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DTSTART:20260329T030000
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DTSTAMP:20260513T182220Z
UID:1780488000@ist.ac.at
DTSTART:20260603T140000
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DESCRIPTION:Speaker: Antoine El-Hayek\nhosted by Georgios Katsaros\nAbstrac
 t: Networks can change over time. Whether it is the Facebook network\, whe
 re 'friendships' emerge or end\, the internet\, where computers connect or
  disconnect from the network\, or the train network\, where new lines can 
 be created or canceled. This creates specific challenges for algorithms de
 signed to either run or manage these 'dynamic' networks.A distributed algo
 rithm is an algorithm that runs on the network. Think of the internet: for
  computers to communicate through this network\, the algorithm should be i
 nstalled on both computers\, and both computers won't necessarily have acc
 ess to the same information. If the network is unstable\, or is simply dyn
 amic\, the communication between them can drop at any point\, and the algo
 rithm should be robust to such changes. In this model\, we look at two pro
 blems: the broadcast problem\, where one computer tries to send a message 
 to every single other computer on the network\, and the majority problem\,
  where initially each computer is given an opinion among k possible ones\,
  and the goal is for every computer to know which opinion was originally t
 he most popular one.A dynamic graph algorithm is an algorithm that manages
  a dynamic network\, or computes a property on it. Think of the network of
  webpages. You might want to rank all webpages from the most important one
  to the least (popular search engines call it the 'PageRank' algorithm). H
 owever\, every day\, new pages go online\, while old pages go offline. You
  wouldn't want the algorithm to be run from scratch every night over all o
 nline webpages\, as this would cost too much energy. Instead\, you would l
 ike to have an algorithm that\, once it has computed the rank of each webp
 age at a given time\, be able to handle a few changes\, and update its sol
 ution accordingly. In the dynamic graph algorithm model\, we look at the m
 inimum cut problem\, where the goal is is divide the network into two subn
 etworks\, such that the number of connections from one subnetwork to the o
 ther is minimized.
LOCATION:Moonstone Bldg / Ground floor / Seminar Room F (I24.EG.030f) and Z
 oom\, ISTA
ORGANIZER:
SUMMARY:Antoine El-Hayek: Thesis Defense: Handling Updates and Failures: Dy
 namic Graph Algorithms and Distributed Computing on Dynamic Networks
URL:https://talks-calendar.ista.ac.at/events/6452
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