Data Redundancy Reduction for Energy-Efficiency in Wireless Sensor Networks: A Comprehensive Review

Wireless Sensor Networks (WSNs) play a significant role in providing an extraordinary infrastructure for monitoring environmental variations such as climate change, volcanoes, and other natural disasters. In a hostile environment, sensors' energy is one of the crucial concerns in collecting and analyzing accurate data. However, various environmental conditions, short-distance adjacent devices, and extreme usage of resources, i.e., battery power in WSNs, lead to a high possibility of redundant data. Accordingly, the reduction in redundant data is required for both resources and accurate information. In this context, this paper presents a comprehensive review of the existing energy-efficient data redundancy reduction schemes with their benefits and limitations for WSNs. The entire concept of data redundancy reduction is classified into three levels, which are node, cluster head, and sink. Additionally, this paper highlights existing key issues and challenges and suggested future work in reducing data redundancy for future research.

Automated summary

This paper reviews the existing energy-efficient data redundancy reduction schemes in Wireless Sensor Networks (WSNs), categorizing the concept into three levels: node, cluster head, and sink. It also highlights current key issues and challenges, as well as suggesting future research directions for reducing data redundancy.