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NEWS

Patent Success from CMPE

Assoc. Prof. Arda Yurdakul, Assoc. Prof. Alper Sen, and Dogan Fennibay were awarded a patent titled "An Integration System". This patent is the first of its kind in Turkey. Read more...
BU/CmpE team wins the Physical Load Sub-Challenge Award at INTERSPEECH Computational Paralinguistics Challenge

Our students Heysem Kaya and Tuğçe Özkaptan under the supervision of Albert Ali Salah and Fikret Gurgen won the Pysical Load Sub-challenge of the Computational Paralinguistics Read more...

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CmpE Events

Friday, May 27th

  1. MS Thesis Defense - Meliksah Turker - Multi-layer Network Approach in Modeling Epidemics in an Urban Town
    • Start time: 10:00am, Friday, May 27th
    • End time: 11:00am, Friday, May 27th
    • Where: Zoom
    • The last two years have been an extraordinary time with the Covid-19 pandemic killing millions, affecting and distressing billions of people worldwide.  Authorities took various measures such as turning school and  work to remote and prohibiting social relations via curfews.  In order to mitigate the negative impact of the epidemics, researchers tried to estimate the future of the pandemic for different scenarios, using forecasting techniques and epidemics simulations on networks. Networks used in these research are either synthetic networks or real networks with limited size and domain specific interactions.  Hence, their ability to represent the world is limited.Intending to represent real-life in an urban town in high resolution, we propose a parametric multi-layer undirected weighted network model, where vertices are the individuals of a town that tend to interact locally, and edges represent transmission probability.  Each layer corresponds to a different interaction that occurs daily,  such as ``household'', ``work'' or ``school'', with their own transmission probability. Our simulations indicate that locking down “friendship” layer  has the highest impact in slowing down epidemics. Hence, our contributions are twofold, first we propose a parametric network generator model; second, we run SIR simulations on it and show the impact of layers.

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Friday, June 3rd

  1. MS Thesis Defense - Kerim Gökarslan - Achieving Ultra-Reliable Low Latency (URLLC) in Next-Generation Cellular Networks with Programmable Data Planes
    • Start time: 01:30pm, Friday, June 3rd
    • End time: 02:30pm, Friday, June 3rd
    • Where: Zoom
    • Recent advancements in wireless technologies towards the next-generation cellular networks have brought a new era that made it possible to apply cellular technology on traditionally-wired networks with tighter requirements, such as industrial networks. The next-generation cellular technologies (e.g., 5G and Beyond) introduce the concept of ultra-reliable low-latency communications (URLLC). This thesis presents Software Defined Networking (SDN) architecture with programmable data planes for the next generation cellular networks to achieve URLLC. Our design deploys programmable switches between the cellular core and Radio Access Networks (RAN) to monitor and modify data traffic at the line speed. We introduce the concept of intra-cellular optimization, a relaxation in cellular networks to allow pre-authorized in-network devices to communicate without being required to signal the cellular core network. We also present a control structure, Unified Control Plane (UCP), containing a novel Ethernet Layer control protocol and an adapted version of link-state routing for user equipment (UE) information distribution among the programmable switches. We implement our proposed architecture using P4 with a 5G implementation (Open5Gs) and a UE/RAN simulator. We further implement a Python simulator to evaluate the performance of our system on multi-switch topologies by simulating the switch behavior. Our extensive evaluation indicates latency reduction up to 2xwith intra-cellular optimization compared to the conventional architecture. We finally show that our design has a ten-millisecond level of control latency, and achieves fine-grained network security and monitoring capabilities.

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Department of Computer Engineering, Boğaziçi University,
34342 Bebek, Istanbul, Turkey

  • Phone: +90 212 359 45 23/24
  • Fax: +90 212 2872461
 

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