Data aggregation represents a fundamental process within
wireless sensor networks, facilitating the transmission of environmental data
to end-users via base stations. Despite its critical role, data aggregation
often receives less attention compared to routing and energy optimization
challenges. This work presents a comprehensive review of existing data
aggregation schemes, with a specific emphasis on correlational-based
approaches. Our analysis reveals a significant gap in research dedicated to
correlational-based data aggregation techniques. Furthermore, existing methods
tend to overlook crucial factors such as data quality, computational
complexity, and appropriate benchmarking. Addressing these unresolved issues is
essential for enhancing the reliability and quality of data aggregation
processes in wireless sensor networks. This chapter outlines the key challenges
and opportunities for future investigations in this domain.
Author(s) Details:
Anand Gudnavar,
Department of CSE, Jain College of Engineering and Research,
Belagavi, Karnataka, India.
Virupaxi Dalal,
Department
of ECE, Jain College of Engineering and Research, Belagavi, Karnataka, India.
Raghavendra Maggavi,
Department of ECE, Jain College of Engineering and Research,
Belagavi, Karnataka, India.
Veeresh Hiremath,
Department of ECE, Jain College of Engineering and Research,
Belagavi, Karnataka, India.
Please see the link here: https://stm.bookpi.org/RUMCS-V4/article/view/14140
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