C. Ganewattha, Z. Khan, J. J. Lehtomäki and M. Matinmikko-Blue, "Real-Time Quantile-Based Estimation of Resource Utilization on an FPGA Platform Using HLS," in IEEE Access, vol. 8, pp. 43301-43313, 2020, doi: 10.1109/ACCESS.2020.2977760
Real-time quantile-based estimation of resource utilization on an FPGA platform using HLS
|Author:||Ganewattha, Chanaka1; Khan, Zaheer1; Lehtomäki, Janne J.1;|
1Centre for Wireless Communications (CWC), University of Oulu, 90014 Oulu, Finland
|Online Access:||PDF Full Text (PDF, 1.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020050725515
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2020-05-07
Hardware accelerated modules that can continuously measure/analyze resource (frequency channels, power, etc.) utilization in real-time can help in achieving efficient network control, and configuration in cloud managed wireless networks. As utilization of various network resources over time often exhibits broad and skewed distribution, estimating quantiles of metrics to characterize their distribution is more useful than typical approaches that tend to focus on measuring average values only. In this paper, we describe the development of a real-time quantile-based resource utilization estimator module for wireless networks. The intensive processing tasks run on the FPGA, while the command and control runs on an embedded ARM processor. The module is implemented by using high level synthesis (HLS) on a Xilinx’s Zynq-7000 series all programmable system on chip board. We test the performance of the implemented quantile estimator module, and as an example, we focus on forecasting congestion with real frequency channel utilization data. We compare the results from the implemented module against the results from a theoretical quantile estimator. We show that with high accuracy and in real time, the implemented module can perform quantile estimation and can be utilized to perform forecasting of congestion in wireless frequency spectrum utilization.
|Pages:||43301 - 43313|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was supported in part by the Business Finland through the MOSSAF Project, and in part by the Academy of Finland through the 6Genesis Flagship under Grant 318927.
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
© The Authors 2020. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/.