Principle Investigator: Prof. Ece Güran Schmidt

Project Manager: Prof. Ece Güran Schmidt (METU), Yük. Müh. Alper Yazar (ASELSAN)

Project Type: TÜBİTAK/ARDEB 1003 – Primary Subjects R&D Funding Program

Project Duration: 36 Months

Project Start Date: April 2018

Funded Personnel: 1 PhD (full-time, 36 months), 2 MSc (full-time, 18 months) student(s)

The data centers of today are mostly cloud based with virtualized servers to provide on-demand scalability and flexibility of the available resources such as CPU, memory, data storage and network bandwidth.  A cloud data center provider may offer resources as IaaS, PaaS and SaaS.

In this respect, it is necessary to maintain a proper mapping of the virtual resources to the underlying physical hardware. This is a particularly difficult task, considering the cloud resource heterogeneity, the unpredictable nature of workload, and the diversified objectives of cloud users. Finally, it is desirable to always select the most appropriate resource type depending on the user requests.

FPGAs increase the popularity of hardware accelerators which can provide better performance and less energy consumption depending on the problem properties and size. To this end, the very recent research focuses on employing hardware resources in cloud based data centers. Integrating hardware resources in the cloud based data center should be seamless, together with virtualization and dynamic resource allocation capabilities.

This project proposes a novel architecture for cloud-based data centers that we call ACCLOUD (ACcelerated CLOUD). The proposed architecture features FPGA hardware resources that can be offered to users in the scope of IaaS, PaaS and SaaS. To this end, we propose augmenting the cloud servers with FPGA as well as to employ standalone FPGA units. The FPGA resources are virtualized using a number of run-time partially reconfigurable regions. We propose to use the OpenStack software framework to allocate these partially reconfigurable regions to the users together with other virtualized computing resources. To this end, the first major contribution of this project is offering hardware resources as IaaS, PaaS and SaaS in the ACCLOUD architecture different from all previous work.

The second major contribution is the entirely novel resource management approach ACCLOUD-MAN that incorporates the hardware resources into the existing CPU, memory, bandwidth and disk resources and coordinates the IaaS, PaaS and SaaS management. To this end, ACCLOUD-MAN achieves near globally optimum resource allocation together with increased performance by employing hardware resources for SaaS whenever appropriate.

The third major contribution of the project is the extensive optimization evaluation, simulation and real test bed implementation and evaluation of ACCLOUD and ACCLOUD-MAN.

The project is proposed in the form of one main project (METU) with one sub-project (ASELSAN) together with competent project teams. The METU project team has experience in research and development of high speed hardware architectures for computer networking and network processing. The ASELSAN project team has experience in the development and implementation of advanced FPGA-based architectures.

Project Coordinator: Assist. Prof. Serdar Kocaman

Project Duration: 36 Months

Project Start Date: 2017

Funded Personnel: 1 PHD and 3 MS Students will be involved.

Today’s common platforms have both electrical and optical components and the signal has to be converted from electrical domain to optical domain and from optical domain to electrical domain at every stage of the link. Furthermore, the electrical wires at their physical limit. Due to these two factors, the new generation systems will include all-optical components as much as it is practical.

In this project, optical modulators and switches will be designed and fabricated. The innovative devices will have a larger spectral width advantage in addition to being all optical. Designed structures will be able to be fabricated in the large foundries that are manufacturing electronic chips. Therefore, there is no additional infrastructure is urgently necessary and this makes the whole process cost efficient.

Project Coordinator: Assoc. Prof. Barış Bayram (ULTRAMEMS)

Project Duration: 36 Months

Project Start Date: 2017

Funded Personnel:Two MS/PhD/engineer (with a BS degree and above) and two undergraduate students will be appointed in the research activities regarding the project.

The proposed project is considered to be competitive in the imaging of microvascular structures and to be a pioneering work in the biomedical health field at international level with outstanding features.

Project Coordinator: Assist. Prof. Ozan Keysan

Project Type: TÜBİTAK/ARDEB 3501 – Career Development Program

Project Duration: 24 Months

Project Start Date: October 2017

Funded Personnel: 1 PhD (half-time) and 1 MSc (full-time) student.

Nowadays, electric motors constitute more than 50% of the total electric consumption. Variable frequency drives (VFD) have become widespread in the industry. Moreover, electric vehicles are expected to be much more common in the next decade. Several control mechanisms which have been achieved via hydraulic systems are now being replaced by electromagnetic systems in the aerospace industry. In addition, sensitive servo drives are substituting for mechanical parts rapidly in the military defense industry. The electric motors are driven by separate drives from outside which are connected via long cables in all these applications. This leads to poor power density (W/kg, W/cm³) values. These applications also require high reliability, redundancy and drives with high fault tolerance.

The aim of this project is to develop an Integrated Modular Motor Drive (IMMD) system where the electric motor and its drive are integrated into a single package. Within this scope:

• The motor and drive will be integrated into a single package which will lead to high power density values (5 kW/liter) which will be very important in electric traction, aerospace and defense industries.
• Both the motor and the drive will be composed of several modules operating in parallel so that the design and control will be more flexible, thermal management will be easier and redundancy of the system will increase.
• Fault tolerance is very important in mission critical systems (aerospace, defense etc.). A fault tolerant system may continue its operation under a faulty condition with reduced power rating. The motor drive system will be able to continue its operation in case one module is faulted thanks to the modularity of the system.

In this project, new generation wide band gap (WBG) Gallium Nitride (GaN) power semiconductor devices will be utilized at high operating frequencies. By doing so, the volume of the motor drive is aimed to be reduced by 30% and the efficiency of the motor drive is aimed to be enhanced by 2% compared to the conventional drives.

All the work within the context of this project are conducted in an open-source manner and can be accessed via https://github.com/mesutto/IMMD. Moreover, the project coordinator is a member of PowerLab research group the website of which is http://power.eee.metu.edu.tr/.

A PhD student is currently working in the project and we are looking for a full-time MSc. scholarship student. 10 undergraduate students are a part of this project with several topics who are performing METU EEE STAR (http://star.eee.metu.edu.tr/current-program/) program and are also members of the sub-research group called Research League (http://power.eee.metu.edu.tr/research-league/).

Project Coordinator: Prof. Nevzat G. Gençer

Project Type: TUBITAK 1001 Scientific and Technological Research Projects Funding Program

Project Duration: 30 Months

Project Start Date: October 2017

Funded Personnel: 1 Post-Doctoral Research Assistant, 3 PhD Students (half-time), 1 PhD Student (full-time), 1 MSc Student (full-time)

Harmonic Motion Microwave Doppler Imaging (HMMDI) is a novel imaging modality to image electrical and mechanical (elastic) properties of body tissues. In the proposed project, it is aimed to accelerate the elapsing time in measurements, improve the accuracy levels in HMMDI and enhance its clinical applications.

Conventional method for breast cancer diagnosis, Mammography, suffers from utilization of ionizing radiation, difficulty in imaging of dense breasts, inconclusive results and patient discomfort. Top and Gencer (2014) proposed the HMMDI method as promising hybrid method for breast cancer detection, which may overcome the limitations of the Mammography. In this method, local vibrations at a focal point are created by focused ultrasound waves. At the same time, a narrowband microwave signal is transmitted to the vibrating region. Due to local vibrations, Doppler component is observed in the spectrum of the received signal. The level of Doppler signal is related to the mechanical and electrical properties of the vibrating region. By scanning the focal region inside the breast volume, HMMDI image of the tissue can be constructed. Technical feasibility of the method has been shown via analytical (Top and Gencer, 2014), numerical and experimental (Top, 2013) (Top et. al, 2016) studies.

In this project, studies for improving accuracy level, safety and accelerating the experimental measurements will be conveyed. In order to improve the sensitivity, the main microwave component in the received signal component will be cancelled out using a active signal cancellation. Spatial accuracy will be improved via utilization of multiple antennas. To decrease the scanning time, feasibility of continuous mechanical scan of the ultrasound probe will be investigated. Numerical studies for investigating electronical scanning of the focus of ultrasound will also be done. In addition, studies for real time monitoring of system safety, such as cavitation onset, and temperature rise will be done using simulations and experimental set-ups. Moreover, by enhancing the hybridization of microwave imaging with HMMDI, dielectric distribution inside the tissue will be monitored yielding a better liability for tumor detection.

The studies will be conducted via phantom materials to investigate the feasibility of HMMDI in breast cancer diagnosis. Overcoming current encountered problems will accelerate the translation of this method to clinical studies. The study can later be developed to be adapted on cancer diagnosis over other tissues (liver, prostate, etc.).

Project Coordinator: Assoc. Prof. Barış Bayram (ULTRAMEMS)

Project Duration: 36 Months

Project Start Date: 2017

Funded Personnel: One MS/PhD and two undergraduate students will be appointed in the research activities regarding the project.

Detection of brain hemorrhage within the first 1.5 hours is critical for a patient to avoid permanent brain damage. However due to their high complexity, high cost devices like MRI and CT can hardly be available in this time frame. This project proposes a method for detection of blood within the brain.

Project Coordinator: Prof. Elif Uysal-Biyikoglu

Project Duration: 36 Months

Project Start Date: October 2017

Funded Personnel: Postdoctoral researcher (12 mo), 2 full time RAs (36 mo, 12 mo), 2 undergraduates (24 mo, 12 mo)

We are witnessing significant change in the structure and quality requirements of data that is transported on communication networks.  Technologies such as control and monitoring systems that run on the Internet, cellular and ad-hoc networks, applications running on social networks, environmental monitoring algorithms of autonomous vehicles, as well as automated decision making in health and finance depend on sufficiently frequent updates  (data packets bearing new samples/measurements/data). The proposed project aims to develop techniques and algorithms that approach theoretical limits of efficiently transporting update packets.

A common performance criterion for applications that depend on updates is how fresh the data at the node that processes the data and forms decisions is. On the other hand, traditionally, optimal design of data networks has been centered on the analysis of throughput and delay.  However, results in recent literature have shown that transmission policies that may be optimal in terms of throughput or delay may be sub-optimal in terms of achieving data freshness.

Age of Information is defined as the amount of time that has elapsed since the most recent update that has been received by the source was generated/sampled at the source, in other words, it  expresses how old the newest update at the receiver is.

The proposed project contains work in three main thrusts. The first is AoI optimal scheduling in single server and multi server queuing models. The second is real time sampling. In preliminary work leading to this project, it has been observed that increasing sampling rate does not always lead to reduction in Age, on the contrary it may sometimes increase it. We will develop a sampling theory for optimizing not only age but also error for remote estimation over a network.

The third stage is implementation and demonstration, that uses a variety of sensors that will collect and sample various physical disturbances (e.g. temperature, humidity, acceleration, motion, image). Wireless access points will collect and forward the data captured by the sensors and send it over the Internet to be processed by an application software, and be used for a remote control/automation system.

Among the expected outputs of the project, the first is groundbreaking scientific contributions in the form of theoretical limits for AoI, optimal sampling in the presence of network delay, and algorithms that approach these limits. The project will include collaboration with MIT and Ohio State University researchers.

Project Coordinator: Assist. Prof. S. Figen Öktem

Project Type: TÜBİTAK/ARDEB 3501 – Career Development Program

Project Duration: 36 Months

Project Start Date: October 2017

Funded Personnel: 1 PhD student (full-time), 1 MSc student (full-time), 2 undergraduate students

Spectral imaging, the sensing of spatial information as a function of wavelength, is a widely used diagnostic technique in diverse fields such as physics, chemistry, biology, medicine, astronomy, and remote sensing. However, the three-dimensional spectral image dataset is required to be obtained using two-dimensional detectors, and this poses intrinsic limitations on the spatio-spectral extent of the technique. For example, for conventional spectral imagers employing wavelength filters, spatial and spectral resolutions are inherently limited by the cost and manufacturability of its optical components.

In this project, we will develop a class of novel spectral imaging techniques that enable capabilities beyond the reach of conventional techniques. Each development will be based on computational imaging. This involves distributing the imaging task between an optical system (containing a photon sieve) and a computational system. The proposed novel optical systems will take multiplexed measurements, and these measurements will then be used in the computational processing unit to digitally form the spectral images by means of solving an inverse problem. Compressive sensing theory and the state-of-the-art image reconstruction approaches will be exploited for this purpose. By building prototypes, the performance of these novel spectral imaging modalities will also be demonstrated experimentally.

The project will include collaboration with University of Illinois at Urbana-Champaign and NASA Goddard Space Flight Center. Moreover, scholarships will be provided to one full-time M.S. and one full-time Ph.D. student as well as two undergraduates. This will enable new researchers in Turkey to join the field of computational imaging, which is an exciting field with several Nobel prizes.

Currently two undergraduate students are involved in the project as part of the METU EE STAR Program (http://star.eee.metu.edu.tr/current-program/), and we are seeking for highly motivated, full-time, M.S. and Ph.D. students to join our team.

Project Coordinator: Assoc. Prof. Barış Bayram (ULTRAMEMS team)

Project Duration: 36 months

Project Start Date: November 2016

Funded Personnel: 2 undergraduate and 1 MS students will engage in the research activities regarding the project.

This new microphone will provide
•Compact size
•High sensitivity
•Low energy consumption
•Durability to acceleration
•Long-term stable performance

Efficiency enhancement of silicon solar cells by photonic up-conversion

Project Coordinator: Assist. Prof. Selçuk Yerci

Project Duration: 24 months

Project Start Date: Jan. 2016

Funded Personnel: Project will be conducted by 1 Ph.D. and 2 M.S. students

Today, over 90% of the solar cells are produced using silicon (Si) material. There are three main reasons for the choice of Si: its relatively low material cost thanks to being the second most earth-abundant element after oxygen, its near-to-ideal band gap, and the well-developed silicon technology that allows advanced fabrication processes. However, silicon solar cells similar to all other solar cells made of single band gap material suffers from two fundamental losses: (1) non-absorbed photons with energies below the band gap of the absorber, and (2) thermalization losses due to the absorption of photons with energies well-above the band gap of the absorber. These fundamental losses can be reduced by spectrum reshaping in which a high energy photon can be converted to two or multiple lower energy photons (down-conversion) and/or two or more low energy photons can be converted to one high energy photon (up-conversion).

"In this project, we aim at increasing the efficiency of bi-facial Si solar cells by reducing the energy losses due to non-absorbed photons." said Selçuk Yerci to summarize the aim of the project. "In this study, first, we will fabricate bi-facial Si solar cells for the first time in Turkey. Next, we will fabricate up-conversion layer at the back of the bi-facial solar cells. Finally, the up-conversion efficiency of the up-converting layer will be enhanced using various photonic structures." 

Other than Asst. Prof. Selcuk Yerci, Prof. Rasit Turan, the director of GUNAM, Assoc. Prof. Ipek Kocer Guler from Cankaya University and Assoc. Prof. Sahin Kaya Ozdemir, a former graduate of EEMB (M.S. 1995 and B.S. 1992), from University of Washington at St. Louis will work as co-PI in the project.

At the moment, 2 undergraduate students are working along the direction of this topic in their STAR project. We are seeking for motivated M.S. and Ph.D. students to join our team.