Towards participatory sensing of regions of interest with adaptive sampling rate

Author(s)

Andre, Carlos Henrique de O. M. ; Medeiros, Dianne S. V. ; Campista, Miguel Elias M.

• Document type: Journal article
• Source: VEHICULAR COMMUNICATIONS; v. 25, p. 14-pg., 2020-10-01.

Abstract

Participatory Sensing (PS) is a known paradigm of collaborative networks which provides incentives for users to participate in sensing tasks of Regions of Interest (RoIs). A challenge in wireless networking, however, is to balance the amount of data collected by users without imposing excessive load to the network. In this direction, this paper proposes a centralized system to adapt the sampling rate assigned to each crowdsourcing participant sensor. The sampling rate is computed based on the standard deviation of samples collected from a given RoI. The results obtained via simulations show a tradeoff between the sampling rate and the number of crowdsourcing participants. The more crowdsourcing participants, the lower must be the individual sampling rate and the amount of data transferred. This strategy can increase the data delivery rate taking into account the available short contact times, even though it requires a larger number of sensors. (C) 2020 Elsevier Inc. All rights reserved. (AU)

• FAPESP's process: 15/24490-2 - MC2: mobile computing, content distribution, and cloud computing
• Grantee: Luis Henrique Maciel Kosmalski Costa
• Support Opportunities: Regular Research Grants
• FAPESP's process: 15/24494-8 - Communications and processing of big data in cloud and fog computing
• Grantee: Nelson Luis Saldanha da Fonseca
• Support Opportunities: Research Projects - Thematic Grants