Peer-to-peer protocols that rely on fully random peer and chunk selection have recently been shown to suffer from instability. The culprit is referred to as the missing piece syndrome, whereby a single chunk is driven to near extinction, leading to an accumulation of peers having almost complete files, but waiting for the missing chunk. We investigate three distributed random peer sampling protocols that tackle this issue, and present proofs of their stability using Lyapunov function techniques. The first two protocols are based on the sampling of multiple peers and a rare chunk selection rule. The last protocol incorporates an incentive mechanism to prevent free riding. It is shown that this incentive mechanism interacts well with the rare chunk selection protocol and stability is maintained. Besides being stable for all arrival rates of peers, all three protocols are scalable in that the mean upload rate of each peer is bounded uniformly independent of the arrival rate.