A new stable peer-to-peer protocol with non-persistent peers

Abstract

Recent studies have suggested that the stability of peer-to-peer networks may rely on persistent peers, who dwell on the network after they obtain the entire file. In the absence of such peers, one piece becomes extremely rare in the network, which leads to instability. Technological developments, however, are poised to reduce the incidence of persistent peers, giving rise to a need for a protocol that guarantees stability with non-persistent peers. We propose a novel peer-to-peer protocol, the group suppression protocol, to ensure the stability of peer-to-peer networks under the scenario that all the peers adopt non-persistent behavior. Using a suitable Lyapunov potential function, the group suppression protocol is proven to be stable when the file is broken into two pieces, and detailed experiments demonstrate the stability of the protocol for arbitrary number of pieces. We define and simulate a decentralized version of this protocol for practical applications. Straightforward incorporation of the group suppression protocol into BitTorrent while retaining most of BitTorrent's core mechanisms is also presented. Subsequent simulations show that under certain assumptions, BitTorrent with the official protocol cannot escape from the missing piece syndrome, but BitTorrent with group suppression does.

Mode-Suppression: A Simple and Provably Stable Chunk-Sharing Algorithm for P2P Networks

“…We consider a model similar to [3], [12], [13] in which peers that have no chunks enter the system according to a Poisson process with a certain arrival rate. There is a seed server that has an independent Poisson clock of a fixed rate, and at each clock tick, it contacts a single peer and uploads a chunk to it following a given policy.…”

“…Also studied in [12] is a variant of this algorithm called the common chunk (CC) algorithm, which proceeds as in the RC algorithm when the peer has no chunks, then follows a policy of sampling a single peer with random selection among its required chunks until it only needs one more chunk, and then proceeds by sampling three peers and only downloading a chunk if every chunk with it appears at least twice with the sampled peers. However, although stable, these algorithms appear to have long sojourn times in some settings [13].…”

“…More recent work on chunk sharing policies [13] describes an algorithm called group suppression (GS), which is based on observations made in [3]. The policy is based on computing the empirical distribution of the states in the system, where a state of a peer is the set of chunks available with that peer.…”

“…, M > max {mN 21 , N 22 } , where > 0 and N 21 , N 23 are positive constants defined in the equations ( 12) and (13). Note that the explicit dependencies of π(x) and y(x) on x are not shown for simplicity.…”

Rarest-First with Probabilistic-Mode-Suppression

“…In this protocol, only new peers who arrive with no pieces follow the rules in [1], and the peers who lack only one piece contact three peers and are allowed to download the last piece only if every piece they have is present with at least two of the three contacted peers. ‚ Bilgen and Wagner [10], [19] proposed the Group Suppression Protocol in which peers who share the same piece profile are defined as a group and the group with the largest population is defined as the largest club. The protocol states that a peer belonging to the largest club uploads only to those peers who hold greater number of pieces than it does, and refuses the upload to all other peers if it contacts them.…”