Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/23112
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Gajduk, Andrej | en_US |
dc.contributor.author | Utkovski, Zoran | en_US |
dc.contributor.author | Basnarkov, Lasko | en_US |
dc.contributor.author | Kocarev, Ljupcho | en_US |
dc.date.accessioned | 2022-09-27T07:24:56Z | - |
dc.date.available | 2022-09-27T07:24:56Z | - |
dc.date.issued | 2014-05-12 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/23112 | - |
dc.description.abstract | Energy efficiency is gaining importance in wireless communication networks which have nodes with limited energy supply and signal processing capabilities. We present a numerical study of cooperative communication scenarios based on simple local rules. This is in contrast to most of the approaches in the literature which enforce cooperation by using complex algorithms and require strategic complexity of the network nodes. The approach is motivated by recent results in evolutionary biology which suggest that, if certain mechanism is at work, cooperation can be favored by natural selection, i. e. even selfish actions of the individual nodes can lead to emergence of cooperative behavior in the network. The results of the simulations in the context of wireless communication networks verify these observations and indicate that uncomplicated local rules, followed by simple fitness evaluation, can generate network behavior which yields global energy efficiency. | en_US |
dc.publisher | IEEE | en_US |
dc.title | Energy-efficiency in decentralized wireless networks: A game-theoretic approach inspired by evolutionary biology | en_US |
dc.type | Proceeding article | en_US |
dc.relation.conference | 2014 12th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt) | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
Appears in Collections: | Faculty of Computer Science and Engineering: Conference papers |
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1405.3491.pdf | 656.09 kB | Adobe PDF | View/Open |
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