We describe a practical auditing approach designed to encourage fairness in peer-to-peer streaming. Auditing is employed to ensure that correct nodes are able to receive streams even in the presence of nodes that do not upload enough data (opportunistic nodes), and scales well when compared to previous solutions that rely on tit-for-tat style of data exchange. Auditing involves two roles: local and global. Untrusted local auditors run on all nodes in the system, and are responsible for collecting and maintaining accountable information regarding data sent and received by each node. Meanwhile, one or more trusted global auditors periodically sample the state of participating nodes, estimate whether the streaming quality is satisfactory, and decide whether any actions are required. We demonstrate through simulation that our approach can successfully detect and react to the presence of opportunistic nodes in streaming sessions. Furthermore, it incurs low network and computational overheads, which remain fixed as the system scales.

The use of Java for distributed systems and highavailable applications demands the validation of their fault tolerance mechanisms to avoid unexpected behavior during execution. We present an extension of FIONA (Fault Injector Oriented to Network Applications), a fault injection environment to experimentally validate the dependability of distributed Java applications. The main features of this extension are: its distributed architecture, which allows centralized configuration of multiple faults scenarios, and the support for a wider fault model associated with distributed systems, which includes network partitioning. For monitoring, FIONA supports the collection of log information and includes a helper application to integrate this information in a global log for post-mortem dependability analysis. FIONA is simple to operate, and we expect it will facilitate the conduction of validation experiments by application developers and testers.

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