A new clustering protocol for energy harvesting-wireless sensor networks. (November 2017)

• Record Type: Journal Article
• Authors: Bozorgi, Seyed Mostafa; Shokouhi Rostami, Ali; Hosseinabadi, Ali Asghar Rahmani; Balas, Valentina Emilia
• Is Part Of: Computers & electrical engineering. Volume 64(2017)
• Page Start: 233
• Page End: 247
• Publication Date: 2017-11
• Subjects: WSN -- Routing -- Clustering -- Energy harvesting -- EH-WSN -- Renewable energy; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2017.08.022
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Consider the challenge of increased Throughput in Energy Harvesting Wireless Sensor Networks. Formulating the problem by taking the sunlight energy harvesting to improve the efficiency under energy harvesting restrictions. Proposing a multi-stage unequal hybrid clustering algorithm for such networks. Extensive evaluations are done to evaluate the performance of the proposed method. Results show that the proposed algorithm is significantly better than existing methods. Abstract: Wireless Sensor Networks (WSNs) are used for environmental monitoring. In recent years, energy constraints have led us to develop sensor nodes that harvest energy from the environment. WSNs improve performances by using techniques such as routing and clustering, by harvesting energy from the environment. These networks are called Energy Harvesting Wireless Sensor Network (EH-WSN). Due to the unique features of EH-WSNs, typical WSN clustering and routing methods are inefficient for EH-WSN. In this paper, we propose a novel hybrid methodology involving static and dynamic clustering operations. It uses a distributed-centralized approach and multi-hop routing and considers criteria, such as the energy level, the amount of harvested energy and the number of neighbors in the clustering process. Simulation results show that the proposed method improves the network stability and efficiency, comparing to other methods.