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Relay discovery and selection for large-scale P2P streaming

View Article: PubMed Central - PubMed

ABSTRACT

In peer-to-peer networks, application relays have been commonly used to provide various networking services. The service performance often improves significantly if a relay is selected appropriately based on its network location. In this paper, we studied the location-aware relay discovery and selection problem for large-scale P2P streaming networks. In these large-scale and dynamic overlays, it incurs significant communication and computation cost to discover a sufficiently large relay candidate set and further to select one relay with good performance. The network location can be measured directly or indirectly with the tradeoffs between timeliness, overhead and accuracy. Based on a measurement study and the associated error analysis, we demonstrate that indirect measurements, such as King and Internet Coordinate Systems (ICS), can only achieve a coarse estimation of peers’ network location and those methods based on pure indirect measurements cannot lead to a good relay selection. We also demonstrate that there exists significant error amplification of the commonly used “best-out-of-K” selection methodology using three RTT data sets publicly available. We propose a two-phase approach to achieve efficient relay discovery and accurate relay selection. Indirect measurements are used to narrow down a small number of high-quality relay candidates and the final relay selection is refined based on direct probing. This two-phase approach enjoys an efficient implementation using the Distributed-Hash-Table (DHT). When the DHT is constructed, the node keys carry the location information and they are generated scalably using indirect measurements, such as the ICS coordinates. The relay discovery is achieved efficiently utilizing the DHT-based search. We evaluated various aspects of this DHT-based approach, including the DHT indexing procedure, key generation under peer churn and message costs.

No MeSH data available.


Error reduction through median-of-5.
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pone.0175360.g005: Error reduction through median-of-5.

Mentions: To reduce the RTT measurement error, for each relay path, one can conduct multiple measurements and use the median value. The median-of-5 CDF curve in Fig 3(b) plots an improved RTT measurement error CDF for the median-of-5. Compared with the empirical CDF curve in Fig 3(b), the RTT measurement error has been reduced. Consequently, the error in the “best-out-of-K” relay selection is also reduced as shown in Fig 5. For example, the “random 20” relay selection mistakenly reports a shortest relay path 20% shorter than the direct path only 50% of the time.


Relay discovery and selection for large-scale P2P streaming
Error reduction through median-of-5.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5391927&req=5

pone.0175360.g005: Error reduction through median-of-5.
Mentions: To reduce the RTT measurement error, for each relay path, one can conduct multiple measurements and use the median value. The median-of-5 CDF curve in Fig 3(b) plots an improved RTT measurement error CDF for the median-of-5. Compared with the empirical CDF curve in Fig 3(b), the RTT measurement error has been reduced. Consequently, the error in the “best-out-of-K” relay selection is also reduced as shown in Fig 5. For example, the “random 20” relay selection mistakenly reports a shortest relay path 20% shorter than the direct path only 50% of the time.

View Article: PubMed Central - PubMed

ABSTRACT

In peer-to-peer networks, application relays have been commonly used to provide various networking services. The service performance often improves significantly if a relay is selected appropriately based on its network location. In this paper, we studied the location-aware relay discovery and selection problem for large-scale P2P streaming networks. In these large-scale and dynamic overlays, it incurs significant communication and computation cost to discover a sufficiently large relay candidate set and further to select one relay with good performance. The network location can be measured directly or indirectly with the tradeoffs between timeliness, overhead and accuracy. Based on a measurement study and the associated error analysis, we demonstrate that indirect measurements, such as King and Internet Coordinate Systems (ICS), can only achieve a coarse estimation of peers’ network location and those methods based on pure indirect measurements cannot lead to a good relay selection. We also demonstrate that there exists significant error amplification of the commonly used “best-out-of-K” selection methodology using three RTT data sets publicly available. We propose a two-phase approach to achieve efficient relay discovery and accurate relay selection. Indirect measurements are used to narrow down a small number of high-quality relay candidates and the final relay selection is refined based on direct probing. This two-phase approach enjoys an efficient implementation using the Distributed-Hash-Table (DHT). When the DHT is constructed, the node keys carry the location information and they are generated scalably using indirect measurements, such as the ICS coordinates. The relay discovery is achieved efficiently utilizing the DHT-based search. We evaluated various aspects of this DHT-based approach, including the DHT indexing procedure, key generation under peer churn and message costs.

No MeSH data available.