A Novel Process Network Model for Interacting Context-Aware Web Services

Abstract

Abstract-Context-aware web services have been attracting significant attention as an important approach for improving the usability of web services. In this paper, we explore a novel approach to model dynamic behaviors of interacting context-aware web services, aiming to effectively process and take advantage of contexts and realize behavior adaptation of web services and further to facilitate the development of context-aware application of web services. We present an interaction model of context-aware web services based on Context-aware Process Network (CAPN), which is a dataflow and channel based model of cooperative computation. CAPN is extended to context-aware web service network by introducing a kind of sensor processes, which is used to catch contextual data from external environment. Through modeling the register link's behaviors, we present how a web service can respond to its context changes dynamically. The formal behavior semantics of our model is described by Calculus of Communicating Systems (CCS) process algebra. The behavior adaptation and context-awareness in our model are discussed. A XML (eXtensible Markup Language) formatted service behavior description language named BML4WS is designed to describe behaviors and behavior adaptation of interacting context-aware web services. Finally, an application case is demonstrated to illustrate the proposed model how to adapt context changes and describe service behaviours and their changes.

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“…Spatial sensing data (e.g., on location, temperature, movement speed) are also available by multiple sensing models and contextual computing capabilities [68] embedded in a mobile device. Such contents may be of interest to specific groups of people in a specific time or geographic area.…”

“…The basic idea of the existing work is to spread the message to a small set of nodes that have a high probability to deliver the message to the destination [73]. Much of the existing work made predictions based on the mobility pattern [68] and the contact history [76,90] of users. Recently, social relationships have also been explored to divide users into different social groups to better predict their meeting probability [6,[76][77][78].…”

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“…They argue that the context should include items such as location, lighting, noise level, network connectivity, and communication costs (Rong & Liu, 2010). (Zhang, Liu et al, 2013) proposed a novel approach to modeling the dynamic behavior of interacting context-aware Web services, aiming to process and take advantage of context effectively in realizing the behavior adaptation of Web services. Moreover, for service recommendation, some researchers have used both personal-usage history-oriented contexts and groupusage history-oriented contexts, such as collaborative filters that assess users' ratings of Web services (Resnick, Iakovou et al, 1994;Manikrao & Prabhakar, 2005).…”

“…These categories include user properties such as location and time (Xiao, Zou et. al., 2010;Bottaro, Bourcier et al, 2007), user preferences (Bottaro, Bourcier et al, 2007), and the environment affecting Web service delivery and execution such as service location (Li, Luo et al, 2013), service profiles and network bandwidth (Zhang, Liu et al, 2013;Chen, Yang et al, 2006). Contexts such as these are used as extra information in the matchmaking process to obtain the desired and most relevant services according to user requests.…”

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