The peer-to-peer paradigm can harness the resources of edge devices while reducing dependence on centrally operated servers and infrastructure. To maintain the quality of peer-to-peer systems, monitoring and management mechanisms are required to provide reliable services despite unreliable, autonomous, and potentially insecure nodes. In this paper we present a monitoring and management framework for structured peer-to-peer systems, termed SkEyeNet, that enables the system to monitor its behaviour and to adapt to the current status of demand. It captures the current state of a peer-to-peer network using an aggregated statistical representation. Following the principles of autonomic computing, the system automatically adapts its configuration when deviations from predefined quality targets are detected. Evaluation shows that the monitoring is precise and lightweight and that preset quality goals are reached and kept automatically.

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