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Morteza Biabani is a Ph.D. candidate in the school of Electrical and Computer Engineering at Tehran University currently. He received the B.S.(2015) and M.S. (2017) degrees in Computer Engineering from the University of Tabriz, Tabriz, Iran, respectively. He is working as a researcher at the Router Laboratory at the University of Tehran. Morteza also received several Distinguished Student Awards from Tabriz University. His current research interests include the internet of things and wireless sensor 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 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.
Morteza Biabani; Nasser Yazdani; Hossein Fotouhi. REFIT: Robustness Enhancement Against Cascading Failure in IoT Networks. IEEE Access 2021, 9, 40768 -40782.
AMA StyleMorteza Biabani, Nasser Yazdani, Hossein Fotouhi. REFIT: Robustness Enhancement Against Cascading Failure in IoT Networks. IEEE Access. 2021; 9 ():40768-40782.
Chicago/Turabian StyleMorteza Biabani; Nasser Yazdani; Hossein Fotouhi. 2021. "REFIT: Robustness Enhancement Against Cascading Failure in IoT Networks." IEEE Access 9, no. : 40768-40782.
Wireless Sensor Networks (WSNs) are key elements of Internet of Things (IoT) networks which provide sensing and wireless connectivity. Disaster management in smart cities is classified as a safety-critical application. Thus, it is important to ensure system availability by increasing the lifetime of WSNs. Clustering is one of the routing techniques that benefits energy efficiency in WSNs. This paper provides an evolutionary clustering and routing method which is capable of managing the energy consumption of nodes while considering the characteristics of a disaster area. The proposed method consists of two phases. First, we present a model with improved hybrid Particle Swarm Optimization (PSO) and Harmony Search Algorithm (HSA) for cluster head (CH) selection. Second, we design a PSO-based multi-hop routing system with enhanced tree encoding and a modified data packet format. The simulation results for disaster scenarios prove the efficiency of the proposed method in comparison with the state-of-the-art approaches in terms of the overall residual energy, number of live nodes, network coverage, and the packet delivery ratio.
Morteza Biabani; Hossein Fotouhi; Nasser Yazdani. An Energy-Efficient Evolutionary Clustering Technique for Disaster Management in IoT Networks. Sensors 2020, 20, 2647 .
AMA StyleMorteza Biabani, Hossein Fotouhi, Nasser Yazdani. An Energy-Efficient Evolutionary Clustering Technique for Disaster Management in IoT Networks. Sensors. 2020; 20 (9):2647.
Chicago/Turabian StyleMorteza Biabani; Hossein Fotouhi; Nasser Yazdani. 2020. "An Energy-Efficient Evolutionary Clustering Technique for Disaster Management in IoT Networks." Sensors 20, no. 9: 2647.