Big data management in participatory sensing: Issues, trends and future directions
Document Type
Article
Publication Date
6-1-2020
Abstract
Participatory sensing has become an emerging technology of this era owing to its low cost in big sensor data collection. Prior to participatory sensing, large-scale deployment complexities were found in wireless sensor networks when collecting data from widespread resources. Participatory sensing systems employ handheld devices as sensors to collect data from communities and transmit to the cloud, where data are further analyzed by expert systems. The processes involved in participatory sensing, such as data collection, transmission, analysis, and visualization, exhibit certain management issues. This study aims to identify big data management issues that must be addressed at the cloud side during data processing and storing and at the participant side during data collection and visualization. It then proposes a framework for big data management in participatory sensing to resolve the contemporary big data management issues on the basis of suggested principles. Moreover, this work presents case studies to elaborate the existence of the highlighted issues. Finally, the limitations, recommendations, and future research directions for academia and industry in the domain of participatory sensing are discussed. (C) 2017 Published by Elsevier B.V.
Keywords
Participatory sensing, Big data, Big data management, Big data analytics, Mobile cloud computing
Divisions
fsktm
Funders
Deanship of Scientific Research, King Saud University [Grant No: 1435-051]
Publication Title
Future generation computer systems-the international journal of Escience
Volume
107
Publisher
Elsevier
Publisher Location
RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS