Routing and Data Aggregation Techniques in Wireless Sensor Networks: Previous Research and Future Scope

Kaur, Navjyot; Vetrithangam, D.

doi:10.1007/978-981-99-5435-3_51

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Book1

Other1

Article1

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Computational Approach for Data Aggregation in Wireless Sensor Networks (WSNs)

Kaur,

Vetrithangam

2024

Lecture Notes in Networks and Systems

View full text Add to dashboard Cite

Computational Approach for Data Aggregation in Wireless Sensor Networks (WSNs)

Kaur,

Vetrithangam

2024

Lecture Notes in Networks and Systems

View full text Add to dashboard Cite

A Comprehensive Study on Aggregation and Routing Techniques with MATLAB Implementation and QoS Parameter Collection

Kaur,

2024

2024 Asia Pacific Conference on Innovation in Technology (APCIT)

View full text Add to dashboard Cite

Energy Efficient Data Aggregation in Wireless Sensor Networks Using Meta Heuristic Based Feed Forward Back Propagation Neural Network Approach

Kaur,

2024

JMC

View full text Add to dashboard Cite

Sensor nodes are low-cost, low-power, tiny devices that make up the majority of WSNs, or distributed, self-organizing systems. These sensor nodes are able to exchange, perceive, and interpret data. The sensor nodes are equipped with a wide variety of sensors, such as chemical, touch, motion, temperature, and weather sensors. Because of its adaptability, sensors are used in a variety of applications such as automation, tracking, monitoring, and surveillance. Despite the enormous number of sensor applications, WSNs continue to suffer from common challenges like as low memory, slow processing speed, and short network lifetime. The feed forward back propagation neural network mode (FFBPNN) based on meta heuristics aims to create many paths for effective data aggregation in wireless sensor networks. This model handled the process of identifying and selecting the optimum route path. The distributed sensor nodes are utilized to create the various route paths. In this research paper, data aggregation is done using meta-heuristic firefly algorithm that helped in identifying an optimal route from among the found routes. After selecting the operative ideal route choice, the data aggregation procedure practices a rank-based approach to accomplish lower latency and a better packet delivery ratio(PDR). In addition to throughput, simulation was done to improve and measure performance in terms of packet delivery ratio, energy consumption, and end-to-end latency.

show abstract

Routing and Data Aggregation Techniques in Wireless Sensor Networks: Previous Research and Future Scope

Cited by 3 publications

References 29 publications

Computational Approach for Data Aggregation in Wireless Sensor Networks (WSNs)

Computational Approach for Data Aggregation in Wireless Sensor Networks (WSNs)

A Comprehensive Study on Aggregation and Routing Techniques with MATLAB Implementation and QoS Parameter Collection

Energy Efficient Data Aggregation in Wireless Sensor Networks Using Meta Heuristic Based Feed Forward Back Propagation Neural Network Approach

Contact Info

Product

Resources

About