Accounting mechanisms based on credit are used in peer-to-peer systems to track the contribution of peers to the community for the purpose of deterring freeriding and rewarding good behavior. Most often, peers earn credit for uploading files, but other activities might be rewarded in the future as well, such as making useful comments or reporting spam. Credit earned can be used for accessing new content, or for receiving preferential treatment in case of network congestion. We define credit mining as the activity performed by peers for the purpose of earning credit. In this paper, we design, implement, and evaluate a system for decentralized credit mining that maximizes the contribution of idle peers to the community by automatically uploading popular files. Building on previous theoretical insights into the economics of communities, we select autonomous algorithms for bandwidth investment as the basis of our credit mining system. Additionally, we describe our experience with important challenges arising from Internet deployment, that are frequently neglected in emulation, including duplicate content avoidance, spam prevention, and the cost of keeping peer information updated. Furthermore, we implement an archival mode of operation, which prevents the disappearance of old content from the community. We show the feasibility and usefulness of our credit mining system through measurements from our implementation on top of Tribler, an Internet-deployed peer-to-peer system.
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