Int. J. Computer Applications in Technology,Vol. 29, No. 1, 2007 71 INCA: qualitative reference framework for incentive mechanisms in P2P networks Andrew Roczniak,* Abdulmotaleb El Saddik and Pierre Lévy Multimedia Communications Research Laboratory and Collective Intelligence Laboratory, University of Ottawa, Ottawa, Canada E-mail: roczniak@mcrlab.uottawa.ca *Corresponding author Abstract: The existence of peer-to-peer networks is due to benefits brought by decentralisation of control and distribution of resources. It is expected that the usage of such networks will grow and provide support for a variety of applications, including collaborative environments. Since entities participating in those networks are autonomous and therefore free to decide on their level of participation, mechanisms to resolve conflicts between individual and collective rationality are needed. How can implementations of such mechanisms be compared? This paper introduces INCentive frAmework (INCA), a qualitative reference framework, highlighting essential elements and major design decisions in any implementation of incentive mechanisms. In the context of collaborative environments built on top of P2P architectures, the reference framework can be used in assessing the impact on the quality of experience of applications when incentive mechanisms are included. Keywords: collaborative environments; peer-to-peer systems; incentives. Reference to this paper should be made as follows: Roczniak, A., El Saddik, A. and Lévy, P. (2007) ‘INCA: qualitative reference framework for incentive mechanisms in P2P networks’, Int. J. Computer Applications in Technology, Vol. 29, No. 1, pp.71–80. Biographical notes: Andrew Roczniak is pursuing his PhD in Electrical Engineering at the University of Ottawa. His research interests include peer-to-peer systems, multimedia communication systems and distributed computing. Abdulmotaleb El Saddik is an Associate Professor in the School of Information Technology and Engineering (SITE). He is the Director of the Multimedia Communications Research Laboratory (MCRLab) and the Director of Information Technology Cluster, Ontario Research Network on Electronic Commerce (ORNEC). He received an MSc (Dipl-Ing) and a PhD (Dr-Ing) in Electrical Engineering and Information Technology from Darmstadt University of Technology, Germany in 1995 and 2001, respectively. He has authored or co-authored two books and more than 70 publications in the areas of software engineering development of multimedia artefacts and collaborative virtual environments. He is a Senior Member of IEEE and a recent winner of the prestigious Canadian Premier’s Research Excellence Awards (PREA). Pierre Lévy is a full-time Professor in the Department of Communication at the University of Ottawa, Fellow of the Royal Society of Canada, Canada Research Chair in Collective Intelligence and Director of the Collective Intelligence Laboratory at the University of Ottawa. He is the author of 12 books, including ‘Collective Intelligence’ and numerous scientific papers. 1 Introduction In contrast to a client-server model where servers provide services to clients, a Peer-to-Peer (P2P) model dictates that an entity should act both as a server and a client with respect to other entities. If providing a service entails costs, then the entity acting as a server should expect some form of compensation or, more generally, should have an incentive to offer this service. Incentive mechanisms are however neither fully understood, nor effectively deployed on existing popular P2P networks, with the result that many entities choose to act solely as clients (free-riders) (Adar and Huberman, 2000). Although incentive mechanisms are well documented in business, economy and sociology literature (Bamberg and Spremann, 1989), their application to P2P networks is relatively new. Issues such as improvement of cooperation using techniques from economics and social sciences, applicability of various market models and viability of different revenue models in P2P networks were recently addressed in Strulo et al. (2003), Senior and Deters (2002) and Hummel et al. (2003). The fundamental difficulty in deploying incentive mechanisms rests in ensuring that they are resilient to failures and robust against malicious entities (Feldman et al., 2004). Since entities are expected to be independent and rational, there is no guarantee that Copyright © 2007 Inderscience Enterprises Ltd.