition approaches based on these techniques. Remember that the Mobile environment is characterized by software, hardware and space constraints and Web Service Composition in mobile environment must respect these conditions.

Service-oriented computing (SOC) has come into view as a new computing paradigm that makes systems development and business process management more flexible and agile. It has recourse to services functioning as a fundamental compound in order to assist the construction of rapid and easy composition of distributed applications in heterogeneous environments. The rapid development of web service technologies has dramatically increased the number of available web services including those available on social networks. Thus, many studies have been carried out in the discovery mechanisms. The majority of proposed approaches in the literature for web services discovery based on the description of web services themselves and neglect their interaction with each other. Through the overlapping between social computing (illustrated by social networks) and service oriented computing (illustrated by web services), social web services are produced that are different from regular web services. In fact, they are a member of a social network and have an idea about other services in the same network. The first purpose of this paper is to justify the need of the use of an extension of WSDL-S to facilitate web service discovery, and the second purpose is to build a social network of web services to take advantage of the interactions that occur between services. However, the effort of developing social web services can partly undermine the utility of their implementation.

Over the last decades, there has been a growing interest to Service Oriented Computing (SOC) especially in a mobile environement. Web Services are the most common form of services for implementing SOC. Service Composition is to create a new business process by composing several services in order to fulfill business goals that individual services cannot achieve. The massive use of web services in the mobile devices imposes more manipulation of these services such as discovery, invocation, composition and execution. Web Service Composition in a mobile environement raises several challenges that does not exist in a classic (non-mobile) environement. Among these challenges is the change of context mainly due to the mobility of the smart device. We will refer to this in the paper as “uncertain context”. In this work we limit uncertain context to the couple(Location, bandwidth). We build an uncertain context based model, calculating the probability of context change. Then we try to find how the uncertain context influences service availability. This is traduced by the defined sensitivity function. Once showing how much does the services are sensitive to uncertain context, we build a web service composition model, based on web service sensitivity and presenting service composition plans according to their probabilities.

In this work, we present a framework for the semantic composition of web services based on Statecharts and uniform community service descriptions. Our model is a two step process. In the first step, we derive the execution model of the user's query. The execution model is specified in Statecharts formalism; whereas the user's query is described in OWL-S. Therefore, a mapping from Statecharts formalism to OWL-S is developed. In the second step, we instantiate the developed execution model through invocation of available e-services instances. Hence, and a result, we obtain an execution plan (said also strategy) satisfying user constraints. The key features of the proposed framework could be summarized as follows. First, unlike other existing languages, using OWL-S enables the semantic description of e-services. These semantics are taken into consideration in our composition strategy. Second, the user constraints (or preferences) are taken into account during composition and are expressed as a finite set of logical formulas with the Knowledge Interchange Format (KIF) language.