Dynamic analysis of an institutional conflict within the music industry

Peer-to-peer technology has made massive music piracy possible, which, in turn, has arguably had a significant economic impact on the recording industry. Record labels have responded to online piracy with litigation and are also considering self-help measures. It is currently not obvious whether or not these counter-piracy strategies will ultimately stifle online file sharing in the long term. With this paper we attempt to add to our understanding of the conflict within the institution that is the commercial music industry. We conduct an institutional analysis of the industry in transition and extend the traditional pattern modeling methodology with a formal resource-based model of a representative online music network. The model accounts for complex causal interactions between resources, private provision of common goods, free riding and membership dynamics. The numerical implementation of the model is the basis of a decision support system, which is used in a series of computer experiments that emulate anti-piracy scenarios. We show that a peer-to-peer system may be quite resilient to outside disturbances. The experiments also demonstrate that policies rank differently in their effectiveness based on a selected yardstick.Peer-to-peer (P2P) networks; Online File Sharing; Copyright; Simulation

Understanding collaboration in volunteer computing systems

Volunteer computing is a paradigm in which devices participating in a distributed environment share part of their resources to help others perform their activities. The effectiveness of this computing paradigm depends on the collaboration attitude adopted by the participating devices. Unfortunately for software designers it is not clear how to contribute with local resources to the shared environment without compromising resources that could then be required by the contributors. Therefore, many designers adopt a conservative position when defining the collaboration strategy to be embedded in volunteer computing applications. This position produces an underutilization of the devices’ local resources and reduces the effectiveness of these solutions. This article presents a study that helps designers understand the impact of adopting a particular collaboration attitude to contribute with local resources to the distributed shared environment. The study considers five collaboration strategies, which are analyzed in computing environments with both, abundance and scarcity of resources. The obtained results indicate that collaboration strategies based on effort-based incentives work better than those using contribution-based incentives. These results also show that the use of effort-based incentives does not jeopardize the availability of local resources for the local needs.Peer ReviewedPostprint (published version

Converging an Overlay Network to a Gradient Topology

In this paper, we investigate the topology convergence problem for the gossip-based Gradient overlay network. In an overlay network where each node has a local utility value, a Gradient overlay network is characterized by the properties that each node has a set of neighbors with the same utility value (a similar view) and a set of neighbors containing higher utility values (gradient neighbor set), such that paths of increasing utilities emerge in the network topology. The Gradient overlay network is built using gossiping and a preference function that samples from nodes using a uniform random peer sampling service. We analyze it using tools from matrix analysis, and we prove both the necessary and sufficient conditions for convergence to a complete gradient structure, as well as estimating the convergence time and providing bounds on worst-case convergence time. Finally, we show in simulations the potential of the Gradient overlay, by building a more efficient live-streaming peer-to-peer (P2P) system than one built using uniform random peer sampling.Comment: Submitted to 50th IEEE Conference on Decision and Control (CDC 2011

`Q-Feed' - An Effective Solution for the Free-riding Problem in Unstructured P2P Networks

This paper presents a solution for reducing the ill effects of free-riders in decentralised unstructured P2P networks. An autonomous replication scheme is proposed to improve the availability and enhance system performance. Q-learning is widely employed in different situations to improve the accuracy in decision making by each peer. Based on the performance of neighbours of a peer, every neighbour is awarded different levels of ranks. At the same time a low-performing node is allowed to improve its rank in different ways. Simulation results show that Q-learning based free riding control mechanism effectively limits the services received by free-riders and also encourages the low-performing neighbours to improve their position. The popular files are autonomously replicated to nodes possessing required parameters. Due to this improvement of quantity of popular files, free riders are given opportunity to lift their position for active participation in the network for sharing files. Q-feed effectively manages queries from free riders and reduces network traffic significantlyComment: 14 pages, 10 figure

The Economics of Peer-to-Peer Networks

Peer-to-Peer (P2P) networks have emerged as a significant social phenomenon for the distribution of information goods and may become an important alternative to traditional client-server network architectures for knowledge sharing within enterprises. This paper reviews and synthesizes the relevant computer science and economics literatures as they relate to P2P networks, and raises important questions for researchers interested in studying the behavior of these networks from the perspective of the economics of information technology. With regard to the economic characteristics of these networks, we show that while the characteristics of services provided over P2P networks are similar to public goods and club goods, they have many important differences and hence there is a need for new theoretical models as well as empirical and experimental analysis to understand P2P user behavior. We then identify several important areas for study with regard to the economics of P2P networks and review recent academic papers in each area

A new analytical framework for studying protocol diversity in P2P networks

Thanks to years of research and development, current peer-to-peer (P2P) networks are anything but a homogeneous system from a protocol perspective. Specifically, even for the same P2P system (e.g., BitTorrent), a large number of protocol variants have been designed based on game theoretic considerations with the objective to gain performance advantages. We envision that such variants could be deployed by selfish participants and interact with the original prescribed protocol as well as among them. Consequently, a meta-strategic situation - judiciously selection of different protocol variants - will emerge. In this work, we propose a general framework, Migration, based on evolutionary game theory to study the coevolution of peers for selfish protocol selection, and, most importantly, its impact on system performance. We apply Migration to P2P systems and draw on extensive simulations to characterize the dynamics of selfish protocol selection. The revealed evolution patterns shed light on both theoretical study and practical system design. © 2013 IEEE.published_or_final_versio