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Design of FPGA Soft Core Based WSN Node Using Customization Paradigm

Wireless Sensor Network (WSN) has critical design objectives required to consider in sensor node design like power consumption, fault tolerance and security. FPGA is considered as preferred solution to design the sensor node. Thus the work in this paper is focused on soft core built custom component...

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Bibliographic Details
Published in:Wireless personal communications 2022, Vol.122 (1), p.783-805
Main Authors: Patil, Vilabha, Deshpande, Shraddha
Format: Article
Language:English
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Summary:Wireless Sensor Network (WSN) has critical design objectives required to consider in sensor node design like power consumption, fault tolerance and security. FPGA is considered as preferred solution to design the sensor node. Thus the work in this paper is focused on soft core built custom component based paradigm to meet the above mentioned objectives with desired flexibility. It includes new custom component based model for WSN nodes with three customization approaches. In first approach, a unique isolated customization is done for fault tolerance, security, reduction in the size of node affecting power consumption. Second approach deals with design and implementation of selection index based extended custom block, which helps to reduce the overall power and time required for execution. The WSN cooperative custom module is designed in third approach which mitigates to achieve all objectives in single module. A sensor node processing unit for acceleration of complex algorithms is sufficed by the use of NIOS II soft-core processor. The work performance of customized soft core based sensor node is compared to the microcontroller based execution. The results represent the significance of soft core based implementation by enhancement in performance of clock cycle counts. They are required for typical processing unit design objectives built as custom instructions. The customization reduces the overhead of soft core processor, thus the notion of custom instruction is compared with software only implementation of respective processing unit tasks. The results show considerable improvement in performance with energy consumption reduction.
ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-021-08925-y