A Location-Based Interactive Model of Internet of Things and Cloud (IoT-Cloud) for Mobile Cloud Computing Applications

Abstract

This paper presents a location-based interactive model of Internet of Things (IoT) and cloud integration (IoT-cloud) for mobile cloud computing applications, in comparison with the periodic sensing model. In the latter, sensing collections are performed without awareness of sensing demands. Sensors are required to report their sensing data periodically regardless of whether or not there are demands for their sensing services. This leads to unnecessary energy loss due to redundant transmission. In the proposed model, IoT-cloud provides sensing services on demand based on interest and location of mobile users. By taking advantages of the cloud as a coordinator, sensing scheduling of sensors is controlled by the cloud, which knows when and where mobile users request for sensing services. Therefore, when there is no demand, sensors are put into an inactive mode to save energy. Through extensive analysis and experimental results, we show that the location-based model achieves a significant improvement in terms of network lifetime compared to the periodic model.

An approach for provisioning virtual sensors in sensor clouds

“…As future work, we also intend to (a) perform simulations in more complex environments, taking into account other variables such as the routing protocol, (b) compare ACxSIM with others clustering algorithms, (c) implement the algorithm on a hardware platform to assess its performance in a real environment, and (d) integrate ACxSIM with the interactive model proposed in the previous studies. ()…”

“…The authors in the previous studies() introduce an interactive model for the sensor cloud environments to efficiently provide on‐demand sensing services for multiple applications with different requirements at the same time. It is a novel concept since the middleware can now perform the aggregation of application requests to minimize the resource consumptions of the constrained physical sensor nodes while attending all the requirements of the users' applications.…”

Uso da IoT, Big Data e inteligência artificial nas capacidades dinâmicas

“…A IoT é uma inovação tecnológica que trouxe inteligência aos objetos, ou como afirmam Zhu, Leung, Shu, & Ngai (2015), é um facilitador inteligente do mundo, que tem na sua estrutura, artefatos como a Internet e objetos inteligentes (Galegale, Siqueira, Souza, & Silva, 2016). As tecnologias de identificação de rádio frequência (RFID) e de sensores, evoluirão ainda mais para enfrentar este novo desafio no qual os sistemas de informação e comunicação estão invisivelmente integrados no ambiente ao nosso redor (Gubbi et al, 2013 (Dinh, Kim, & Lee, 2017;Gubbi et al, 2013;Zhu et al, 2015). Além de fornece a infraestrutura necessária para acessar de forma transparente sensores e processos usando protocolos padronizados independentemente de hardware, sistemas operacionais ou localização (Hart & Martinez, 2015).…”

Design and Implementation of a Sensor-Cloud Platform for Physical Sensor Management on CoT Environments

“…Furthermore, users are assigned different levels of priority in order to boost the system performance. A location-based interactive model [47] specified for mobile cloud computing applications is proposed to render sensing services on the demand of a user's interest and location in order to save energy. The cloud controls the sensing scheduling of sensors, for example, sensors are put into inactive mode when there is no demand.…”