169 research outputs found
Rarest First and Choke Algorithms Are Enough
The performance of peer-to-peer file replication comes from its piece and peer selection strategies. Two such strategies have been introduced by the BitTorrent protocol: the rarest first and choke algorithms. Whereas it is commonly admitted that BitTorrent performs well, recent studies have proposed the replacement of the rarest first and choke algorithms in order to improve efficiency and fairness. In this paper, we use results from real experiments to advocate that the replacement of the rarest first and choke algorithms cannot be justified in the context of peer-to-peer file replication in the Internet. We instrumented a BitTorrent client and ran experiments on real torrents with different characteristics. Our experimental evaluation is peer oriented, instead of tracker oriented, which allows us to get detailed information on all exchanged messages and protocol events. We go beyond the mere observation of the good efficiency of both algorithms. We show that the rarest first algorithm guarantees close to ideal diversity of the pieces among peers. In particular, on our experiments, replacing the rarest first algorithm with source or network coding solutions cannot be justified. We also show that the choke algorithm in its latest version fosters reciprocation and is robust to free riders. In particular, the choke algorithm is fair and its replacement with a bit level tit-for-tat solution is not appropriate. Finally, we identify new areas of improvements for efficient peer-to-peer file replication protocols
Analyzing Peer Selection Policies for BitTorrent Multimedia On-Demand Streaming Systems in Internet
The adaptation of the BitTorrent protocol to multimedia on-demand streaming
systems essentially lies on the modification of its two core algorithms, namely
the piece and the peer selection policies, respectively. Much more attention
has though been given to the piece selection policy. Within this context, this
article proposes three novel peer selection policies for the design of
BitTorrent-like protocols targeted at that type of systems: Select Balanced
Neighbour Policy (SBNP), Select Regular Neighbour Policy (SRNP), and Select
Optimistic Neighbour Policy (SONP). These proposals are validated through a
competitive analysis based on simulations which encompass a variety of
multimedia scenarios, defined in function of important characterization
parameters such as content type, content size, and client interactivity
profile. Service time, number of clients served and efficiency retrieving
coefficient are the performance metrics assessed in the analysis. The final
results mainly show that the novel proposals constitute scalable solutions that
may be considered for real project designs. Lastly, future work is included in
the conclusion of this paper.Comment: 19 PAGE
Clustering and Sharing Incentives in BitTorrent Systems
Peer-to-peer protocols play an increasingly instrumental role in Internet
content distribution. Consequently, it is important to gain a full
understanding of how these protocols behave in practice and how their
parameters impact overall performance. We present the first experimental
investigation of the peer selection strategy of the popular BitTorrent protocol
in an instrumented private torrent. By observing the decisions of more than 40
nodes, we validate three BitTorrent properties that, though widely believed to
hold, have not been demonstrated experimentally. These include the clustering
of similar-bandwidth peers, the effectiveness of BitTorrent's sharing
incentives, and the peers' high average upload utilization. In addition, our
results show that BitTorrent's new choking algorithm in seed state provides
uniform service to all peers, and that an underprovisioned initial seed leads
to the absence of peer clustering and less effective sharing incentives. Based
on our observations, we provide guidelines for seed provisioning by content
providers, and discuss a tracker protocol extension that addresses an
identified limitation of the protocol
Multimedia Streaming over P2P networks using Markov Decision Processes
Projecte final de carrera realitzat en col.laboració amb EPFL LausanneThe aim of this project is to overcome the limitations of Foresighted Resource
Reciprocation strategy (FRR) [11] for distributing multimedia content while
providing a better performance for resource reciprocation than other solutions proposed.
In this project, we build on the Foresighted Resource Reciprocation strategy
by explicitly considering the timing constraints for continuous display of
the multimedia data and the importance of each multimedia data segment for
the multimedia quality. In particular, we incorporate data priority functions
into the reward function in order to adapt to the specific characteristics of
media streaming applications. As a result, the peers exchange video packets
with a strategy that ensures that the most important packets have a higher
probability to reach the decoder on time for proper decoding
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