ROAD4WS -- Extending Apache Axis2 for Adaptive Service Compositions

et al. 2014

Context in Computing

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Context aware software systems and adaptive software systems sense changes in their environments, and respond by changing their behaviour and/or structure appropriately. The perspective of these two approaches, however, tends to differ. Context aware systems focus on modelling and reasoning about the relevant environmental context often with aid of formal ontologies The system, however, can only respond to an anticipated change of configuration setting or a change of application mode. Adaptive systems in contrast focus on how the system responds to an unanticipated environmental change. However, adaptive systems typically lack sophisticated models of context. This chapter analyses the differences and similarities between context-aware and adaptive systems. It then describes an approach and framework called ROAD that supports the development of context-aware applications whose structure and behavior can be altered at runtime. ROAD provides mechanisms to acquire and record context information and provision a central store of 'facts' which are evaluated in rules. These rules mediate operational messages or trigger adaptations to the structure of the application.A. Colman ( ) ·

Section: Composite Structurementioning

confidence: 98%

Section: Composite Structurementioning

confidence: 99%

Section: Engineering Caas Applications Using the Road Frameworkmentioning

confidence: 99%

See 1 more Smart Citation

Context Aware and Adaptive Systems

Colman

Hussein

et al. 2014

Context in Computing

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“…In our previous work, we have proposed the ROAD framework which is an extension to Apache Axis2 to realize adaptive service compositions [8]. To realize contextaware adaptive services using this framework (i.e.…”

Section: Realizing Context-aware Adaptive Web Servicesmentioning

confidence: 99%

Scenario-Driven Development of Context-Aware Adaptive Web Services

Hussein

Web Information Systems Engineering - WISE 2012

et al. 2012

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“…In the model deployment step, this composite is instantiated using ROAD4WS [9] which is a middleware extension to the Apache Axis2 1 web service engine. ROAD4WS exposes each role as a service and the associated interactions of the role as methods of that service.…”

Section: A Tool Support For Modeling and Deploymentmentioning

confidence: 99%

SocioTelematics: Leveraging Interaction-Relationships in Developing Telematics Systems to Support Cooperative Convoys

Kabir

2012 9th International Conference on Ubiquitous Intelligence and Computing and 9th International Conference on Autonomic and Tr

Colman

et al. 2012

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Abstract-In a cooperative convoy, a vehicle interacts with other vehicles, service providers and infrastructure systems to make the travel safe and convenient. Through these interactions a vehicle can share its domain-specific information -acquired from service providers and infrastructure -with other vehicles in the convoy. Such interactions are subject to defined agreements and constraints between the entities (i.e., vehicle to vehicle, vehicle to service providers, and so on), which may need to adapt with the changes of requirements. Also a driver may want to automate certain interactions to reduce distraction during driving. A cooperative convoy telematics system should support collaboration (i.e., allow drivers to share specific travel information) and coordination, and be able to cope with the changes.In this paper, we address these issues and demonstrate how our interaction-relationship modeling technique can be exploited to develop a telematics system provides such flexibility. This system allows interactions and coordination preferences explicitly specified and updated to cope with the changes. In particular, our service oriented implementation enhances flexibility and adaptability of the system making it easily deployable and changeable. We have implemented a prototype based on a client-server architecture where the client application is developed for Android and the server is running on the Amazon cloud. The system's performance and resource consumption were evaluated using real-life experiments.