scholarly journals The Price of Anarchy in Network Creation Games Is (Mostly) Constant

2010 ◽  
pp. 276-287 ◽  
Author(s):  
Matúš Mihalák ◽  
Jan Christoph Schlegel
Keyword(s):  
Price Of Anarchy ◽  
Network Creation Games

scholarly journals Flow-Based Network Creation Games

2020 ◽  
Author(s):  
Hagen Echzell ◽  
Tobias Friedrich ◽  
Pascal Lenzner ◽  
Anna Melnichenko
Keyword(s):  
Communication Networks ◽  
Network Flow ◽  
Price Of Anarchy ◽  
Simple Algorithm ◽  
Past Research ◽  
Price Of Stability ◽  
Central Position ◽  
Network Nodes ◽  
Strategic Agents ◽  
Network Creation Games

Network Creation Games(NCGs) model the creation of decentralized communication networks like the Internet. In such games strategic agents corresponding to network nodes selfishly decide with whom to connect to optimize some objective function. Past research intensively analyzed models where the agents strive for a central position in the network. This models agents optimizing the network for low-latency applications like VoIP. However, with today's abundance of streaming services it is important to ensure that the created network can satisfy the increased bandwidth demand. To the best of our knowledge, this natural problem of the decentralized strategic creation of networks with sufficient bandwidth has not yet been studied. We introduce Flow-Based NCGs where the selfish agents focus on bandwidth instead of latency. In essence, budget-constrained agents create network links to maximize their minimum or average network flow value to all other network nodes. Equivalently, this can also be understood as agents who create links to increase their connectivity and thus also the robustness of the network. For this novel type of NCG we prove that pure Nash equilibria exist, we give a simple algorithm for computing optimal networks, we show that the Price of Stability is 1 and we prove an (almost) tight bound of 2 on the Price of Anarchy. Last but not least, we show that our models do not admit a potential function.

scholarly journals The price of anarchy in cooperative network creation games

2009 ◽  
Vol 8 (2) ◽  
pp. 1-20 ◽  
Author(s):  
Erik D. Demaine ◽  
Mohammadtaghi Hajiaghayi ◽  
Hamid Mahini ◽  
Morteza Zadimoghaddam
Keyword(s):  
Price Of Anarchy ◽  
Cooperative Network ◽  
Network Creation Games

scholarly journals The Price of Anarchy in Network Creation Games Is (Mostly) Constant

2013 ◽  
Vol 53 (1) ◽  
pp. 53-72 ◽  
Author(s):  
Matúš Mihalák ◽  
Jan Christoph Schlegel
Keyword(s):  
Price Of Anarchy ◽  
Network Creation Games

scholarly journals The price of anarchy in network creation games

2007 ◽  
Author(s):  
Erik D. Demaine ◽  
MohammadTaghi Hajiaghayi ◽  
Hamid Mahini ◽  
Morteza Zadimoghaddam
Keyword(s):  
Price Of Anarchy ◽  
Network Creation Games

scholarly journals The price of anarchy in network creation games

2012 ◽  
Vol 8 (2) ◽  
pp. 1-13 ◽  
Author(s):  
Erik D. Demaine ◽  
Mohammadtaghi Hajiaghayi ◽  
Hamid Mahini ◽  
Morteza Zadimoghaddam
Keyword(s):  
Price Of Anarchy ◽  
Network Creation Games

scholarly journals Network Creation Games with Traceroute-Based Strategies

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 35
Author(s):  
Davide Bilò ◽  
Luciano Gualà ◽  
Stefano Leucci ◽  
Guido Proietti
Keyword(s):  
Communication Networks ◽  
Price Of Anarchy ◽  
Complete Information ◽  
Network Size ◽  
Upper And Lower Bounds ◽  
Small Scale ◽  
Response Dynamics ◽  
Best Response ◽  
Partial View ◽  
Network Creation Games

Network creation games have been extensively used as mathematical models to capture the key aspects of the decentralized process that leads to the formation of interconnected communication networks by selfish agents. In these games, each user of the network is identified by a node and selects which link to activate by strategically balancing his/her building cost with his/her usage cost (which is a function of the distances towards the other player in the network to be built). In these games, a widespread assumption is that players have a common and complete information about the evolving network topology. This is only realistic for small-scale networks as, when the network size grows, it quickly becomes impractical for the single users to gather such a global and fine-grained knowledge of the network in which they are embedded. In this work, we weaken this assumption, by only allowing players to have a partial view of the network. To this aim, we borrow three popular traceroute-based knowledge models used in network discovery: (i) distance vector, (ii) shortest-path tree view, and (iii) layered view. We settle many of the classical game theoretic questions in all of the above models. More precisely, we introduce a suitable (and unifying) equilibrium concept which we then use to study the convergence of improving and best response dynamics, the computational complexity of computing a best response, and to provide matching upper and lower bounds to the price of anarchy.

A microsimulation based analysis of the price of anarchy in traffic routing: The enhanced Braess network case

2021 ◽  
pp. 1-16
Author(s):  
Aleksandr Belov ◽  
Konstantinos Mattas ◽  
Michail Makridis ◽  
Monica Menendez ◽  
Biagio Ciuffo
Keyword(s):  
Price Of Anarchy ◽  
Traffic Routing
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