Analysis of Different Models for Optimal P2P Content Distribution Network

Analysis of Different Models Analysis of Different Models for Optimal P2P Content for Optimal P2P Content

Distribution NetworkDistribution Network

Subhamoy GhoshSubhamoy Ghoshsghosh@cc.hut.fisghosh@cc.hut.fi

Agenda

• Introduction• The Next – Step Problem• Analysis of the Next – Step Problem• Chunk – based CDS• Analysis of Chunk – based CDS• Discussion – Other Models: Merits/Demerits• Conclusion• References

Introduction

• P2P systems – – designed to share computer resources by direct exchange, w/o any

central authority.– Application overlay network on top of conventional protocols.– Fault-tolerant, reliable, scalable massive content distribution system.– Only possible option to manage flash crowds.

• Content Distribution – – Has been the main focus of P2P research.– Responsibility is spread amongst all downloader(s).– Clients contribute resources of the system as a function of their

upload capacities.

Introduction

• Performance perceived by user –– Time taken to fulfill request for a particular file.– Download time as the dominant factor.

• Generic trend for file dissemination – – Partition the file to N equal parts.– User can download either from server or from a peer who has the

requested chunk.

The Next-Step Problem

• Source node s divides a file into k equal parts to disseminate amongst n peers.

• Assumptions:– Communications are synchronous.– Ignores link latencies– File reaches the destination in the same round, as the departure.

• Graph G = (V,E) with |V| = n, W:VxV--->R• File is divided into k-parts such that: • Next – Step problem calculates the actions of each node,

represented by Action Matrix:

The Next-Step Problem

• Max-Product Belief Propagation Network –– Calculates the MAP estimates of the nodes.– Provides a vector of node beliefs and selects the action with

the highest probability.– Algorithm converges, when a node receives duplicate

packets for two consecutive rounds from all nodes.

• With the Next-Step Solution and a pre-defined Cost function, the problem reduces to:

Analysis of Next-Step Problem

Optimizing Chunk-Based CDS

• Provide a network model independent lower – bound on the time taken for file dissemination in a chunk – based CDS.

• Makespan: Time taken to disseminate M parts of a file to I peers in a centralized scenario.

• Assumptions:– Peers upload only 1 file in each round.– Upload capacities are considered to be equal.

• Lower bound on minimum number of rounds for any CDS is:

• Delay Stretch: Captures the delay in download of a peer, for sharing chunks with other peers. Maximum delaystretch is calculated as:

Analysis of Chunk – based CDS

Scatter plots of data with M = 10 and M =50 [8].

• 100 independent simulations with N = 2, 4, …215. • In each case of M = 1 – 5, 8,10, 15, 20 ,50 fits a linear model.

Discussion – Other Models: Merits/Demerits• Maximize peer – bandwidth utilization:

– P2P is scalable since bandwidth increases with increase in participants.– Models focus on i) peer selection strategy – self-organization, ii) chunk selection strategy -

duplication, iii) network degree – choose in-degree/out-degree of client based on upload/download capacity.

• Uniform Workload Distribution:– Fairness in workload minimizes average download time.

• Incentive – driven P2P Networks:– Minimizes download time subject to budget constraint.

• Network Coding based P2P CDS: – Improves delay in transmission time, and makes network more robust and adaptive.

• But almost all models suffer from the churning problem, and network coding models do not perform well, in case multiple nodes fail to reach every client.

Conclusion• Loopy BP algorithm -

– Approximate solution in case of cycled graphs, – Currently the experiment is terminated after a user-defined threshold of operations.– The authors in [1] consider to use gradient – descent algorithm here instead, to overcome this

fluctuation in local optimum.

• Pre-emptive operations in belief propagation - – improve on the computational delay and the final response on the choice of nodes.

• The generic file dissemination approach -– equal service capacity for all peers, and the model can be extended to consider the case of selfish

peers.

• However it provides a model independent performance benchmark, that can be used to compare the dissemination times of different overlay networks.

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Thanks to all !