An Enhanced CoAP Scheme Using Fuzzy Logic With Adaptive Timeout for IoT Congestion Control

Congestion management in the Internet of Things (IoT) is one of the most challenging tasks in improving the quality of service (QoS) of a network. This is largely because modern wireless networks can consist of an immense number of connections. Consequently, limited network resources can be consumed...

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Main Authors: Phet Aimtongkham, Paramate Horkaew, Chakchai So-In
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9400832/
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spelling doaj-d112dc77c009426faba512ba878c8eb22021-04-22T23:00:27ZengIEEEIEEE Access2169-35362021-01-019589675898110.1109/ACCESS.2021.30726259400832An Enhanced CoAP Scheme Using Fuzzy Logic With Adaptive Timeout for IoT Congestion ControlPhet Aimtongkham0Paramate Horkaew1https://orcid.org/0000-0003-0879-7125Chakchai So-In2https://orcid.org/0000-0003-1026-191XDepartment of Computer Science, Faculty of Science, Applied Network Technology (ANT) Laboratory, Khon Kaen University, Khon Kaen, ThailandSchool of Computer Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima, ThailandDepartment of Computer Science, Faculty of Science, Applied Network Technology (ANT) Laboratory, Khon Kaen University, Khon Kaen, ThailandCongestion management in the Internet of Things (IoT) is one of the most challenging tasks in improving the quality of service (QoS) of a network. This is largely because modern wireless networks can consist of an immense number of connections. Consequently, limited network resources can be consumed simultaneously. This eventually causes congestion that has adverse impacts on both throughput and transmission delay. This is particularly true in a network whose transmissions are regulated by the Constrained Application Protocol (CoAP), which has been widely adopted in the IoT network. CoAP has a mechanism that allows connection-oriented communication by means of acknowledgment messages (ACKs) and retransmission timeouts (RTOs). However, during congestion, a client node is unable to efficiently specify the RTO, resulting in unnecessary retransmission. This overhead in turn causes even more extensive congestion in the network. Therefore, this research proposes a novel scheme for optimally setting the initial RTO and adjusting the RTO backoff that considers current network utilization. The scheme consists of three main components: 1) a multidimensional congestion estimator that determines congestion conditions in various aspects, 2) precise initial RTO estimation by means of a relative strength indicator and trend analysis, and 3) a flexible and congestion-aware backoff strategy based on an adaptive-boundary backoff factor evaluated by using a fuzzy logic system (FLS). The simulation results presented here reveal that the proposed scheme outperforms state-of-the-art methods in terms of the carried load, delay and percentage of retransmission.https://ieeexplore.ieee.org/document/9400832/Adaptive timeoutcongestion controlconstrained application protocolfuzzy logic systemsInternet of Things
collection DOAJ
language English
format Article
sources DOAJ
author Phet Aimtongkham
Paramate Horkaew
Chakchai So-In
spellingShingle Phet Aimtongkham
Paramate Horkaew
Chakchai So-In
An Enhanced CoAP Scheme Using Fuzzy Logic With Adaptive Timeout for IoT Congestion Control
IEEE Access
Adaptive timeout
congestion control
constrained application protocol
fuzzy logic systems
Internet of Things
author_facet Phet Aimtongkham
Paramate Horkaew
Chakchai So-In
author_sort Phet Aimtongkham
title An Enhanced CoAP Scheme Using Fuzzy Logic With Adaptive Timeout for IoT Congestion Control
title_short An Enhanced CoAP Scheme Using Fuzzy Logic With Adaptive Timeout for IoT Congestion Control
title_full An Enhanced CoAP Scheme Using Fuzzy Logic With Adaptive Timeout for IoT Congestion Control
title_fullStr An Enhanced CoAP Scheme Using Fuzzy Logic With Adaptive Timeout for IoT Congestion Control
title_full_unstemmed An Enhanced CoAP Scheme Using Fuzzy Logic With Adaptive Timeout for IoT Congestion Control
title_sort enhanced coap scheme using fuzzy logic with adaptive timeout for iot congestion control
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2021-01-01
description Congestion management in the Internet of Things (IoT) is one of the most challenging tasks in improving the quality of service (QoS) of a network. This is largely because modern wireless networks can consist of an immense number of connections. Consequently, limited network resources can be consumed simultaneously. This eventually causes congestion that has adverse impacts on both throughput and transmission delay. This is particularly true in a network whose transmissions are regulated by the Constrained Application Protocol (CoAP), which has been widely adopted in the IoT network. CoAP has a mechanism that allows connection-oriented communication by means of acknowledgment messages (ACKs) and retransmission timeouts (RTOs). However, during congestion, a client node is unable to efficiently specify the RTO, resulting in unnecessary retransmission. This overhead in turn causes even more extensive congestion in the network. Therefore, this research proposes a novel scheme for optimally setting the initial RTO and adjusting the RTO backoff that considers current network utilization. The scheme consists of three main components: 1) a multidimensional congestion estimator that determines congestion conditions in various aspects, 2) precise initial RTO estimation by means of a relative strength indicator and trend analysis, and 3) a flexible and congestion-aware backoff strategy based on an adaptive-boundary backoff factor evaluated by using a fuzzy logic system (FLS). The simulation results presented here reveal that the proposed scheme outperforms state-of-the-art methods in terms of the carried load, delay and percentage of retransmission.
topic Adaptive timeout
congestion control
constrained application protocol
fuzzy logic systems
Internet of Things
url https://ieeexplore.ieee.org/document/9400832/
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