https://hdl.handle.net/20.500.12619/2410 2026-04-11T19:12:54Z 2026-04-11T19:12:54Z Sadettin Demir Özçelik, İbrahim https://hdl.handle.net/20.500.12619/69643 2020-10-16T10:27:16Z 2020-01-01T00:00:00Z

A priority-based queuing model approach using destination parameters for real-time applications on IPv6 networks Sadettin Demir; Özçelik, İbrahim In the early days of the Internet architecture, the most important aim is to transmit data over packet switched networks. The traditional Internet architecture used in these networks lacks quality of service. However, today, as real-time applications increase, it is needed. There are approaches to improving the quality of service using the flow label field in the Internet Protocol version 6 header. In this study, a novel algorithm that uses destination network parameters to reduce queuing and end-to-end delay is created. A round-robin-based time-aware priority queue new model is used within this algorithm. Data packets using this proposed queue are prioritized with metric values of the destination network. In order to provide end-to-end service quality, the prioritization value is used by placing it in the flow label field. For this purpose, a new approach to the use of this field is proposed. Delay, one of the most important factors affecting quality of service, is reduced with the proposed algorithm and flow label usage approach. As a result, the reduction in delay times between 22 and 39 ms resulted in various improvement rates between 16.79% and 35.13%.

2020-01-01T00:00:00Z Kaynak, Sümeyye Kaynak, Baran Özmen, Ahmet https://hdl.handle.net/20.500.12619/69644 2020-10-16T10:27:16Z 2020-01-01T00:00:00Z

GPU-Based Dynamic Solar Potential Estimation Tool Using 3D Plans Kaynak, Sümeyye; Kaynak, Baran; Özmen, Ahmet Estimations of the solar potential from the building design files may affect placement considerations in favor of more sunlight reception that reduces the energy costs and saves the environment. In this study, a GPU based system (GPU-DSRM) is proposed to estimate direct and diffuse solar radiation aggregated on 3D structures at urban or individual scale. In the proposed approach, finite element method, back-face detection and ray-tracing algorithms are customized to run in parallel to reduce the execution time. Thus, real-time shadow analysis with adjustable sampling rate and time scale can be performed without compromising precision and accuracy of the estimations. The most important novel aspect of the study is that it can be used anywhere in the world without the need for meteorological data. Some of the test results obtained from a site with 10 buildings are presented in this paper that shows a speedup value of 45 with the new GPU-based implementation compared to the CPU-based model. The GPU-DSRM tool has also been compared with geometric tools in the literature. Solar energy potential analysis of building designs or existing urban formations can be completed faster and more precisely with this new approach.

2020-01-01T00:00:00Z Ovaz Akpınar, Kevser https://hdl.handle.net/20.500.12619/69642 2020-10-16T10:27:16Z 2020-01-01T00:00:00Z

Service-based IoT architecture for vehicular communication (Under Review) Ovaz Akpınar, Kevser

2020-01-01T00:00:00Z Akpınar, Mustafa Yumuşak, Nejat https://hdl.handle.net/20.500.12619/69639 2020-10-16T10:27:15Z 2020-01-01T00:00:00Z

Daily basis mid-term demand forecast of city natural gas using univariate statistical techniques Akpınar, Mustafa; Yumuşak, Nejat City distribution companies or companies with high consumption are required to report monthly consumption demand forecasts for the year ahead and year based daily consumption demand forecasts in natural gas sector. This paper studies forecasting daily and monthly demand for mid-term natural gas as contract estimations using statistical methods (time series decomposition, Holt-Winters exponential smoothing, ARIMA/SARIMA), include univariate seasonality. In the study, 365-day forecast is performed on a daily basis and 12-month forecast is performed on a monthly basis at once. Among all statistically appropriate forecasting models, ARIMA(1,0,1)1(0,1,1)(365) model found daily basis year ahead natural gas consumptions the best with the lowest error, highest compliance with 24.6% MAPE and 0.802 R-2, for the year 2014. The coefficients of this model were statistically significant and the residuals were found as white noise. The same model has the lowest error (MAPE - 11.32%) and highest compliance (R-2 - 0.981) in the monthly estimations as well. The results show that seasonal ARIMA models are the most appropriate estimation technique among the univariate techniques. The fact that many predictions can be made at a time and the results are acceptable allow these techniques to be used in the year ahead monthly and daily forecasting.

2020-01-01T00:00:00Z