Browsing by Author "Czachorski, Tadeusz"

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Citation - WoS: 4
Citation - Scopus: 17
Diffusion Analysis Improves Scalability of IoT Networks to Mitigate the Massive Access Problem
(IEEE Computer Society, 2021) Erol Gelenbe; Mert Nakıp; Dariusz Marek; Tadeusz Czachórskí; Czachorski, Tadeusz; Marek, Dariusz; Nakip, Mert; Gelenbe, Erol
A significant challenge of IoT networks is to offer Quality of Service (QoS) and meet deadline requirements when packets from a massive number of IoT devices are forwarded to an IoT gateway. Many IoT devices tend to report their data to their wired or wireless network gateways at closely correlated instants of time leading to congestion known as the Massive Access Problem (MAP) which increases the probability that the IoT data will not meet its required deadlines. Since IoT data loses much of its value if it arrives to destination beyond a required deadline MAP has been extensively studied in the literature. Thus we first take a queueing theoretic view of the problem and also use a Diffusion Approximation to gain insight into the IoT traffic statistics that affect MAP. Then we introduce the Quasi-Deterministic Transmission Policy (QDTP) which significantly alleviates MAP when the average traffic rate grows beyond a given level and substantially reduces the probability that IoT data deadlines are missed. The results are validated using real IoT data which has been placed in IP packets for transmission. © 2022 Elsevier B.V. All rights reserved.
Citation - WoS: 8
Improving Massive Access to IoT Gateways
(ELSEVIER, 2022) Erol Gelenbe; Mert Nakip; Tadeusz Czachorski; Czachorski, Tadeusz; Nakip, Mert; Gelenbe, Erol
IoT networks handle incoming packets from large numbers of IoT Devices (IoTDs) to IoT Gateways. This can lead to the IoT Massive Access Problem that causes buffer overflow large end-to-end delays and missed deadlines. This paper analyzes a novel traffic shaping method named the Quasi-Deterministic Traffic Policy (QDTP) that mitigates this problem by shaping the incoming traffic without increasing the end-to-end delay or dropping packets. Using queueing theoretic techniques and extensive data driven simulations with real IoT datasets the value of QDTP is shown as a means to considerably reduce congestion at the Gateway and significantly improve the IoT network's overall performance.(c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CCBY license (http://creativecommons.org/licenses/by/4.0/).
Citation - Scopus: 3
Mitigating the Massive Access Problem in the Internet of Things
(Springer Science and Business Media Deutschland GmbH, 2022) Erol Gelenbe; Mert Nakıp; Dariusz Marek; Tadeusz Czachórskí; Czachorski, Tadeusz; Marek, Dariusz; Nakıp, Mert; Gelenbe, Erol; E. Gelenbe , M. Jankovic , D. Kehagias , A. Marton , A. Vilmos
The traffic from the large number of IoT devices connected to the IoT is a source of congestion known as the Massive Access Problem (MAP) that results in packet losses delays and missed deadlines for real-time data. This paper reviews the literature on MAP and summarizes recent results on two approaches that have been designed to mitigate MAP. One approach is based on randomizing the packet arrival instants to IoT gateways within a given time interval that is chosen so that packet arrivals do not exceed their deadlines but also so that they do not constitute bulk arrivals. The second approach is a novel traffic shaping policy named the Quasi-Deterministic-Transmission-Policy (QDTP) which has been proved to drastically reduce queue formation at the receiving gateway by delaying packet departures from the IoT devices in a judicious manner. Both analytical and experimental results are summarized that describe the benefits of these techniques. © 2022 Elsevier B.V. All rights reserved.