TY  - JOUR
AU  - Gulyás, András
AU  - Bíró, József
AU  - Rétvári, Gábor
AU  - Novák, Márton
AU  - Kőrösi, Attila
AU  - Slíz, Marianna Ilona
AU  - Heszberger, Zalán
TI  - The role of detours in individual human navigation patterns of complex networks
JF  - SCIENTIFIC REPORTS
J2  - SCI REP
VL  - 10
PY  - 2020
IS  - 1
PG  - 10
SN  - 2045-2322
DO  - 10.1038/s41598-020-57856-4
UR  - https://m2.mtmt.hu/api/publication/31146298
ID  - 31146298
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Heszberger, Zalán
AU  - Bíró, József
AU  - Gulyás, András
AU  - László, Balázs
AU  - András, Biró
ED  - Arabnia, Hamid R.
TI  - The Skeleton of Hyperbolic Graphs for Greedy Navigation
T2  - 6th Annual Conference on Computational Science and Computational Intelligence (CSCI 2019)
PB  - American Council on Science and Education
CY  - San Diego (CA)
SN  - 9781728155845
PY  - 2019
SP  - 476
EP  - 480
PG  - 5
SN  - 9781728155845
DO  - 10.1109/CSCI49370.2019.00092
UR  - https://m2.mtmt.hu/api/publication/31249358
ID  - 31249358
AB  - A set of compulsory links in  greedy  navigable  graphs  called  Greedy  Skeleton  is  identified.
LA  - English
DB  - MTMT
ER  - 

TY  - CONF
AU  - Heszberger, Zalán
AU  - Gulyás, András
AU  - Majdán, András
AU  - Bíró, József
TI  - Robust Navigable Cores in the Human Brain Networks
T2  - Dynamics of the brain: temporal aspects of computation
PY  - 2019
SP  - 34
EP  - 34
PG  - 1
UR  - https://m2.mtmt.hu/api/publication/30860091
ID  - 30860091
LA  - English
DB  - MTMT
ER  - 

TY  - CONF
AU  - Heszberger, Zalán
AU  - Majdán, András
AU  - Gulyás, András
AU  - Gyimóthy, Tibor
AU  - Bilicki, Vilmos
AU  - Bíró, József
TI  - Robust Navigable Cores in the Human Brain Networks
T2  - Proc. of The 7th International Conference on Complex Networks and Their Applications
PY  - 2018
SP  - 324
EP  - 326
PG  - 3
SN  - 9783030054144
UR  - https://m2.mtmt.hu/api/publication/30385098
ID  - 30385098
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Tapolcai, János
AU  - Vass, Balázs
AU  - Heszberger, Zalán
AU  - Bíró, József
AU  - Hay, D
AU  - Kuipers, F A
AU  - Rónyai, Lajos
ED  - IEEE, .
TI  - A Tractable Stochastic Model of Correlated Link Failures Caused by Disasters
T2  - IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
PB  - IEEE
CY  - Piscataway (NJ)
SN  - 9781538659793
PY  - 2018
SP  - 2105
EP  - 2113
PG  - 9
DO  - 10.1109/INFOCOM.2018.8486218
UR  - https://m2.mtmt.hu/api/publication/3371218
ID  - 3371218
N1  - Huawei Technologies 
 MTA-BME Lendület Future Internet Research Group, MTA-BME Information Systems Research Group, Budapest University of Technology and Economics (BME), Hungary 
 School of Engineering and Computer Science, Hebrew University, Jerusalem, Israel 
 Delft University of Technology, Netherlands 
 Computer and Automation Research Institute, Hungarian Academy of Sciences and BME, Hungary 
 Conference code: 140725 
 Cited By :2 
 Export Date: 15 December 2018 
 CODEN: PINFE
WoS:hiba:000509768900236 2020-09-02 18:24 befoglaló egyiknél nincsenek szerzők, befoglaló cím nem egyezik
AB  - In order to evaluate the expected availability of a service, a network administrator should consider all possible failure scenarios under the specific service availability model stipulated in the corresponding service-level agreement. Given the increase in natural disasters and malicious attacks with geographically extensive impact, considering only independent single link failures is often insufficient. In this paper, we build a stochastic model of geographically correlated link failures caused by disasters, in order to estimate the hazards a network may be prone to, and to understand the complex correlation between possible link failures. With such a model, one can quickly extract information, such as the probability of an arbitrary set of links to fail simultaneously, the probability of two nodes to be disconnected, the probability of a path to survive a failure, etc. Furthermore, we introduce a pre-computation process, which enables us to succinctly represent the joint probability distribution of link failures. In particular, we generate, in polynomial time, a quasilinear-sized data structure, with which the joint failure probability of any set of links can be computed efficiently.
LA  - English
DB  - MTMT
ER  - 

TY  - JOUR
AU  - Kőrösi, Attila
AU  - Csoma, Attila
AU  - Rétvári, Gábor
AU  - Heszberger, Zalán
AU  - Bíró, József
AU  - Tapolcai, János
AU  - Pelle, István
AU  - Dávid, Klajbár
AU  - Márton, Novák
AU  - Valentina, Halasi
AU  - Gulyás, András
TI  - A dataset on human navigation strategies in foreign networked systems
JF  - SCIENTIFIC DATA
J2  - SCI DATA
VL  - 5
PY  - 2018
PG  - 6
SN  - 2052-4463
DO  - 10.1038/sdata.2018.37
UR  - https://m2.mtmt.hu/api/publication/3350776
ID  - 3350776
N1  - WoS:hiba:000427256400003 2020-08-29 10:16 típus nem egyezik
LA  - English
DB  - MTMT
ER  -