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Full-Text Articles in Systems Architecture
Virtual Sensor Middleware: Managing Iot Data For The Fog-Cloud Platform, Fadi Almahamid, Hanan Lutfiyya, Katarina Grolinger
Virtual Sensor Middleware: Managing Iot Data For The Fog-Cloud Platform, Fadi Almahamid, Hanan Lutfiyya, Katarina Grolinger
Electrical and Computer Engineering Publications
This paper introduces the Virtual Sensor Middleware (VSM), which facilitates distributed sensor data processing on multiple fog nodes. VSM uses a Virtual Sensor as the core component of the middleware. The virtual sensor concept is redesigned to support functionality beyond sensor/device virtualization, such as deploying a set of virtual sensors to represent an IoT application and distributed sensor data processing across multiple fog nodes. Furthermore, the virtual sensor deals with the heterogeneous nature of IoT devices and the various communication protocols using different adapters to communicate with the IoT devices and the underlying protocol. VSM uses the publish-subscribe design pattern …
Similarity-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian, Ljubisa Sehovac, Katarina Grolinger
Similarity-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian, Ljubisa Sehovac, Katarina Grolinger
Electrical and Computer Engineering Publications
Smart meter popularity has resulted in the ability to collect big energy data and has created opportunities for large-scale energy forecasting. Machine Learning (ML) techniques commonly used for forecasting, such as neural networks, involve computationally intensive training typically with data from a single building or a single aggregated load to predict future consumption for that same building or aggregated load. With hundreds of thousands of meters, it becomes impractical or even infeasible to individually train a model for each meter. Consequently, this paper proposes Similarity-Based Chained Transfer Learning (SBCTL), an approach for building neural network-based models for many meters by …
Integrating Recommender Information In Social Ecosystems Decisions, Renato A C Capuruco, Luiz Fernando Capretz
Integrating Recommender Information In Social Ecosystems Decisions, Renato A C Capuruco, Luiz Fernando Capretz
Electrical and Computer Engineering Publications
The exploration of online social networks whose members share mutual recommendations and interactions is a time-dependent and contextual-based process which aims to predict the social status among members, ultimately improving the network's discoverability to achieve societal gain. To address the difficulties associated with the process, this article presents an integrated recommender model whose statements are time-dependent, interaction-aware, and social context-sensitive. The originality of the proposed model stems from the integration of the predictive recommender, social networks, and interaction components. Each model is developed based on: (1) a time history and decay algorithm to consider the decreasing intensity of recommendations among …