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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.


Change ratio of peers’ coordinates, starting from stable values for 90% of the peers in each data set and then merging in the remaining 10%.
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pone.0175360.g012: Change ratio of peers’ coordinates, starting from stable values for 90% of the peers in each data set and then merging in the remaining 10%.

Mentions: We randomly select 90% of the nodes and compute the Vivaldi coordinates of these nodes. The coordinates stabilize after 15 or more iterations. After the coordinates stabilize, we then include the remaining 10% of the nodes and recompute all peer coordinates in one interval. We calculate the ratio of the distance between the coordinates for each point versus the size of the coordinate space. For all three data sets, the average change ratio of the distance was < 1%. Fig 12 plots the change ratio sorted in decreasing size for each neighbor set of the peers. The change ratio of the neighbor set, whose coordinates change exceeded the grid spacing, is 2% for the Cornell data set, 10% for the MIT data set and 16% for the OSU data set. The change rate of the relay advertisements also depends on the churn rate of relays. Relays should be substantially more stable than non-relay nodes to achieve a good performance.


Relay discovery and selection for large-scale P2P streaming
Change ratio of peers’ coordinates, starting from stable values for 90% of the peers in each data set and then merging in the remaining 10%.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0175360.g012: Change ratio of peers’ coordinates, starting from stable values for 90% of the peers in each data set and then merging in the remaining 10%.
Mentions: We randomly select 90% of the nodes and compute the Vivaldi coordinates of these nodes. The coordinates stabilize after 15 or more iterations. After the coordinates stabilize, we then include the remaining 10% of the nodes and recompute all peer coordinates in one interval. We calculate the ratio of the distance between the coordinates for each point versus the size of the coordinate space. For all three data sets, the average change ratio of the distance was < 1%. Fig 12 plots the change ratio sorted in decreasing size for each neighbor set of the peers. The change ratio of the neighbor set, whose coordinates change exceeded the grid spacing, is 2% for the Cornell data set, 10% for the MIT data set and 16% for the OSU data set. The change rate of the relay advertisements also depends on the churn rate of relays. Relays should be substantially more stable than non-relay nodes to achieve a good performance.

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&rsquo; 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 &ldquo;best-out-of-K&rdquo; 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.