Energy-Efficient Clustering-Based Mobile Routing Algorithm For Wireless Sensor Networks

In this paper, we propose and investigate two types of algorithms for improving energy efficiency in wireless sensor networks. Clustering sensors in wireless sensor networks is considered an effective approach to prolonging network lifetime. In this paper, we divide the study area into clusters at 30-m2 intervals. In each cluster, the sensor that is the closest to the cluster center and has the highest residual energy is selected as the cluster head. In addition, a mobile sink is used to reduce the energy consumption of the cluster heads. The mobile sink travels to all clusters starting with the nearest cluster and collects data from the cluster heads. In the first model, cluster head selection is performed and the mobile sink route is calculated using a greedy approach. In the second model, cluster head selection is performed using an artificial neural network, and the mobile sink route is calculated using a greedy approach. We compared our models with the energy-efficient scalable routing algorithm by the first node dies parameter, all nodes die, and the residual energy of the network for each round condition. The simulation results demonstrated that the proposed models improved the energy efficiency and extended the network lifetime.

[1]  Louiza Bouallouche-Medjkoune,et al.  Placement optimization of wireless mesh routers using firefly optimization algorithm , 2018, 2018 International Conference on Smart Communications in Network Technologies (SaCoNeT).

[2]  Manju,et al.  Genetic algorithm-based meta-heuristic for target coverage problem , 2018, IET Wirel. Sens. Syst..

[3]  Lajos Hanzo,et al.  A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems , 2016, IEEE Communications Surveys & Tutorials.

[4]  Sangwoon Yun,et al.  An Improved Clustering with Particle Swarm Optimization-Based Mobile Sink for Wireless Sensor Networks , 2018, 2018 2nd International Conference on Trends in Electronics and Informatics (ICOEI).

[5]  Yuan Zhou,et al.  Clustering Hierarchy Protocol in Wireless Sensor Networks Using an Improved PSO Algorithm , 2017, IEEE Access.

[6]  Subbu Neduncheliyan,et al.  Genetic algorithm based fault tolerant clustering in wireless sensor network , 2017, IET Commun..

[7]  Meng Zheng,et al.  A Connectivity-Aware Approximation Algorithm for Relay Node Placement in Wireless Sensor Networks , 2015, IEEE Sensors Journal.

[8]  Thomas Weise,et al.  Energy-Efficient Load Balancing Ant Based Routing Algorithm for Wireless Sensor Networks , 2019, IEEE Access.

[9]  Padmalaya Nayak,et al.  Energy Efficient Clustering Algorithm for Multi-Hop Wireless Sensor Network Using Type-2 Fuzzy Logic , 2017, IEEE Sensors Journal.

[10]  Thair. A. Al-Janabi,et al.  A Centralized Routing Protocol With a Scheduled Mobile Sink-Based AI for Large Scale I-IoT , 2018, IEEE Sensors Journal.

[11]  S. K. Mohapatra,et al.  Energy-efficient modified LEACH protocol for IoT application , 2018, IET Wirel. Sens. Syst..

[12]  S. Deng,et al.  Mobility-based clustering protocol for wireless sensor networks with mobile nodes , 2011, IET Wirel. Sens. Syst..

[13]  Ping Ji,et al.  Study on Connected Target Coverage Algorithm for Wireless Sensor Network , 2018, IEEE Access.

[14]  Tat-Chee Wan,et al.  EESRA: Energy Efficient Scalable Routing Algorithm for Wireless Sensor Networks , 2019, IEEE Access.

[15]  Muyiwa B. Balogun,et al.  Energy-balanced and energy-efficient clustering routing protocol for wireless sensor networks , 2019, IET Commun..

[16]  Rajeev Kumar,et al.  Energy Optimization Using Game Theory in Energy-Harvesting Wireless Sensor Networks , 2018, 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC).

[17]  Sukhdeep Kaur,et al.  Nature Inspired Approach based Energy Optimization using Dynamic Clustering in Wireless Sensor Networks , 2018, 2018 International Conference on Computing, Power and Communication Technologies (GUCON).

[18]  Ju-Jang Lee,et al.  Ant-Colony-Based Scheduling Algorithm for Energy-Efficient Coverage of WSN , 2012, IEEE Sensors Journal.

[19]  Padmalaya Nayak,et al.  A Fuzzy Logic-Based Clustering Algorithm for WSN to Extend the Network Lifetime , 2016, IEEE Sensors Journal.

[20]  Richa Sharma,et al.  EEFCM-DE: energy-efficient clustering based on fuzzy C means and differential evolution algorithm in WSNs , 2019, IET Commun..

[21]  Manimozhi Muthukumarasamy,et al.  Energy-efficient clustering algorithm for structured wireless sensor networks , 2018, IET Networks.

[22]  Amir H. Gandomi,et al.  Residual Energy-Based Cluster-Head Selection in WSNs for IoT Application , 2019, IEEE Internet of Things Journal.

[23]  Der-Jiunn Deng,et al.  Router Node Placement With Service Priority in Wireless Mesh Networks Using Simulated Annealing With Momentum Terms , 2016, IEEE Systems Journal.

[24]  Meng-Lin Ku,et al.  A Hybrid Mesh-Ring Topology for Bluetooth Networks , 2018, 2018 IEEE 5G World Forum (5GWF).

[25]  Shivangi Verma,et al.  Efficient energy optimization in Wireless Mesh Network using cluster point , 2015, 2015 1st International Conference on Next Generation Computing Technologies (NGCT).