SENSE: Scalable Data Acquisition from Distributed Sensors with Guaranteed Time Coherence

12/10/2019
by   Jonas Traub, et al.
0

Data analysis in the Internet of Things (IoT) requires us to combine event streams from a huge amount of sensors. This combination (join) of events is usually based on the time stamps associated with the events. We address two challenges in environments which acquire and join events in the IoT: First, due to the growing number of sensors, we are facing the performance limits of central joins with respect to throughput, latency, and network utilization. Second, in the IoT, diverse sensor nodes are operated by different organizations and use different time synchronization techniques. Thus, events with the same timestamps are not necessarily recorded at the exact same time and joined data tuples have an unknown time incoherence. This can cause undetected failures, such as false correlations and wrong predictions. We present SENSE, a system for scalable data acquisition from distributed sensors. SENSE introduces time coherence measures as a fundamental data characteristic in addition to common time synchronization techniques. The time coherence of a data tuple is the time span in which all values contained in the tuple have been read from sensors. We explore concepts and algorithms to quantify and optimize time coherence and show that SENSE scales to thousands of sensors, operates efficiently under latency and coherence constraints, and adapts to changing network conditions.

READ FULL TEXT
research
10/05/2022

SECOE: Alleviating Sensors Failure in Machine Learning-Coupled IoT Systems

Machine learning (ML) applications continue to revolutionize many domain...
research
11/10/2017

D-SLATS: Distributed Simultaneous Localization and Time Synchronization

Through the last decade, we have witnessed a surge of Internet of Things...
research
09/14/2018

Lightweight Synchronization Algorithm with Self-Calibration for Industrial LORA Sensor Networks

Wireless sensor and actuator networks are gaining momentum in the era of...
research
04/21/2021

Analysis of Distributed Average Consensus Algorithms for Robust IoT networks

Internet of Things(IoT) is a heterogeneous network consists of various p...
research
04/10/2019

On Maximizing Task Throughput in IoT-enabled 5G Networks under Latency and Bandwidth Constraints

Fog computing in 5G networks has played a significant role in increasing...
research
02/17/2022

Iterative Probabilistic Performance Prediction for Multiple IoT Applications in Contention

Internet of Things (IoT) have become omnipresent in many applications su...

Please sign up or login with your details

Forgot password? Click here to reset