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Exploring an Effectiveness & Pitfalls of Correlational-based Data Aggregation Approaches in Sensor Network
Author(s) -
Anand Gudnavar,
Rajashekhara
Publication year - 2017
Publication title -
international journal of wireless and microwave technologies
Language(s) - English
Resource type - Journals
eISSN - 2076-9539
pISSN - 2076-1449
DOI - 10.5815/ijwmt.2017.02.05
Subject(s) - data aggregator , computer science , scope (computer science) , benchmarking , wireless sensor network , focus (optics) , process (computing) , reliability (semiconductor) , quality (philosophy) , data quality , data science , data mining , computer network , engineering , metric (unit) , power (physics) , philosophy , physics , operations management , epistemology , marketing , quantum mechanics , optics , business , programming language , operating system
Data aggregation is one of the core processing in wireless sensor network which ensures that environmental data being captured reaches the user via base station. In order to ensure proper data aggregation, there are many underlying principles that need more attention as compared to more frequently visited routing and energy problems. We reviewed existing data aggregation schemes with special focus on data correlation scheme and found that there is still a large scope of investigation in this area. We find that there are only less number of research publications towards existing techniques of data aggregation using correlational-based approach. It was also explored that such techniques still does not focus much on data quality, computational complexity, inappropriate benchmarking, etc. This paper elaborates about all the unsolved issues which require dedicate focus of investigation towards enhancing the data reliability and data quality in aggregation process in wireless sensor network.

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