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This study has been done to monitor the network traffic using a software defined network controller. For this purpose, Floodlight was used as the controller and Eclipse was used as the development platform. In order to increase the accuracy, the statistical information on packets was obtained after observing five separate topologies. The statistical data were processed on MATLAB and the desired data sets were created. These data sets are used in artificial neural networks via nntool on MATLAB to predict the packet flow at a particular time. Artificial neural networks were tested on five separate topologies and their accuracies were tested with MAPE and R2 functions. The optimization operations were applied to the topology having the highest accuracy derived from the performed tests. For this purpose, the optimization tests were verified by four optimization techniques which were linear search, tabu search, modified tabu search and combination algorithm (simulated annealing-tabu search). As a result, with the optimization performed with the proposed combination algorithm, the densest route was determined at the smallest time duration., Bu çalışma yazılım tanımlı ağ denetleyicisi kullanarak ağ trafiğini takip etme amacıyla yapılmıştır. Bu doğrultuda denetleyici olarak Floodlight ve çalışma platformu olarak Eclipse kullanılmıştır. Doğruluğu artırmak adına beş ayrı topoloji üzerinde gerçekleştirilen takipler sonrasında paket istatistik bilgileri elde edilmiştir. İstatistik verileri MATLAB üzerinde işlenerek istenilen veri setleri oluşturulmuştur. Bu veri setleri MATLAB’de yer alan nntool vasıtasıyla yapay sinir ağlarında kullanılarak belirli zamanlardaki paket akışı tahmin edilmiştir. Yapay sinir ağları beş ayrı topoloji üzerinde denenmiş ve doğrulukları MAPE ve R2 denklemleri ile test edilmiştir. Yapılan testler sonucunda doğruluğu en yüksek çıkan topoloji üzerinde optimizasyon işlemleri uygulanmıştır. Bu amaç doğrultusunda doğrusal arama, tabu arama, değiştirilmiş tabu arama ve tavlama benzetimi ile tabu arama algoritmasının karışımı olmak üzere toplamda dört ayrı optimizasyon tekniği ile optimizasyon testleri gerçekleştirilmiştir. Sonuç olarak çalışmada önerilen karışım algoritması ile gerçekleştirilen optimizasyon sonucunda en yoğun olan güzergâh en kısa sürede tespit edilmiştir.

26th IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 02-05, 2018 -- Izmir, TURKEY, WOS:000511448500513, Advantages of Software Defined Networks (SDN) technology, which decouples control and transmission planesof computer networks, provides the infrastructure that can help to improve the system performance of video streaming applications, one of today's popular Internet applications. The SDN controller may assist the clients by using the network statistics while determining the routes of the appropriate streaming paths in the physical network in this study, a layered video streaming architecture is proposed, in which SDN controller recommends a server, video codec, and the optimal number of video layers to clients, with taking into account the server load and network status. Performance of the proposed system is given comparatively and it has been shown that the system parameters considered can help to improve the video streaming system performance., IEEE, Huawei, Aselsan, NETAS, IEEE Turkey Sect, IEEE Signal Proc Soc, IEEE Commun Soc, ViSRATEK, Adresgezgini, Rohde & Schwarz, Integrated Syst & Syst Design, Atilim Univ, Havelsan, Izmir Katip Celebi Univ

In traditional networking architecture, for each problem a specific protocol is dedicated to network devices and these devices are configured manually. Since they are hardware-based, the implementation of new ideas and technologies to these devices is very difficult. However, today's increasing use of smartphones and other mobile data devices has increased the data traffic, and with the addition of service diversity and the needs of users, the existing network structure has become much more complex. Software Defined Networks (SDN) is a new network paradigm that allows a programmable central controller mechanism which separates the control plane from the data plane. With the advantage of a centralized control mechanism, SDN ensures that network structures can respond more quickly to current demands, be more flexible and reprogrammable. In addition, all these processes are implemented at a lower cost compared to traditional networking architecture. To evaluate the performance of SDN architectures, testbeds are used by researchers. In this paper, a small-scale and cost-effective SDN testbed is designed and implemented. The testing environment is realized using Raspberry Pi 3, Floodlight and Open vSwitch. Controller performance has been observed with the MACtracker application.