@inproceedings{24a357ec722b4760ba6c0bb83c4259c3,
title = "Intelligent Edge: An Instantaneous Detection of IoT Traffic Load",
abstract = "Internet of Things (IoT) can be defined as the interconnection of any device to the Internet that collects and exchanges information. With the rapidly growing heterogenetic IoT applications and its associated devices, a massive amount of data is being transmitted in the network. Often, a large spike in network traffic to a particular destination causes a widespread disruption of Internet services for end users, which can cause online businesses billions of dollars in losses. In this paper, we analyze an intelligent edge that can identify volumetric traffic and address them in real-time using an instantaneous detection method for IoT applications. This approach can easily detect a large surge and a potential variation in traffic patterns for an IoT application, which can contribute to safer and more efficient operation of the overall system. As per our results, we gave a closer insight on the advantage of having an intelligent edge to serve as a detection mechanism.",
keywords = "Arrival Rate, IoT, Publish/Subscribe Model, QoS, Queueing Delay, Queueing Theory, Traffic Load",
author = "Maha Alaslani and Basem Shihada",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Communications, ICC 2018 ; Conference date: 20-05-2018 Through 24-05-2018",
year = "2018",
month = jul,
day = "27",
doi = "10.1109/ICC.2018.8423004",
language = "English (US)",
isbn = "9781538631805",
series = "IEEE International Conference on Communications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2018 IEEE International Conference on Communications, ICC 2018 - Proceedings",
address = "United States",
}