Al-Kashoash, HAA, Amer, HM, Mihaylova, L et al. (1 more author) (2017) Optimization Based Hybrid Congestion Alleviation for 6LoWPAN Networks. IEEE Internet of Things Journal, 4 (6). pp. 2070-2081. ISSN 2327-4662
Abstract
The IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) protocol stack is a key part of the Internet of Things (IoT) where the 6LoWPAN motes will account for the majority of the IoT ‘things’. In 6LoWPAN networks, heavy network traffic causes congestion which significantly effects the network performance and the quality of service (QoS) metrics. Generally, two main strategies are used to control and alleviate congestion in 6LoWPAN networks: resource control and traffic control. All the existing work of congestion control in 6LoWPAN networks use one of these. In this paper, we propose a novel congestion control algorithm called optimization based hybrid congestion alleviation (OHCA) which combines both strategies into a hybrid solution. OHCA utilizes the positive aspects of each strategy and efficiently uses the network resources. The proposed algorithm uses a multi-attribute optimization methodology called grey relational analysis for resource control by combining three routing metrics (buffer occupancy, expected transmission count and queuing delay) and forwarding packets through non-congested parents. Also, OHCA uses optimization theory and Network Utility Maximization (NUM) framework to achieve traffic control when the non-congested parent is not available where the optimal nodes’ sending rate are computed by using Lagrange multipliers and KKT conditions. The proposed algorithm is aware of node priorities and application priorities to support the IoT application requirements where the applications’ sending rate allocation is modelled as a constrained optimization problem. OHCA has been tested and evaluated through simulation by using Contiki OS and compared with comparative algorithms. Simulation results show that OHCA improves performance in the presence of congestion by an overall average of 28.36%, 28.02%, 48.07%, 31.97% and 90.35% in terms of throughput, weighted fairness index, end-to-end delay, energy consumption and buffer dropped packets as compared to DCCC6 and QU-RPL.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 IEEE. This is an author produced version of a paper published in IEEE Internet of Things Journal. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Congestion alleviation, hybrid solution, multi attribute decision making, optimization theory, 6LoWPAN networks, IoT applications. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Funding Information: | Funder Grant number EPSRC EP/P023312/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 26 Sep 2017 10:25 |
Last Modified: | 27 Feb 2019 16:12 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Identification Number: | 10.1109/JIOT.2017.2754918 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:121683 |