Visible to the public Data Management Portfolio for Improvement of Privacy in Fog-to-cloud Computing Systems

TitleData Management Portfolio for Improvement of Privacy in Fog-to-cloud Computing Systems
Publication TypeConference Paper
Year of Publication2019
AuthorsChertchom, Prajak, Tanimoto, Shigeaki, Konosu, Tsutomu, Iwashita, Motoi, Kobayashi, Toru, Sato, Hiroyuki, Kanai, Atsushi
Conference Name2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)
KeywordsAdvanced Message Queuing Protocol, cloud computing, Computing Theory and Privacy, data management, data management portfolio, Data models, data portfolio, data privacy, Data Privacy for Fog-to-Cloud (DPPforF2C), data service model, Data Transmission, DPPforF2C, edge devices, fog architecture, Fog Computing, fog nodes, fog-to-cloud computing systems, Human Behavior, Internet of Things, IoT, Message Queuing Telemetry Transport, middleware, practical data model, privacy architecture, privacy concerns, Protocols, pubcrawl, queueing theory, Resiliency, sample data models, Scalability, telemetry
AbstractWith the challenge of the vast amount of data generated by devices at the edge of networks, new architecture needs a well-established data service model that accounts for privacy concerns. This paper presents an architecture of data transmission and a data portfolio with privacy for fog-to-cloud (DPPforF2C). We would like to propose a practical data model with privacy from a digitalized information perspective at fog nodes. In addition, we also propose an architecture for implicating the privacy of DPPforF2C used in fog computing. Technically, we design a data portfolio based on the Message Queuing Telemetry Transport (MQTT) and the Advanced Message Queuing Protocol (AMQP). We aim to propose sample data models with privacy architecture because there are some differences in the data obtained from IoT devices and sensors. Thus, we propose an architecture with the privacy of DPPforF2C for publishing data from edge devices to fog and to cloud servers that could be applied to fog architecture in the future.
Citation Keychertchom_data_2019