I have received my PhD degree in Computer Engineering from Boğaziçi University in 2001. After working as a post-doc for 18 months in Broadband and Wireless Networking Lab at Georgia Institute of Technology, I was appointed as a visiting professor at Georgia Institute of Technology - Savannah Campus for two years. Currently, I am a professor in the Department of Computer Engineering at Boğaziçi University. I am a faculty member of the Computer Networks Research Lab (NetLab). I also take part in Telecommunications and Informatics Technologies Research Center (TETAM) in Kandilli Campus of Boğaziçi University and the associated TAM project funded by the State Planning Organization of Turkey (DPT).
My research interests include wireless networks, with the emphasis on Cognitive Radio and 5G Networks, as well as Molecular Communications and NanoNetworking. You may follow the "Research" link on the left for my past and present projects.
You may access directly to our emulators (developed by my students) on several topics in Molecular Communications by following the links below. You may run the emulators with the default parameters or you may modify the parameters as you wish.
- Emulator for Communication via Diffusion (CvD) & Brownian Motion (thanks to Sinan Narmanlı & Murat Güvenç)
- Emulator for Calcium Signaling (thanks to Sinan Narmanlı & Murat Güvenç)
- Emulator for Neuromuscular Junctions (NMJ) (thanks to Helin Ece Akgül)
- Emulator for Protrusions (thanks to Helin Ece Akgül)
Also, you may find a simple emulator that explains how instructions are executed in the CPU. This emulator was developed by a high school student, Oktay Çomu from Robert College. It aims to give a broad sense of instruction execution; it does not show exact instruction execution process. It starts with a default set of instructions loaded in the memory cells, but you may modify them by changing the content of the cells in the lower left.
Novel Network Coding Applications for Diffusion-Based Molecular Nanonetworks
Optimal Cooperator Set Selection in Social Cognitive Radio Networks
ISI-Aware Modeling and Achievable Rate Analysis of the Diffusion Channel
Analyzing the achievable rate of molecular communication via diffusion (MCvD) inherits intricacies due to its nature: MCvD channel has memory, and the heavy tail of the signal causes inter-symbol interference (ISI). Therefore, using Shannon’s channel capacity formulation for memoryless channel is not appropriate for the MCvD channel. Instead, a more general achievable rate formulation and system model must be considered to make this analysis accurately. In this letter, we propose an effective ISI-aware MCvD modeling technique in 3-D medium and properly analyze the achievable rate.
Optimal Cooperator Set Selection in Social Cognitive Radio Networks
While there is a huge body of research on cooperative spectrum sensing in cognitive radio networks (CRN), incentives for cooperative behavior or the conditions under which cooperation is more likely are not explored. We model cooperation among cognitive radios (CRs) as a function of social ties among CRs. In this social CRN where CRs do not necessarily fulfill every cooperative sensing request, we focus on the cooperator set selection problem, i.e. which CRs to ask for cooperation so that resulting throughput and sensing accuracy are maximized subject to detection and false alarm probability constraints. For single channel scenario, we devise a multi-objective optimization model and obtain the solution using an evolutionary multi-objective algorithm. Our evaluations show that our solution is near-optimal in terms of throughput under legitimate operation, i.e., no malicious users, whereas it outperforms expected-throughput-optimal scheme in case of attackers. Numerical analysis demonstrates the robustness of our proposal with little loss of performance when the network is subject to common sensing attacks. In addition, our analysis underlines one significant drawback of existing works: assuming all CRs to be cooperative leads to a substantial overestimation of throughput capacity. Finally, to tackle the increasing complexity under multi-channel setting, we propose a heuristic for multichannel cooperative sensing for the considered social CRN.
Optimized Sensor Network for Transmitter Localization and Radio Environment Mapping
This course provides an introduction to computer programming using the C language. It is a required course for all Faculty of Engineering students (except for CMPE students who should register the Java section) as well as CET and MATH students. Students from other departments may take the course subject to availability (via consent of the instructor). There is no web site for this course. All course content will be managed through Teaching.Codes system. You will have access to Teaching.Codes when you register the course.
All course content is accessible via Teaching.Codes system, not BOUN-Moodle. Lecutres, labs, and PS will be taught via Teaching.Codes as well as all exams and quizzes. So, make sure that you install Teaching.Codes plug-in to Eclipse.
This course introduces basic data structures concepts together with the object oriented programming paradigm. The course is intended solely for CMPE students who have taken CMPE150 in Java.
All course content is accessible via Teaching.Codes system, not BOUN-Moodle. Lectures, labs, and PS will be taught via Teaching.Codes as well as all exams and quizzes. So, make sure that you install Teaching.Codes plug-in to Eclipse.
Broadband Wireless Networks course is being video recorded. To access the lecture videos, you may:
Follow my channel on YouTube.
Students registered for the course may access the lecture notes via BOUN-Moodle.
Though nanotechnology has been a hot topic for nearly a decade, nano-machines are still far from achieving complicated tasks. Therefore, collaborative operation of nano-machines is a must for nanotechnology. Nanonetworking, i.e., communication between nano-machines, is an emerging technology that enables communication at the nanoscale.
This course aims introducing concepts and research topics on communications and networking issues among nano-machines. We will cover nanoscale communication networks ranging from molecular motors for intra-cell communication to diffusion and gap junctions for inter-cell communications. We will also have a brief look at carbon nanotube-based nanonetworks. Our focus will be mostly on bio-hybrid approaches.
Lecture notes and additional material is available to registered students of the course via BOUN-Moodle.
Professor, Advisor to the Rector
Snail Mail address:
Department of Computer Engineering
34342 Bebek, Istanbul, TURKEY
Office: BM 43 (North Campus)