bullet: high bandwidth data dissemination using an overlay mesh

Bullet: High Bandwidth Data Dissemination Using an Overlay Mesh

Introduction

Given a sender and a large set of receivers spread across the Internet, how can we maximize the bandwidth?

Problem domain: Software or video distribution Real-time multimedia streaming

Existing Solutions

IP multicast does not consider bandwidth when constructing its distribution tree

A promising alternative: Overlay Attempts to mimic the multicast routing

trees Instead of high-speed routers, use

programmable end hosts as interior nodes in the overlay tree

Existing Solutions

A tree structure is problematic Decreasing bandwidth as moving

down a tree Any loss high up the tree will reduce

the bandwidth lower down the tree Bandwidth of a node limited by its

single parent

A New Approach

Transmit disjoint data set to various points in the network

A node download from multiple sources rather than a single parent Higher reliability

Conceptual Model

A B

Root1 Mbps 1 Mbps

1 Mbps

Conventional Model

A B

Root1 Mbps 1 Mbps

1 Mbps

Bullet

A B

Root1 Mbps 1 Mbps

1 Mbps

Bullet Properties TCP friendly

Must respond to congestion signals Low control overhead

Probing resource Locating multiple downloading sources

Decentralized and scalable No global knowledge

Robust to failures, even high up in a tree

Bullet Overview

Use meshes as opposed to trees Bandwidth independent of the

underlying overlay tree Used a 1,000-node overlay and

20,000 network topologies Up to 2x bandwidth improvement

over a bandwidth-optimized tree Overhead of 30 Kbps

System Components Split the data into packet-sized objects Disseminate disjoint objects to clients

at a rate determined by bandwidth to each client

Nodes need to locate and retrieve disjoint data from their peers

Periodically exchange summary tickets Minimize overlapping objects from

each peer

Illustration

S

A

ED

CB

1 2 3 4 5 76

1 2 3 5 1 3 4 6 2 4 5 6

1 2 5 1 3 4

Data Encoding

Multimedia: MDC encoding Large files: erasure encoding

Tornado code Only need to locate 5% extra packets

to reconstruct the original message Faster encoding and decoding time

RanSub Distributes random subsets of

participating nodes During the collect phase, each

node sends a random subset of its descendant nodes up the tree

During the distribute phase, each node sends a random subset of collected nodes down the tree

Informed Content Delivery Techniques

Use summary tickets A summary ticket is an array

array[i] = hashi(working set)

Check ticket elements against a Bloom filter It is possible to have false positives It is possible that B will not send a

packet to A even though A is missing it

TCP Friendly Rate Control (TFRC)

TCP halves the sending rate as soon as one packet loss is detected Too severe

TFRC is based on loss events, or multiple dropped packets within one round-trip time

TCP Friendly Rate Control (TFRC)

Bullet eliminated retransmission from TFRC Easier to recover from other sources

than from the initial sender TFRC does not aggressively seek

newly available bandwidth like TCP

Bullet

Layers a mesh on top of an overlay tree to increase overall bandwidth

Finding Overlay Peers

RanSub periodically delivers subsets of uniformly random selected nodes

Via summary tickets (120 bytes per node)

The working set from each node is associated with a Bloom filter

Peer with nodes with the lowest similarity ratio

Recovering Data from Peers A receiver assigns a portion of the

sequence space to each of its senders, to avoid duplication among senders

A receiver periodically updates each sender with its current Bloom filter and the range of sequences covered in its Bloom filter

Less than 10% of all received packets are duplicates

Making Data Disjoint

Given a randomly chosen subset of peer nodes, it is about the same probability that each node has a particular data packet

A parent decides the portion of its data being sent to each child A function of limiting and sending

factors


The portion of data a child should own is proportional to The number of its descendants Bandwidth

If not enough bandwidth Each child receives a completely

disjoint data stream


If ample bandwidth Each child will received the entire

parent stream

Improving the Bullet Mesh

What can go wrong Not enough peers Constant changing network

Use trial senders and receivers Bullet periodically evaluates the

performance of its peers Places the worst performing

sender/receiver

Evaluation

Used Internet environments and ModelNet IP emulation

Deployed on the PlanetLab Built on MACEDON

Specifies the overlay algorithms Core logic under 1,000 lines of

code

Evaluation

ModelNet experiments 50 2 GHz Pentium 4’s running Linux

2.4.20 100 Mbps and 1 Gbps Ethernet

switches 1,000 emulated instances 20,000 INET-generated topologies

Offline Bottleneck Bandwidth Tree

Given global knowledge, what is the overlay tree that will deliver the highest bandwidth to a set of overlay nodes? Finding a tree with a maximum

bottleneck NP hard in general

Offline Bottleneck Bandwidth Tree

Assumptions The path between two overlay nodes is fixed The overlay tree uses TCP-friendly unicast

connections to transfer data point-to-point In the absence of other flows, we can

estimate the throughput of a TCP-friendly flow using a steady-state formula

In the case of sharing, each flow can achieve at most of 1/nth of the total throughput

Bullet vs. Streaming

The maximum bottleneck tree achieves 5x bandwidth compared to random trees

Bullet outperforms the bottleneck tree by a factor up to 100%

Creating Disjoint Data

Without disjoint transmission of data Bullet degrades by 25%

Epidemic Approaches

Bullet is 60% better than anti-entropy (gossiping) approaches Epidemic algorithms have an

excessive number of duplicate packets

Bullet on a Lossy Network

Bullet achieves 2x bandwidth compared to maximum bottleneck trees

Performance Under Failure

With failure detection/recovery disabled 30% performance degradation with a

missing child under the root With failure detection/recovery

enabled Negligible disruption of performance

PlanetLab

47 nodes for deployment Similar results

Related Work Kazza

Perpendicular downloads Does not use erasure code Bandwidth consuming

BitTorrent Centralized tracker

FastReplica Not bandwidth aware

Related Work

Scalable Reliable Multicast Difficult to configure

Epidemic approaches Do not avoid duplicates

Narada Use overlay meshes Bandwidth still limited by parent

Related Work

Overcast More heavyweight when nodes leave

a tree Splitstream

Not bandwidth aware CoopNet

Centralized