@inproceedings{acc27dffcfc44e798a600fe326f792d0,
title = "Enabling Design of Middleware for Massive Scale IOT-based Systems",
abstract = "Recently, the Internet of Things (IoT) technology has rapidly advanced to the stage where it is feasible to discover, locate and identify various smart sensors and devices based on the context, situation, their characteristics and relevancy to query for their data or control actions. Taking things, a step further when developing Large Scale Applications requires to overcome two serious issues. The first issue is find a solution for data sensing and collection from a massive number of various ubiquitous devices when converging these into the next generation networks. The second important issue is to deal with the {"}Big Data{"} that arrive from a very large number of sources. This research emphasizes the need for finding a solution for a large scale data aggregation and delivery. The paper introduces biomimetic design methods for data aggregation in the context of large scale IoT-based systems.",
keywords = "5G Communications, Internet of Things, Massive-scale systems, Middleware, Ubiquitous Systems",
author = "Zenon Chaczko and Ryszard Klempous and Jerzy Rozenblit and Christopher Chiu and Konrad Kluwak and Czeslaw Smutnicki",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 23rd IEEE International Conference on Intelligent Engineering Systems, INES 2019 ; Conference date: 25-04-2019 Through 27-04-2019",
year = "2019",
month = apr,
doi = "10.1109/INES46365.2019.9109497",
language = "English (US)",
series = "INES 2019 - IEEE 23rd International Conference on Intelligent Engineering Systems, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "219--223",
booktitle = "INES 2019 - IEEE 23rd International Conference on Intelligent Engineering Systems, Proceedings",
}