REFIT: Robustness Enhancement Against Cascading Failure in IoT Networks
There has been tremendous growth in the Internet of Things (IoT) technologies, and many new applications have emerged. However, cascading failure as one of the major issues in such constrained networks have been neglected. In this paper, we apply an effective clustering approach dubbed as REFIT to e...
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doaj-98757003a96a4066acd8de26744d6ee72021-03-30T14:58:41ZengIEEEIEEE Access2169-35362021-01-019407684078210.1109/ACCESS.2021.30652939374409REFIT: Robustness Enhancement Against Cascading Failure in IoT NetworksMorteza Biabani0https://orcid.org/0000-0002-1480-7820Nasser Yazdani1Hossein Fotouhi2School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, IranSchool of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, IranSchool of Innovation, Design and Engineering, Mälardalen University, Västerås, SwedenThere has been tremendous growth in the Internet of Things (IoT) technologies, and many new applications have emerged. However, cascading failure as one of the major issues in such constrained networks have been neglected. In this paper, we apply an effective clustering approach dubbed as REFIT to enhance network topology robustness via nodes’ residual energy. The REFIT protocol divides the network processes into two stages, (i) set-up state and (ii) steady state. The Cluster Head (CH) selection method determines the supreme set of CHs that balances load distribution. The routing method is developed with the modified Particle Swarm Optimization (PSO) algorithm and the objective function to find the supreme set of Relay Nodes (RNs). These complete methods are combined into a set-up state to construct an optimal routing tree that links these CHs to the sink via RNs. In steady state, we model the routing tree to Conditional Directed Acyclic Graph (C-DAG) infrastructure that leads to shortcut routes. Simulation results on MATLAB Simulink have demonstrated that compared with the state-of-the-art works, REFIT can significantly promote network robustness against cascading failure.https://ieeexplore.ieee.org/document/9374409/IoTcascading failurerobustnessclusteringparticle swarm optimizationfault tolerance |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Morteza Biabani Nasser Yazdani Hossein Fotouhi |
spellingShingle |
Morteza Biabani Nasser Yazdani Hossein Fotouhi REFIT: Robustness Enhancement Against Cascading Failure in IoT Networks IEEE Access IoT cascading failure robustness clustering particle swarm optimization fault tolerance |
author_facet |
Morteza Biabani Nasser Yazdani Hossein Fotouhi |
author_sort |
Morteza Biabani |
title |
REFIT: Robustness Enhancement Against Cascading Failure in IoT Networks |
title_short |
REFIT: Robustness Enhancement Against Cascading Failure in IoT Networks |
title_full |
REFIT: Robustness Enhancement Against Cascading Failure in IoT Networks |
title_fullStr |
REFIT: Robustness Enhancement Against Cascading Failure in IoT Networks |
title_full_unstemmed |
REFIT: Robustness Enhancement Against Cascading Failure in IoT Networks |
title_sort |
refit: robustness enhancement against cascading failure in iot networks |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2021-01-01 |
description |
There has been tremendous growth in the Internet of Things (IoT) technologies, and many new applications have emerged. However, cascading failure as one of the major issues in such constrained networks have been neglected. In this paper, we apply an effective clustering approach dubbed as REFIT to enhance network topology robustness via nodes’ residual energy. The REFIT protocol divides the network processes into two stages, (i) set-up state and (ii) steady state. The Cluster Head (CH) selection method determines the supreme set of CHs that balances load distribution. The routing method is developed with the modified Particle Swarm Optimization (PSO) algorithm and the objective function to find the supreme set of Relay Nodes (RNs). These complete methods are combined into a set-up state to construct an optimal routing tree that links these CHs to the sink via RNs. In steady state, we model the routing tree to Conditional Directed Acyclic Graph (C-DAG) infrastructure that leads to shortcut routes. Simulation results on MATLAB Simulink have demonstrated that compared with the state-of-the-art works, REFIT can significantly promote network robustness against cascading failure. |
topic |
IoT cascading failure robustness clustering particle swarm optimization fault tolerance |
url |
https://ieeexplore.ieee.org/document/9374409/ |
work_keys_str_mv |
AT mortezabiabani refitrobustnessenhancementagainstcascadingfailureiniotnetworks AT nasseryazdani refitrobustnessenhancementagainstcascadingfailureiniotnetworks AT hosseinfotouhi refitrobustnessenhancementagainstcascadingfailureiniotnetworks |
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1724180238631436288 |