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Erschienen in:
Optimization of Network Mapping for Screening and Intrusion Sensing Devices Kapitel lesen Erstes Kapitel lesen

2024 | OriginalPaper | Buchkapitel

Congestion Management Techniques in WSNs: A Comparative Study

verfasst von : Ajai Kumar, D. K. Lobiyal

Erschienen in: Cryptology and Network Security with Machine Learning

Verlag: Springer Nature Singapore

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Abstract

Wireless sensor network (WSN) is an interconnection of numerous sensor nodes with autonomous processing and communication capability. Sensor nodes collect data from the surroundings and transmit it to an endpoint receiver which is known as a sink, so that appropriate decisions can take place. WSN has resource constraints in terms of bandwidth, energy, storage, and processing. Due to limited resources, congestion may occur in WSN. Congestion is one of the serious issues in the network which is degrading the performance of the network and quality of service (QoS). Some factors like packet collision, channel contention, and data transmission in many-to-one fashions become the catalyst for congestion and result in packet drop. Many researchers provided different solutions to solve the issue, but congestion is still a serious problem. Therefore, more specialized strategies are required to manage congestion. In this paper, we have investigated various congestion detection and management methods and compared them based on queue, priority, source management, traffic management, packet service time, channel load, and buffer occupancy.

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Metadaten
Titel
Congestion Management Techniques in WSNs: A Comparative Study
verfasst von
Ajai Kumar
D. K. Lobiyal
Copyright-Jahr
2024
Verlag
Springer Nature Singapore
Buch
Cryptology and Network Security with Machine Learning

Print ISBN: 978-981-9706-40-2

Electronic ISBN: 978-981-9706-41-9

Copyright-Jahr: 2024

DOI
https://doi.org/10.1007/978-981-97-0641-9_18

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