A scalable content-addressable network
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Chord: a scalable peer-to-peer lookup protocol for internet applications
IEEE/ACM Transactions on Networking (TON)
Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems
Middleware '01 Proceedings of the IFIP/ACM International Conference on Distributed Systems Platforms Heidelberg
Robust incentive techniques for peer-to-peer networks
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Real-world oriented information sharing using social networks
GROUP '05 Proceedings of the 2005 international ACM SIGGROUP conference on Supporting group work
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
SLACER: A Self-Organizing Protocol for Coordination in Peer-to-Peer Networks
IEEE Intelligent Systems
Indirect partner interaction in peer-to-peer networks: stimulating cooperation by means of structure
Proceedings of the 8th ACM conference on Electronic commerce
Communications of the ACM
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We investigate how to ensure efficiency (in the economic sense of the word) in structured networks, with a focus on heterogeneity. A network is structured if the network designer has predefined some relationships between individuals (aka. nodes). Structured networks have turned out to be surprisingly efficient – at least as long as nodes face the same costs and benefits, i.e., are homogeneous [25]. However, the homogeneity assumption is unnatural and restrictive. Economic experiments in general (not with a focus on structured networks) suggest that heterogeneity is in the way of efficiency, i.e., reduces the sum of all payoffs. This is because individuals favor outcomes where everybody earns the same. This paper describes behavioral experiments that investigate this issue, i.e., the influence of heterogeneity on efficiency in structured networks. We show that most nodes in structured networks cooperate even if they earn less than others. Our explanation is that – with our design – competition enhances cooperation. This effect is rarely observed with other networks as well as in other, less specific settings where competition is in the way of cooperation. This result is an important step towards establishing networks that yield more tangible payoffs for its nodes.