I received B.S. and M.S. degrees from Bilkent University, Ankara, Turkey, in 2002 and 2005, in electrical and electronics engineering. I received Ph.D. degree from Osaka University, Japan, in information science and technology, in 2008. I am a Specially Appointed Associate Professor at Osaka University. My research interests are computer networks, intra-vehicle networks, software defined networks, AI, optical networks, traffic engineering, and simulation. I have worked on several government funded projects on computer networks and telecommunications in Europe and Japan. I was the recipient of Monbukagakusho Graduate Scholarship from the Ministry of Education, Science, Sports and Culture of Japan between 2005–2008. I received the Best M.S. Thesis Award from IEEE student branch in Turkey in 2005. I was the recipient of "Best Paper Award" at the First International Conference on Evolving Internet (INTERNET 2009). I am an editor of IEEE Technology Policy & Ethics Newsletter of IEEE Future Directions Technical Community. I am serving in the steering committee of International Conference on Evolving Internet. I was the Operations Chair of IEEE World Forum on Internet of Things 2022. I was an editor of IEEE Access Special Issue "Flying Ad Hoc Networks: Challenges, Potentials, Future Applications, and Way Forward". I am a Senior Member of IEEE.
Ph.D. in Information Science and Technology
Dissertation: Design and Performance Evaluation of Small-buffered Optical Packet Switched Networks
M.S. in Electrical and Electronics Engineering on Computer Networks Area
Thesis: Combined Use of Prioritized AIMD and Flow-Based Traffic Splitting for Robust TCP Load Balancing
Summer School organized by European Union
Topic: Routing and Multi-Layer Traffic Engineering in Next Generation IP Networks
B.S. in Electrical and Electronics Engineering
Specially Appointed Associate Professor
Specially Appointed Researcher
Specially Appointed Assistant Professor
Specially Appointed Researcher
• Research Assistant
• Teaching Assistant
• Administrator of computer systems of Department of Electrical and Electronics Engineering
• Administrator of Bilkent University Information Networks Laboratory
My research topics and some selected publications are as follows:
Recently, the innovation in the automotive industry is mostly based on providing new and better services and features by mounting embedded systems called electronic control unit (ECU). ECUs of some features like self-driving systems require transferring large amounts of data with low latency and strict Quality of service (QoS). While Ethernet may be used in the intra-vehicle backbone, satisfying the severe hardware reliability requirements of intra-vehicle networks while providing high-bandwidth and low latency by Ethernet may be costly. As a solution, we proposed a novel optical intra-vehicle backbone network architecture called SiPhON that may have a lower cost and higher reliability in terms of hardware when compared to Ethernet. I proposed dynamic slot scheduling algorithms for SiPhON. By simulating a zone-based intra-vehicle network, I showed that the slot scheduling delays in our architecture are negligibly low when compared with the total delays in an optical TSN Ethernet backbone architecture.
One of the models in the literature for modeling the behavior of the brain is the Bayesian attractor model, which is a kind of supervised machine-learning algorithm. According to this model, the brain assigns stochastic variables to possible decisions (attractors) and chooses one of them when enough evidence is collected from sensory systems to achieve a confidence level high enough to make a decision. We introduced a software defined networking (SDN) framework based on a brain-inspired BAM for identification of the current traffic pattern for the supervision and automation of traffic engineering in Internet of Things (IoT) networks. When a new traffic pattern is identified, the framework updates the routing table in the network and applies virtual network topologies (VNTs) optimized by traffic engineering with network slicing to minimize the maximum link utilization. Later, I implemented brain-inspired BAM framework as an extension on OpenDaylight SDN controller. I built a real SDN demonstration testbed with high-speed SDN-capable switches and routers for emulating an IoT network for surveillance. The brain-inspired BAM framework correctly identified the place of the crowds by only sampling the fluctuating link utilization levels and then applied the optimum routing table for carrying the traffic generated by the crowd. I represented Osaka University by doing demonstrations of “Brain-inspired IoT network control for surveillance” at Combined Exhibition of Advanced Technologies (CEATEC) Exhibition in Chiba Prefecture and Japan IT Week Kansai Exhibition in Osaka Prefecture
I proposed a network architecture that increases the resiliency against distributed denial-of-service (DDoS) attacks by leveraging virtual network functions (VNF) and software defined networking (SDN). The architecture calculates the optimum multipath VNF orchestration by two-stage linear programming (LP) using CPLEX. The simulation results revealed that the architecture highly improves the DDoS traffic absorption rate, while minimizing the performance penalty when the network is not under heavy DDoS attack.
Yuragi, a mathematical neural network model derived from biological systems, was applied to computer networks. The gene regulatory network of cells was modeled as an attractor selection-based neural network and used to control virtual network topologies (VNTs) in optical networks. The attractor VNT candidates are stored in a Hopfield network, which is a kind of recurrent artificial neural network. I designed heuristic algorithms for designing attractor VNTs that are robust against large scale network failures
I designed a hybrid optical network architecture, which uses both path (circuit) and packet switching. It dynamically changes the ratio of path and packet switching wavelengths network-wide according to the traffic characteristics. I showed that it can greatly increase the goodput of large TCP flows, while decreasing the cost and the power consumption.
To the best of my knowledge the simulator that I implemented for this research is the fastest and most scalable simulator for packet level simulation of TCP flows in the literature. I optimized the TCP Cubic simulation code of ns-2 simulator and made it more than 1000 times faster. Some of the simulation results in the paper were obtained by a packet level simulation of a mesh network with around 10 billion (10^10) TCP Cubic flows
Using a M∕G∕c∕c Markov chain queuing model, I proposed an analytical model for calculating the circuit blocking probabilities and reservation delays in circuit switching optical WDM networks. I showed that the analytical model is the most accurate one in the literature
In my Ph.D. thesis, I challenged the famous rule of thumb, which states that network routers require a buffer size of Bandwidth*RTT to achieve high utilization with TCP flows. I proposed novel network architectures, which greatly decrease the buffering requirements of both electronic and optical networks. After my Ph.D., I continued working on evaluating and further decreasing the buffer requirements of both electronic and optical networks
The effects of the number of justifiers on TCP performance in an optical burst switching (OBS) network were examined in this work. I designed and implemented an advanced optical burst network simulator on ns-2 for this project and released its source code on the Internet available here. My simulator is used by many papers in literature. A survey paper selected my simulator as the most advanced OBS simulator among all related free and commercial simulators including OPNET simulator, which cost more than 10,000 dollars at that time.
In my master’s thesis, I proposed a network architecture for electronic networks using TCP load balancing and multi-path routing based on queuing delays. I showed that the architecture consistently outperforms the single-path routing policy and provides substantial TCP per-flow goodput gains. My master’s thesis won the Best Master’s Thesis Award of IEEE Turkey Student Branch in Bilkent University.
I proposed a biologically inspired attractor selection algorithm to design efficient integrated nanophotonic devices. The 3D FDTD analyses showed that the designed photonic integrated devices have compact sizes, high efficiencies, and compatibility with CMOS fabrication technology
The source code of SiPhON (Si-Photonics-Based In-Vehicle Optical Network) simulator extension that I implemented for OMNEST/OMNeT++ simulator is here. It was presented and used in "A Zone-based Optical Intra-Vehicle Backbone Network Architecture with Dynamic Slot Scheduling" journal paper .
The source code of OBS (optical burst switching) extension that I implemented for ns-2 simulator is here. The new version is updated for ns2.35. It was presented and used in "nOBS: an ns2 based simulation tool for performance evaluation of TCP traffic in OBS networks" journal paper available here.
The ns-2 simulator module and simulation scripts that I implemented for the simulations in the paper "Combined use of prioritized AIMD and flow-based traffic splitting for robust TCP load balancing," are here. The paper is here.
The source code and executables of the encoder and the differential cryptanalysis key finder programs that I implemented for the MacGuffin block cipher algorithm are here. The encoder program creates 100000 random cyphertext plaintext pairs by encrypting with 8-block MacGuffin cipher algorithm with 128-bit input key and the findkey program calculates the secret subkeys of the encrypted ciphertexts by differential cryptanalysis.
Advanced Network Architecture Laboratory,
Graduate School of Information Science and Technology,
Osaka University,
1-5 Yamadaoka, Suita,
Osaka 565-0871, Japan
a-onurist.osaka-u.ac.jp