Energy-Efficient Fuzzy-Logic-Based Data Aggregation in Wireless Sensor Networks

Abstract

Wireless sensor networks have limited processing capability and limited battery power. Due to large collection of input data, it is difficult to manage the data along with different domains. Hence, energy-efficient data aggregation technique is required for efficient data collection. Data aggregation is the method in which data coming from different sensors is combined and provides useful aggregated information. Keeping in view the above issue, a novel energy-efficient fuzzy-logic-based data aggregation technique is proposed. The proposed technique collects, analyzes, classifies, and aggregates the data of different domains automatically which is reported by various sensors. Further, fuzzy logic technique is applied as it has capability to deal with dynamic situations and to model the conditions which are inherently imprecisely defined. The proposed data aggregation technique aggregates the incoming data in an effective manner by reducing energy consumption based on different fuzzy rules designed in knowledge base, which further improves network lifetime. The performance of the proposed technique has been evaluated and compared with the existing technique, i.e., energy-efficient scheduling strategy (EESS) in terms of energy consumption, data aggregation rate, data persistence, and network lifetime.