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Toka László
Network technologies for big data applications

TÉMAKIÍRÁS

Intézmény: Budapesti Műszaki és Gazdaságtudományi Egyetem
informatikai tudományok
Informatikai Tudományok Doktori Iskola

témavezető: Toka László
helyszín (magyar oldal): Távközlési és Médiainformatikai Tanszék
helyszín rövidítés: TMIT


A kutatási téma leírása:

Research objectives:
The evolution of the digital world, the ubiquitous connectivity, and the spreading of "Internet of Things" technologies have led to an extremely steep increase in the amount of data collected from information sources of all kinds, e.g., environmental sensors, user and device logs from IT systems, financial transactions. The gathered information cannot be processed with traditional database solutions within an acceptable timeframe for many data analytics use cases, but novel big data systems are capable of handling huge amount of complex and rapidly changing data. Today big data analytics is one of the fastest developing technological areas: new solutions and tools are emerging every day.

Components of data processing systems, including big data applications, are usually deployed to distributed systems built on server clusters. With the advent of virtualization,
services and applications can be installed in virtual machines or containers and can be run on virtualized infrastructure, instead of on bare metal. Besides of applying virtualization in centralized resources, such as data centers, virtualized computing platform technologies also allow for the exploitation of the benefits of easily running big data applications on geographically scattered infrastructure for processing the data close to where it was generated.

The virtualized technologies running on distributed systems for data analytics applications pose numerous questions and research problems in terms of networking: the research plan involves performance, reliability and economic aspects. The goal is to model, analyze and design high performing big data frameworks that are distributed (in geographical sense) and reliable for applications that will determine the everyday life of society in the near future. The applicant must have a good understanding of data analytics use cases, data mining techniques, big data applications, compute and network virtualization technologies and distributed systems.

előírt nyelvtudás: english
további elvárások: 
Some experience in data analytics, data mining, distributed systems, virtualization, big data

felvehető hallgatók száma: 1

Jelentkezési határidő: 2018-07-31


2020. VI. 25.
ODT ülés
Az ODT következő ülésére 2020. július 10-én 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).

 
Minden jog fenntartva © 2007, Országos Doktori Tanács - a doktori adatbázis nyilvántartási száma az adatvédelmi biztosnál: 02003/0001. Program verzió: 2.2358 ( 2017. X. 31. )