A Scalable Monitoring System for Distributed Environments

Author(s):  
Sayaka Akioka ◽  
Junichi Ikeda ◽  
Takanori Ueda ◽  
Yuki Ohno ◽  
Midori Sugaya ◽  
...  
2012 ◽  
Vol 13 (6) ◽  
pp. 63-74 ◽  
Author(s):  
Bup-Ki Min ◽  
Yongjin Seo ◽  
Hyeon Soo Kim ◽  
Seunghak Kuk ◽  
Yonghwan Jung ◽  
...  

Author(s):  
Aleksander Laurentowski ◽  
Jakub Szymaszek ◽  
Andrzej Uszok ◽  
Krzysztof Zieliński

Author(s):  
Andre Brinkmann ◽  
Christoph Fiehe ◽  
Anna Litvina ◽  
Ingo Luck ◽  
Lars Nagel ◽  
...  

The absence of the tyres monitoring system on vehicle has caused difficulty for driver to check the pressure and temperature of the tyres in real time. Besides that, due to the large geographical area of rural area where the distribution of petrol station with air pump might not be equally distributed, certain area is hard to access air pump. The abnormal pressure and increases in temperature on tyre lead to longer braking distance, tyre blowouts and related issues. The paper describes the deployment of IoT sensors for monitoring application in tyres and data is accessible on mobile app. This monitoring system consists of two sensors to measure the temperature and pressure of the tyre using ESP32 microcontroller board and uploaded into the cloud platform using Wi-Fi technology. While Blynk the mobile app is designed to collect the informative data from the cloud platform and the data is represented in graphical representation using open source Cloud platform. It is made available for real-time monitoring data. Apart from that, this system also incorporates alert system to provide a scalable monitoring system as well as alerting the user for any abnormal reading of the tyre.


Author(s):  
Michel Bonfim ◽  
Kelvin Dias ◽  
Stenio Fernandes

A comprehensive monitoring system is essential to assist solutions for most of SFC problems. Therefore, in this work, we propose SFCMon, an efficient and scalable monitoring solution to keep track network flows in SFC environments. To achieve the desired goals, SFCMon works with a pipeline of probabilistic data structures to detect and store large flows as well as perflow counters. For evaluation purposes, based on the SFC reference architecture defined by RFC 7665, we implement a Proof-of-Concept (PoC) framework, which provides a P4-based SFC switch and Python-based SFC Controller. Presented initial experiments demonstrate that SFCMon introduces a negligible performance penalty while providing significant scalability gains.


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