Abstract

Internet of things (IoT) systems are making a significant contribution to the growth of global traffic. There is a tendency towards a decrease in the volume of transmitted and stored data, for which various approaches are used. Most of these approaches involve traditional cloud and gateway processing, leaving the endpoints idle in the process. The article discusses the correlation method of data processing on the end device. The results of the study of the maximum performance when implemented on FPGAs with different orders of the matched filter N and different bit widths of the input data stream are presented. A huge number of devices have been connected to the network for a long time. On the Internet of Things, communication must occur between things (without human intervention). This paper presents a correlation method for processing data on end devices and reducing the amount of data transmitted over the network. Instead of expensive and complex network devices, developers can use cheap and proven low-speed Internet of Things (ZigBee, NB IoT, BLE) solutions for data transfer. The novelty lies in one of the features of this approach: the use of components for analysis, rather than a complete copy of the signals, as well as processing directly on the sensor. The advantage of this approach allows you to reduce the number of operations and complexity of implementation, in contrast to other methods focused on the cloud computing paradigm. We provide results for correlation values and the number of logical elements (LE) when implemented on the FPGA, depending on the number of elements in the correlator. This allows to maintain a balance between the required calculation accuracy and spent hardware resources, as well as to simplify the end device.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.