Energy‐efficient routing technique for reliable data transmission under the background of big data for disaster region. (22nd February 2020)

• Record Type: Journal Article
• Authors: Peng, Xiaobo; Chang, Yanfen
• Is Part Of: Computational intelligence. Volume 36:Number 4(2020)
• Page Start: 1593
• Page End: 1608
• Publication Date: 2020-02-22
• Subjects: big data -- big data‐based clustering technique -- environment data -- hybrid metaheuristic optimization -- Internet of things (IoT); Artificial intelligence -- Periodicals; Computational linguistics -- Periodicals; 006.3
• DOI: 10.1111/coin.12294
• Languages: English
• ISSNs: 0824-7935

Abstract

Abstract: Big data analysis and cloud computing are gaining much interest in various applications including disaster management. One of the major difficulties in the process of exchanging environmental data in the disaster affected areas has been considered as one of the emerging areas of research. This research focuses on maintaining the environmental data information management of the disaster affected areas, where the intermediate node has been used to transmit the information during transmission and an optimized routing has been used to create efficient data transmission, such as temperature, pressure, humidity, and the level of pollution within the network. The intermediate node may also be hacked during data processing. In this article, the efficient big data‐based clustering technique has been proposed. In this research, the information is grouped into a cluster in every comparable node and the energy consumption has been efficiently managed with the hybrid metaheuristic optimization‐based effective routing technique. The system excellence has been evaluated using the energy utilization factor, packet delivery ratio, and attack‐free routing effectiveness metrics to handle environmental information on disaster affected areas.