CoAP-CTX: extensão sensível ao contexto para descoberta de objetos inteligentes em internet das coisas

• Ano de defesa: 2017
• Autor(a) principal: Barreto, Felipe Mota
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Internet das coisas; Descoberta de objetos inteligentes; Sensibilidade ao contexto; CoAP
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/30529

In the Internet of Things paradigm, smart objects are interconnected to allow the creation of applications that are part of environments of everyday life (e.g., houses, cars, schools and buildings). The number of these smart objects tends to increase in elevate rates in the next years, creating an overload on the process of configuration, control and use of these objects. Solve this problem is even more important on applications such as the ones classified as universal control, because the main goal of these applications is to let the user control all smart objects available for him. Context-aware discovery services have potential to minimize this problem by applying contextual filters to determine which smart objects will be discovered and become available to user. However, in the IoT scenario, these solutions are still scarce. Then, this work proposes the CoAP-CTX, an extension of the built-in discovery service present in the CoAP (Constrained Application Protocol) that aims to provide support to a context-aware discovery of smart objects. The CoAP-CTX matches user’s interest and context with the smart objects state data to discover only of the most relevant smart objects to the user in this context. Additionally, smart objects that are not of the user’s interest go into an idle state, optimizing the network and battery usage. A proof of concept has been implemented on Android to illustrate how CoAP-CTX works and a performance evaluation was performed on a simulator of wireless sensor networks. The experiments have shown that CoAP-CTX can decrease the total number of messages up to 80% in scenarios where a large number smart objects are presents in a generic environment, like working buildings. The overhead of the discovery latency shows a maximum discovery time increase of 1.5 seconds, which represents an acceptable discovery time for the most type of applications.