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Recommended System for Cluster Head Selection in a Remote Sensor Cloud Environment Using the Fuzzy-Based Multi-Criteria Decision-Making Technique
Clustering is an energy-efficient routing algorithm in a sensor cloud environment (SCE). The clustering sensor nodes communicate with the base station via a cluster head (CH), which can be selected based on the remaining energy, the base station distance, or the distance from the neighboring nodes. If the CH is selected based on the remaining energy and the base station is far away from the cluster head, then it is not an energy-efficient selection technique. The same applies to other criteria. For CH selection, a single criterion is not sufficient. Moreover, the traditional clustering algorithm head nodes keep changing in every round. Therefore, the traditional algorithm energy consumption is less, and nodes die faster. In this paper, the fuzzy multi-criteria decision-making (F-MCDM) technique is used for CH selection and a threshold value is fixed for the CH selection. The fuzzy analytical hierarchy process (AHP) and the fuzzy analytical network process (ANP) are used for CH selection. The performance evaluation results exhibit a 5% improvement compared to the fuzzy AHP clustering method and 10% improvement compared to the traditional method in terms of stability, energy consumption, throughput, and control overhead.
Recommended System for Cluster Head Selection in a Remote Sensor Cloud Environment Using the Fuzzy-Based Multi-Criteria Decision-Making Technique
Clustering is an energy-efficient routing algorithm in a sensor cloud environment (SCE). The clustering sensor nodes communicate with the base station via a cluster head (CH), which can be selected based on the remaining energy, the base station distance, or the distance from the neighboring nodes. If the CH is selected based on the remaining energy and the base station is far away from the cluster head, then it is not an energy-efficient selection technique. The same applies to other criteria. For CH selection, a single criterion is not sufficient. Moreover, the traditional clustering algorithm head nodes keep changing in every round. Therefore, the traditional algorithm energy consumption is less, and nodes die faster. In this paper, the fuzzy multi-criteria decision-making (F-MCDM) technique is used for CH selection and a threshold value is fixed for the CH selection. The fuzzy analytical hierarchy process (AHP) and the fuzzy analytical network process (ANP) are used for CH selection. The performance evaluation results exhibit a 5% improvement compared to the fuzzy AHP clustering method and 10% improvement compared to the traditional method in terms of stability, energy consumption, throughput, and control overhead.
Recommended System for Cluster Head Selection in a Remote Sensor Cloud Environment Using the Fuzzy-Based Multi-Criteria Decision-Making Technique
Proshikshya Mukherjee (Autor:in) / Prasant Kumar Pattnaik (Autor:in) / Ahmed Abdulhakim Al-Absi (Autor:in) / Dae-Ki Kang (Autor:in)
2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
sensor cloud environment , clustering , fuzzy multi-criteria decision-making , fuzzy analytical hierarchy process , fuzzy analytical network process , energy consumption , Environmental effects of industries and plants , TD194-195 , Renewable energy sources , TJ807-830 , Environmental sciences , GE1-350
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