Energy Efficient Routing-Based Clustering Protocol Using Computational Intelligence Algorithms in Sensor-Based IoT
الموضوعات :
Mohammad sedighimanesh
1
,
Hessam Zandhessami
2
,
Mahmood Alborzi
3
,
Mohammadsadegh Khayyatian
4
1 - Science and Research branch, Islamic Azad University
2 - Science and Research branch, Islamic Azad University
3 - Science and Research branch, Islamic Azad University
4 - shahid Beheshti university
الکلمات المفتاحية: Sensor-based IoT, Clustering and Routing, Type-1 and type-2 Fuzzy Algorithms, Computational Intelligence Techniques,
ملخص المقالة :
Background: The main limitation of wireless IoT sensor-based networks is their energy resource, which cannot be charged or replaced because, in most applications, these sensors are usually applied in places where they are not accessible or rechargeable. Objective: The present article's main objective is to assist in improving energy consumption in the sensor-based IoT network and thus increase the network’s lifetime. Cluster heads are used to send data to the base station. Methods: In the present paper, the type-1 fuzzy algorithm is employed to select cluster heads, and the type-2 fuzzy algorithm is used for routing between cluster heads to the base station. After selecting the cluster head using the type-1 fuzzy algorithm, the normal nodes become the members of the cluster heads and send their data to the cluster head, and then the cluster heads transfer the collected data to the main station through the path which has been determined by the type-2 fuzzy algorithm. Results: The proposed algorithm was implemented using MATLAB simulator and compared with LEACH, DEC, and DEEC protocols. The simulation results suggest that the proposed protocol among the mentioned algorithms increases the network’s lifetime in homogeneous and heterogeneous environments. Conclusion: Due to the energy limitation in sensor-based IoT networks and the impossibility of recharging the sensors in most applications, the use of computational intelligence techniques in the design and implementation of these algorithms considerably contributes to the reduction of energy consumption and ultimately the increase in network’s lifetime.
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