25 research outputs found
A Resource-Aware and Time-Critical IoT Framework
Internet of Things (IoT) systems produce great
amount of data, but usually have insufficient resources to
process them in the edge. Several time-critical IoT scenarios
have emerged and created a challenge of supporting low latency
applications. At the same time cloud computing became a success
in delivering computing as a service at affordable price with great
scalability and high reliability. We propose an intelligent resource
allocation system that optimally selects the important IoT data
streams to transfer to the cloud for processing. The optimization
runs on utility functions computed by predictor algorithms that
forecast future events with some probabilistic confidence based
on a dynamically recalculated data model. We investigate ways of
reducing specifically the upload bandwidth of IoT video streams
and propose techniques to compute the corresponding utility
functions. We built a prototype for a smart squash court and
simulated multiple courts to measure the efficiency of dynamic
allocation of network and cloud resources for event detection
during squash games. By continuously adapting to the observed
system state and maximizing the expected quality of detection
within the resource constraints our system can save up to 70%
of the resources compared to the naive solution
Correction to: How will a drier climate change carbon sequestration in soils of the deciduous forests of Central Europe?
The initial online publication contained a typesetting mistake in the author information. The original article has been corrected
ICTAC Kinetics Committee recommendations for collecting experimental thermal analysis data for kinetic computations
International audienceThe present recommendations have been developed by the Kinetics Committee of the International Confederation for Thermal Analysis and Calorimetry (ICTAC). The recommendations offer guidance for obtaining kinetic data that are adequate to the actual kinetics of various processes, including thermal decomposition of inorganic solids; thermal and thermo-oxidative degradation of polymers and organics; reactions of solids with gases; polymerization and crosslinking; crystallization of polymers and inorganics; hazardous processes. The recommendations focus on kinetic measurements performed by means of thermal analysis methods such as thermogravimetry (TG) or thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and differential thermal analysis (DTA). The objective of these recommendations is to assist a non-expert with collecting adequate kinetic data by properly selecting the samples and measurement conditions