Developing Self-Adaptive Service-Oriented Mobile Applications: A Framework Based on Dynamic Deployment
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2018-11-01
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Today's society is increasingly dependent on the use of mobile or smart devices (e.g. smartphones, tablets, hybrid devices, smart-TVs, smart-watches, among others), which have changed over these last 10 years the way people perform their daily tasks. In parallel, Internet of Things (IoT) systems have played a prominent position in this scenario, since they enable to exchange information among different types of devices and services (e.g. physical devices, vehicles, home appliances, sensors, among others). This scenario has boosted the demand for development of high-quality Mobile Applications (MobApps), which can be pre-installed on such devices during manufacturing platforms, or delivered as applications by the mobile stores or third parties. According to [1-3], mobile devices have some physical limitations (e.g. processing and storage) compared to personal computers. Thus, service-oriented MobApps have been a feasible alternative to overcome such limitations, improving the efficiency of the development life cycle of these applications with adoption of third-party components (e.g. software components, web services, and other mobile applications). In another perspective, it is also been noted a change in the user behavior of MobApps, which demand applications capable of operating in adverse conditions, maintaining their integrity of execution. Considering the relevance of such applications, this paper reports the extension of a framework to support the development of Self-adaptive Services-oriented MobApps (Self-MobApps), which enables modification of services at runtime [4] by means of a deployment dynamic approach. To show the feasibility of our framework, a case study for a smart restaurant was conducted in a mobile environment. The results of this study enable us to create a positive perspective on the contribution of our framework to the research communities involved.
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International Journal of Software Engineering and Knowledge Engineering, v. 28, n. 11-12, p. 1537-1558, 2018.
