Authors:
João Mafra
;
Francisco Brasileiro
and
Raquel Lopes
Affiliation:
Department of Computing and Systems, Federal University of Campina Grande, Campina Grande, Brazil
Keyword(s):
Edge-computing, Community, Analytics, Privacy.
Abstract:
The popularization of resource-rich smartphones has enabled a wide range of new applications to emerge. Typically, these applications use a remote cloud to process data. In many cases, the data processed (or part of it) is collected by the users’ devices and sent to the cloud. In this architecture, the external cloud provider is the sole responsible for defining the governance of the application and all its data. This is not satisfactory from the privacy viewpoint, and may not be feasible in the long run. We propose an architecture in which the service is governed by the users of a community who have a common problem to solve. To make it possible, we use the concepts of Participatory Sensing, Mobile Social Networks (MSN) and Edge Computing, which enable data processing closer to the data sources (i.e. the users’ devices). We describe the proposed architecture and a case study to assess the feasibility and quality of our solution compared with other solutions already in place. Our cas
e study uses simulation experiments fed with real data from the public transport system of Curitiba, a city in the South of Brazil with a population of approximately 2 million people. The results show that our approach is feasible and can potentially deliver quality of service (QoS) similar or close to the QoS delivered by current approaches that require the existence of a central server.
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