Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/23124
DC FieldValueLanguage
dc.contributor.authorUtkovski, Zoranen_US
dc.contributor.authorGajduk, Andrejen_US
dc.contributor.authorBasnarkov, Laskoen_US
dc.contributor.authorBosnakovski, Darkoen_US
dc.contributor.authorKocarev, Ljupchoen_US
dc.date.accessioned2022-09-27T09:08:33Z-
dc.date.available2022-09-27T09:08:33Z-
dc.date.issued2014-05-16-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/23124-
dc.description.abstractWe develop a game-theoretic framework to investigate the effect of cooperation on the energy efficiency in wireless networks. We address two examples of network architectures, resembling ad-hoc network and network with central infrastructure node. Most present approaches address the issue of energy efficiency in communication networks by using complex algorithms to enforce cooperation in the network, followed by extensive signal processing at the network nodes. Instead, we address cooperative communication scenarios which are governed by simple, evolutionary-like, local rules, and do not require strategic complexity of the network nodes. The approach is motivated by recent results in evolutionary biology which suggest that cooperation can emerge in Nature by evolution, i. e. can be favoured by natural selection, if certain mechanism is at work. As result, we are able to show by experiments that cooperative behavior can indeed emerge and persist in wireless networks, even if the behavior of the individual nodes is driven by selfish decision making. The results from this work indicate that uncomplicated local rules, followed by simple fitness evaluation, can promote cooperation and generate network behavior which yields global energy efficiency in certain wireless networks.en_US
dc.relation.ispartofarXiv preprint arXiv:1405.4120en_US
dc.titleOn Energy-efficiency in Wireless Networks: A Game-theoretic Approach to Cooperation Inspired by Evolutionary Biologyen_US
dc.typeJournal Articleen_US
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles
Files in This Item:
File Description SizeFormat 
1405.4120.pdf914.4 kBAdobe PDFView/Open
Show simple item record

Page view(s)

26
checked on Jul 24, 2024

Download(s)

3
checked on Jul 24, 2024

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.