Thesis Presentation P2 P Vo D On Internet Rodrigo Godoi

UniversitatAutònoma de Barcelona
Computer Architecture & Operating Systems Department
P2P-VoD on Internet: Fault Tolerance and Control Architecture
Rodrigo Godoi
Advisor: Dr. Porfidio Hernández Budé
Barcelona, July 2009.

Contents

Video on Demand - VoD

Multimedia service
Asynchronous requests
Every client enjoys entire content
Long sessions (> 60 min.)

VoD - requirements and constraints
Scalability
Large scale Video on Demand - LVoD

Clients: thousands and disperse
Multimedia contents: huge catalogue

Multicast
Peer-to-Peer
Internet
Soft real-time

Time limit on handling data
Quality of Service (QoS)

Control Architecture
Fault Tolerance

Multicast
- implementations
IP Multicast:

Source tree (e.g. PIM-DM)
Shared tree (e.g. PIM-SM)

Application Layer Multicast ALM
(e.g. NICE, ALMI)
Overlay Multicast
(e.g. OMNI)

Multicast- Patching
Patching: multicast technique for multimedia data delivery
Base stream
t= 0
t = 6
Multicast
Unicast
Patchstream

Peer-to-Peer
Free cooperation of equals in view of the performance of a common task.

Takes advantage of resources (storage, cycles, content, human presence) available at the edges of the Internet.
Usage: file sharing, distributed multimedia systems, high performance computing.

Synchronised usage of peers resources: Collaboration Groups

Tracker
Peers
Peers
Peers
Supernodes
Peer-to-Peer - classification
Peers
Location mechanism

Peer-to-Peer - classification
Overlay topology
Chain
Mesh
Tree

Internet environment

Worldwide scale
Heterogeneous environment
Best-effort service
Exponential growth rate

Organisation:

Autonomous Systems (AS): collection of connected IP routing prefixes under the control of one or more network operators (ISPs, universities, companies)
Network arranged by dimension and purpose (LAN, WAN, MAN)
Modeled by complex network theory

Clustering coefficient
Average path length

Problem
Large scale
system
Failures
Network
Server
Peers
Frequent arrivals/departures

Problem
Failures/Errors treatment
Input rate fluctuation
Source crash
Cushion buffer
QoS
Start-up delay
VoD service must…

respect deadlines
provide low start-up delay
have a clever buffer usage
enforce low control overhead

Fault Tolerance

Control relevance
P2P and Multicast
Heterogeneity: Internet, peers capabilities, lifetimes
Resources sharing
Delivery Architecture

FaultTolerance
Consequence of a failure
System defect
Do not solve the fault

State of the art

Contents

Goal of the Thesis
To assess Control impact and propose a Fault Tolerance Scheme for P2P-VoD service on the Internet.

Scalability
Flexibility
Reliability
Efficiency
Low overhead

QoS

Contents

System architecture
Clients overlay topology
Distributed proxy servers
Distributed video servers
Internet
Clients
P2P Collaborations
Servers overlaytopology
IP Multicast zone
Internet Autonomous System

The Failure Management Process
Basis of Fault Tolerance Mechanisms

Income stream monitoring
Heartbeat messages
Centralised
Subsequent queries

Detection
Recovery
Maintenance

Network infrastructure
Peer status

Load and Time metrics
Load cost
Volume of control messages that flows through the system on failure management processes
Control overhead - congestion, bandwidth consumption
Time cost
Time consumed by solving peer failures
Control efficiency - start-up delay, buffer usage

Background: VoD service schemes
Gather different aspects of P2P-VoD services

PCM/MCDB
PCM
MCDB
PCM: Patch Collaboration Manager
MCDB: Multicast Channel Distributed Branching
Bypass

FaultTolerance - PCM/MCDB
MCDB
Maintenance messages
Ch.M0
Ch.M1
Recovery messages
Ch.M2

Centralised recovery.
IP Multicast tree rearrangement

Detection messages

P2Cast
Base Stream
Patch Stream

Clients are divided into sessions according to the arrival time in the system (session threshold parameter - T)
Best-fit algorithm: Peer with great amount of available bandwidth is selected as parent

VoD Server
Session 4
Session 3
31.0
20.0
34.0
35.0
24.0
21.0
37.0
35.8
39.9
35.5
27.0
40.0
T

FaultTolerance - P2Cast

Source peers (Parents) failures provoke stream disruption
Subsequent recovery queries

Detection messages
VoD Server
Recovery messages
Session 4
Session 3
31.0
20.0
34.0
35.0
24.0
21.0
37.0
35.8
39.9
35.5
27.0
40.0

Load cost
Control messages
PCM/MCDB
P2Cast
Heartbeats
Heartbeats
Detection
IP multicast rearrangement
Recovery request
Subsequent queries
Recovery
Peers status
Routers status
Routers status
Maintenance

Time cost
Time consumption
Recovery messages
Detection
Path (network theory): small-world effect
latency
PCM/MCDB
Subsequent queries
Recovery messages
Detection
Path (network theory): small-world effect
latency
P2Cast

Contents

TheFaultToleranceScheme (FTS)
Cushion
Delivery
Collaboration
Altruist
FTS stands on peers capabilities:

Input / Output bandwidth
Buffer size

bwo
bwi
buffer
8
9
10
11
12
L
6
7
13
Fault Tolerance Groups
Buffer In
Buffer Out

MN
C1
C2
Cushion
Delivery
Gen. purpose
Altruist
MN
Fault Tolerance Groups
MN
MN
L
1
2
3
1
2
3
t = 0
L
4
5
1
2
3
7
8
9
4
5
6
1
2
3
10
7
MN
13
14
L
15
10
11
12
8
9
4
5
1
2
3
t = 0
t = 0
C1
7
L
4
5
6
1
2
3
6
7
C1
10
11
L
12
7
8
9
4
5
6
9
10
6
7
8
13
14
Video
8
9
10
6
7
13
14
15
11
12
3
4
5
1
2
Manager Node
MN
C2
7
L
4
5
6
1
2
3
14
15
11
12
13
t = 3
t = 3
t = 10
C1
Video
8
9
10
6
7
13
14
15
11
12
3
4
5
1
2
7
Video
8
9
10
6
13
14
15
11
12
3
4
5
1
2
FTS Collaborators
[t = 17]

Load and Time costswiththe FTS
The proposed Fault Tolerance Scheme…

distributes the control through Manager Nodes
removes subsequent queries during recovery
eliminates messages for peers status maintenance
can detect failures through heartbeats (FTS I) and income stream monitoring (FTS II)

Contents

Simulation tool: VoDSim
Computational simulations provide a more dynamic and scalable analysis

Discrete event-driven model
More than 50 classes in C++
Over 46.000 lines
Peer arrival rate: Poisson
Content popularity: Zipf

VoDSim extensions

Implementation of ALM service scheme: P2Cast
Peers disruptions: Weibull
FMP instrumentation:

Load and Time costs measurement
Fault probability
Lifetime

Contents

Experimental Results

Failure Management Process validation

Control vs. Multimedia traffic
Analytical results (PCM/MCDB and P2Cast)
∆w = 13%-39%
∆w =13%- 37%
∆w = 10%-28%
Simulated results (P2Cast)

Load cost analysis

Time cost analysis
High latency
Time cost increment
Recovery control messages

Time cost analysis
Download rate: 1500 kb/s (750+750)
Cushion buffer
56MB
11MB
1 min.
5 min.
Start-up delay

Experimental Results

Load cost analysis
Cost increment
Cost reduction
FTS I - heartbeat detection
FTS II - buffer monitoring detection

Load cost analysis

Overhead reduction
Scalability

Time cost analysis
High latency
Time cost increment
Volume of communication
FTS

Efficiency

Cushion buffer
56MB
11MB
Start-up delay
5 min.
1 min.
τ = 1/(2·fHB)
FTS I - heartbeat detection
FTS II - buffer monitoring detection

Fault Tolerance service performance

Reliability
Flexibility

Altruist buffer 338MB
Altruist buffer 102MB

Contents

Conclusions
Control mechanism plays a crucial role on designing P2P-VoD systems
Load cost
Control overhead: network congestion, bandwidth resources
Time cost
Efficiency: buffer usage, start-up delay
Load and Time costs trade-off
Reduction of Load and Time costs
Quality of Service

Conclusions
The Fault Tolerance Scheme…

is flexible for Internet use
presents hierarchical control structure
has scalable backup mechanism
do not demand extra data communication and dedicated resources
is able to guarantee system reliability
reduces Load and Time costs

Contents

Future Work

Application and assessment of the FTS in a wide range of VoD architectures and service policies
Implementation of the FTS in a simulation environment
FTS improvement: storing parts of non-visualized contents; using non-volatile storage devices (e.g. Solid State Disk drives)
Addition of VCR / DVD-like operations
Usage of clients behaviour information to improve system performance

P2P-VoD on Internet: Fault Tolerance and Control Architecture
Rodrigo Godoi
Thankyou
Gracias
Obrigado
Barcelona, July 2009.

Server
Fault Tolerance Group
Control comm.
Manager Node
Clients
FTG members
Architecture elements

Server: content seed
Peer: multimedia client / source
FTG member: collaborator in the FTS
Distributed backup: flexibility and reliability.
Built on the fly: backup do not need retransmission.
P2P based: mechanism uses own system available resources.
Hierarchical control: scalability and deployment.
Manager Node: organize and monitor FTG

The FTS formationlaw
While
If
then
Add Collaborator to FTG
If
Peers’ bandwidth greater than playback rate (bw≥Vpr)
then
New FTG.
Input parameters
FTG size
Distributed backup
Service conditions

The FTS formationlaw
While
MN
C1
C2
C3
A · 2
A · 3
A · 5
A · 5
15
15
15
15
If
then
Add Collaborator to FTG.
If
if:
Peers’ bandwidth lower than playback rate (bw<Vpr)
then
New FTG.
if:
A
Video
C
B
D
E
H
G
F
…
Collaboration Capacity
A
Buffer and Bandwidth constraints
…
C1
A*
B*
…
A*
B*
C2
FTG size
MN [500kb/s]
C1 [200kb/s]
C2 [300kb/s]
C3 [500kb/s]
Vpr [1500kb/s]
…
A*
B*
C3
MN
A*
…
B*

MN
C1
C2
Client
MN
I
II
III
IV
Creation of Fault Tolerance Groups
Local Server
Collab. availability
FTS ack.
Join to FTG
Start new FTG and become Manager Node
Standby status

Standby Peer
I
II
FTG: complexity and maintenance
O(NCFTG)
MN
MN
failure
Local Server
Member failure
C1
C1
C2
Designation of new MN
Restoring the FTG
Restoring the FTG

Evaluation environment
Underlying network: GT-ITM topology generator
Transit-stub model