Generic Warfighter’s Information Network
(WIN) Components
Parallel Simulation of Large-Scale
Heterogeneous Communication
Systems
UAV Network
PI: Rajive Bagrodia
rajive@cs.ucla.edu
How does the network perform as it is
scaled to 100,000+ heterogeneous devices?
Senior Dev Engr: Dr. Mineo Takai
mineo@cs.ucla.edu
Computer Science Department
UCLA
OSPF, LANDMARK, or
DAWN, routing?
Partial support from DARPA
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
•
•
•
•
•
•
•
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Project Accomplishments
Technology Transfer
Design & development of GloMoSim framework with rich
protocol stack
Demonstrated substantially superior sequential
performance compared to existing alternatives (2-5x faster)
Demonstrated further improvement with parallel execution
(up to 10x)
Demonstrated scalability of GloMoSim using very highfidelity models with a complete protocol stack to networks
with 50,000+ devices;
Demonstrated feasibility of real-time simulation of networks
with 100s of nodes
Demonstrated hybrid simulations with integration of real
applications running with virtual protocol stack.
Direct comparison of alternative unicast and multicast
wireless protocols for GloMo scenarios
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
•
•
•
•
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Scalable Simulation Technology
•
GloMoSim and PARSEC integrated into SEAM-LSS, a
DARPA-funded M&S environment developed by SAIC
GloMoSim commercialized by Scalable Simulation Solutions
Commercial version of GloMoSim being used in M&S study
for the JTRS program
Wide distribution (close to 3000 downloads) of public domain
simulation software
GloMoSim Library
Efficient and high-fidelity simulations via parallel execution on
diverse parallel architectures (PARSEC )
•
PARSEC
PARSEC(C-Based)
(C-Based)Front-End
Front-End
Portable
PortableMulti-threaded
Multi-threadedCommunication
CommunicationLibrary
Library
(xsend,
(xsend,xrec,
xrec,etc...)
etc...)
MPI/AIX
MPI/AIX
MPI
MPICH/
CH/
BSD
BSDUnix
Unix
Pthreads
Pthreadson
onWindows
WindowsNT,
NT,
Linux,
Linux,Solaris,
Solaris,IRIX
IRIX
Data Plane
Linux,
Linux,
Windows
Windows
NT,
NT,
Unix
Unix
•
•
•
•
IBM SP
•
PC Network
Dell SMP, Sun Sparc
1000; SGI Origin 2000
Uniprocessor
Machine
•
Modular, extensible library for
network models
Model each layer using
abstract or detailed model
Built-in statistics collection at
each layer
Customizable GUI
Large and growing model
library
worldwide installed base of
users
Modular and composable library of parallelized models with
standard APIs for end-end models (GloMoSim)
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Page 1
Application Processing
Application
RTP Wrapper
TCP, UDP, RSVP
IP
OSPF, AODV, …
Transport
IP
Network
IEEE 802.11, 802.3, …
Link Layer
MAC Layer
EPLRS, WaveLAN, ...
Radio
Free space, TIREM
Propagation
model
Packet Store/Forward
Glomosim
Standalone
•
•
•
•
•
•
•
•
Application: Replicated file system, ftp, telnet, cbr, web
caching, NetMeeting, WebPhone, synthetic traffic generators
Transport : TCP(FreeBSD), NS TCP (Tahoe), UDP, DBS
satellite models,
Multicasting: ODMRP, CAMP, AMRIS, AMRoute, AST, DVMRP
Routing: Distributed Bellman-Ford, Flooding, Fisheye, DSR,
DSDV, WRP, LAR, NS-DSDV, DREAM, MMWN
MAC: CSMA, IEEE 802.11, MACA-W,
Radio: DS SS with and without capture
Propagation: analytical (free space, Rayleigh, Ricean), 2-ray
ground reflection model, path loss trace files
Mobility: random waypoint, trace files
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
GloMoSim Path Loss Models
Critical for accurate wireless network simulations
•
•
•
•
•
•
•
Memory consumption [MB]
500
Scalability
400
•
300
200
100
8
16
No. of processors
0
10000
20000
30000
40000
50000
Real-Time
2.5
50
2
100
1.5
200
1
0.5
0
50 nodes
100 nodes
500 nodes
1000 nodes
0
1
2
3
4
5
6
-40
-50
-60
NS RX limit (-64.3)
-70
GloMoSim prop limit (-76.0)
-80
Backgroundnoise
Ambient noise
-100
Thermal noise (-100.9)
New GloMoSim prop limit
-110
-120
NS
GloMoSim 1.x
Opnet / GloMoSim 2.x
0
10000 20000 30000 40000 50000
•
The packet delivery ratio decreases gradually as the CBR traffic
increases.
The end-to-end delay is more adversely affected by heavier
traffic than the packet delivery ratio due to many retransmission,
but the major loss of packets is derived from the network queue
overflow (50 tail drop), not from IEEE 802.11 retransmission
limits.
4
0.6
0.4
0.2
0
Packet drops per session
0.8
End-to-end delay [s]
Packet delivery ratio
300
5
What causes
this increase?
3
2
1
150
200
250
300
Number of CBR sources
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
250
200
802.11 retx limit
Queue overflow
150
100
50
0
0
100
NS CS limit (-78.0)
-90
Large-scale Simulation Results (2)
•
1,000 network nodes on a flat terrain (density of 20,000m2/node)
376m boundary radio model (from the WaveLAN specification)
with detailed SIR (signal to interference) calculation
IEEE 802.11 DCF with RTS / CTS option; LAR (Location Aided
Routing Protocol) scheme 1 ad hoc wireless routing
100 to 300 CBR sources with 4 packets/s for randomly selected
destinations (about 6 hops away)
1
50
100000
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Network analysis using large-scale
Simulations
•
10000
Number Network Nodes
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
•
5000
1200
1000
800
600
400
200
0
Packets processed per node [/s]
•
•
1000
Simulation of wireless networks with full protocol stack (density
of 20,000m 2 per node, free space, 250m boundary radio model,
IEEE 802.11 DCF, AODV, UDP, 10% nodes have CBR traffic
with 4 packet per second)
Memory
Consumption [MB]
1
4
550
Simulation Scalability
600
3
2
250
-30
SIRCIM (topography,
building type)
GloMoSim 2.x includes all
the above.
3.5
3
1
100
Number of network nodes
Parallel Execution
5
86.1
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
0
Sim / real time ratio
Speedup
7
10
-20
? : std dev for log normal shadowing
GloMoSim
Unique Features:
• Scalability to very large
(wireless) networks
• Efficiency via transparent
support for parallel execution
• Potential for real-time
simulation of networks
Distance [m]
Free space
Abstracted two-ray
ground reflection(NS-2)
Trace based
(path loss - distance)
Generic (n, ? )
• n: path loss exponent
Rx Power [dBm]
Models currently available in GloMoSim
50
100
150
200
250
50
300
100
150
200
Number of CBR sources
Number of CBR sources
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Page 2
250
300
Models available in QualNet 1.0
GloMoSim & QualNet
•
•
wireless
•
GloMoSim: library for mobile ad hoc networks
developed as a research tool at UCLA
QualNet: Wired & wireless network modeling library
commercialized by Scalable Simulation Solutions (SSS)
• GUI for experiment design, animation, protocol
model design
• Larger model library: wired, wireless, QoS
• Built in statistics collection and analysis capabilities
• Application level performance prediction
• Technical support, maintenance & training
• For information on QualNet: info@scalable-solutions.com
•
•
•
•
•
•
•
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
32.3705
SEAM-LSS Integration
32.37
Developing a complete analysis capability for military comm needs
(in partnership with Telcordia/SAIC)
Latitude (degrees)
•
Application: ftp,telnet,cbr, Tcplib, NetMeeting, WebPhone,
MODSAF, SEAM-LSS, synthetic traffic, self-similar traffic with long
range dependency
Transport : TCP (FreeBSD), UDP, RTP, RSVP, MPLS, DiffServ
Multicasting : ODMRP, PIM
Routing: Distributed Bellman-Ford, OSPFv2, RIPv2, BGP, Flooding,
Fisheye, DSR , DSDV, WRP, LAR, AODV
MAC: CSMA, IEEE 802.11, IEEE 802.3
Physical : point-point link, wired bus, IEEE 802.11 DSSS radio
Propagation : analytical(free space, Rayleigh, Ricean), TIREM, 2-ray
ground reflection model, path loss trace files
Mobility : random waypoint, MODSAF, SEAM-LSS, trace files
SEAMLSS
Results
32.3695
Completed
PARSEC McKenna 11-node DAWN
Latitude vs. Simulation Time
32.369
32.3685
32.368
32.3675
0
100
300
400
500
600
700
100
Thread Completion Time (s, log scale)
QualNet
Models
200
800
900
1000
Simulation Time (seconds)
Mobility
Scenarios
Scenarios
Simulation
Realistic Propagation
Models
Communication Threads
PARSEC McKenna 11-node DAWN
Thread Completion Time vs. Thread Start Time
Number of Completions: 371
10
1
Thread Instance
0.1
0.01
0
100
200
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
•
100
10
Min
Mean
Max
•
0.01
0.001
0.0001
•
SIT
RE
P
SL
SIT
to
PL
RE
P
PL
LO
GR to CC
EP
LO
S
GR
Lt
oP
EP
S
PS
Se
to
ns
1S
itiv
GT
e
Re
Se
p
ns
SL
itiv
to
e
Re
PL
p
PL
Sta
tus
to
CC
Re
Sta
pS
tus
Lt
oP
Re
G
pP
Off
G
to
en
Co
1S
siv
nd
GT
euc
Off
on
ta
tta
en
the
c
siv
kc
m
e
ov
om
-o
eP
Off
p
n
en
L to
the
siv
SL
em
ov
on
Off
e
the
SL
en
siv
m
to
ov
e
FT
-o
eF
Off
L
n
TL
en
the
siv
to
m
SL
e
ov
-o
e
n
PL
De
the
fen
to
m
siv
SL
ov
ee
2
De
sta
RT
fen
tion
O
siv
ary
to
e
PL
PL
-s
to
tati
RT
on
O
ar
yP
L
to
RT
O
2
Min, Mean, & Max Thread Comp. Time (sec,
log scale)
PARSEC GloMo 78-node DAWN
Min, Mean, & Max Thread Completion Time vs. Thread Type
1
500
600
700
800
900
ModSAF (Modular Semi-Automated Forces) models
munitions, group movement behavior
• ModSAF supports HLA through a DIS/HLA gateway
• GloMoSim, being written in PARSEC, supports HLA
extensions
HLA Interactions between MODSAF & GloMoSim:
• ModSAF sends unit positions through HLA
• GloMoSim receives position updates, computes
signal transmission based on new positions
HLA and sfdsimulator interfaces from GloMoSim
have been integrated with MODSAF 5.1
Thread Type
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
400
Thread Start Time (seconds)
GloMoSim and ModSAF 5.0 Cosimulation
SEAMLSS Results
0.1
300
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Page 3
1000
ModSAF, DIS/HLA, Intermediate
Federate, GloMoSim
Execution Constraints
•
ModSAF position updates are real-time, while
GloMoSim/PARSEC is a DES
• an intermediate PARSEC federate was created
between the gateway and GloMoSim
DIS-HLA
Gateway
RO
MODSAF
Real time
DIS-HLA
IF
Intermediate
Federate (IF)
Time Regulated
MODSAF
GloMoSim
GloMoSim
Time Constrained
RTI
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Co-Simulation
•
Validation Using Emulation
•
Interfaces to support interoperability of OPNET and
GloMoSim models using HLA and modified RPR-FOM
Heavy traffic using FTP transferring a 10MByte file in a wireless
Wavelan network over 802.11 (with RTS/CTS) using a 2Mbit/s link
Same scenarios in both real network and hybrid network with a real
FTP client and server
0
Ftp
1
Distance between nodes is 1m
•
•
OPNET
80
0.5
40
0.4
1
2
3
4
5
Scenario No.
Gateway
2
Scenario5
120
0
Gateway
Ftp
3
160
Real Network
Hybrid Network
Loss Rate(%)
Throughput(Kbyte/sec)
DAWN subnets in PARSEC/SEAMLSS
Ftp
Ftp
200
0.3
0.2
0.1
0
1
2
3
4
5
Scenario No.
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Technology Transfer
Selected Users
Users by Platform
19%
2%
2%
1%
2%
36%
21%
12%
•
•
•
•
0%
1%
0%
0%
Redhat Linux
Other Linux
Solaris
Windows 95/98
Windows NT
SunOS
FreeBSD
•
Other
PC Solaris
HPUX
Irix
Macintosh
OSF
•
1%
5%
Over 1775 PARSEC and/or GloMoSim downloads Mar 00-July 00
• Over 900 PARSEC/GloMoSim downloads Nov ‘99-- Feb 00
•
http//pcl .cs.ucla.edu/projects/parsec
Second Parsec workshop held Nov 11 & 12, 1999
•
•
http//pcl .cs.ucla.edu/projects/parsec/workshop99
Over 50 attendees including commercial, military, universities
Integrated into SEAM LSS: http://www.seamlss .com
Commercialization via Scalable Simulation Solutions
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Government/Military: MITRE, Lawrence Livermore National
Labs*, FAA, Jet Propulsion Lab, NASA *, MIT Lincoln
Laboratory, Space and Naval Warfare System Center
(SPAWAR)*, …
Corporations : Cisco Systems, Fujitsu Laboratories, General
Dynamics*, Philips Research, Lockheed Martin, Lucent
Technologies*, Motorola*, NEC*, Nortel Networks, Nokia
•
Research Center*, Oracle Telecomputing, Primeon Inc.*,
SAIC*, SRI International*, …
Universities (US): Boston University*, Caltech*, Cornell,
•
International Sites: AT&T (UK), CSIRO (Australia), NATO
Dartmouth, UC Berkeley, UCLA*, University of Texas*, USC*, …
SACLANT Undersea Research Centre, Italy; Technion, Israel;
University of Aizu , Japan; VTT Electronics, Finland; …
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Page 4
Multicast Protocol Performance
•
ODMRP (UCLA)
• Creates a mesh of nodes (the forwarding group) to
provide redundant multicast routes
• on-demand technique to establish route/membership
CAMP (UCSC)
• Creates a shared mesh
• requires underlying unicast protocols (e.g., WRP)
AMROUTE (Telcordia)
• Creates bidirectional shared multicast tree
• Uses virtual mesh links to establish the multicast tree
AMRIS (NUS, Singapore)
• Creates a shared tree and uses ranking to direct the
flow of multicast data
Flooding
•
Selected Case Studies
•
•
•
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Forwarding Group Concept
Multicast Protocol Comparisons
A set of nodes in charge of forwarding multicast packets
Supports shortest paths between any member pairs
Mesh topology and flooding help overcome displacements and
channel fading
•
Configuration:
• 50 nodes placed randomly in 1000m x 1000m area
• Capture Radio; power of 250 m; Bandwidth: 2 Mbps
• MAC: IEEE 802.11 DCF
• Traffic: CBR with payload size 512 bytes
Metrics:
• Packet delivery ratio;
• control overhead
Independent variables:
• Mobility
• Network traffic load
• Multicast group size
• No. of senders
Paper presented at Infocomm 2000 (Lee et al): http://pcl .cs.ucla.edu/papers
•
•
•
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Multicast Performance with Mobility
Multicast Performance with Mobility
Packet Delivery Ratio (PDR)
•
•
•
•
20 multicast members
5 sources transmit
packets at the rate of 2
pkt/sec each
Mobility Speed: 0-72
km/hr
PDR : fraction of packets
actually received by
intended recipients.
Control Overhead
1.0
35
0.9
30
0.8
25
0.7
ODMRP
FLOOD
CAMP
0.6
0.5
15
AMROUTE
AMRIS
0.4
10
0.3
5
0.2
0
0.1
0
0.0
10
20
30
40
50
60
70
Mobility Speed (kph)
0
10
20
30
40
50
60
70
1.2
1.0
0.8
0.6
0.4
0.2
0.0
0
10
20
30
40
50
Mobility Speed (kph )
60
70
Mobility Speed (kph)
• Mesh-based (CAMP, ODMRP, flooding ) do better than tree based
(AMRIS, AMROUTE)
• Good delivery ratio in ODMRP due to multiple redundant routes
•CAMP degrades due to poor pkt delivery to distant routers (these have
fewer redundant paths); WRP loop detection can temporarily mark
node subsets as unreachable, postponing rote updates for mesh
maintenance.
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
ODMRP
FLOOD
CAMP
AMROUTE
AMRIS
20
Control Bytes Transmitted
•
•
•
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
•
•
•
Control overhead: no. of control pkt bytes + header size in data packets
AMRIS is low due to very low delivery ratio; AMROUTE high due to
loops
CAMP has higher overhead than ODMRP due to trigerred updates in
WRP, particularly with high mobility.
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Page 5
TCP and MAC Interactions
Evaluate MAC interaction with TCP in presence of
mobility.
0
10 m
1
2
10
11
17
18
19
20
26
72
73
74
•
• with mobility: Bellman-Ford with routing table updates every second.
3 horizontal (18-26; 36-44; 54-62) and 3 vertical (2-74; 4-76; 6-78) end-end FTP connections.
•
•
without mobility : static routing
•
WMSCA ‘99 (Gerla, Bagrodia, Tang): http:// pcl.cs.ucla.edu/papers
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
•
•
•
Study performance issues of (ad hoc) wireless
networks using real applications
Importance of abstract vs. detailed network models
Efficient simulation of large scale models via
parallel execution
•
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Replicated File System
When are detailed models of the protocol stack necessary for
studying application performance?
FAMA
802.11
Throughput
(bps)
36-44
100000
54-62
50000
0
6-78
2-74
CSMA
FAMA
802.11
MAC Protocol
4-76
6-78
•
•
Link level ACKs help recover from loss caused by transient nodes.
Capture exists.
Conclusion
• Link-level ACKs important to combat packet loss in wireless ad-hoc environment.
Faster update dissemination
Better adaptation to dynamic network topologies
Replicated File System: Results
Reconcilitaion behavior as a function of MAC protocol & mobility
speed
Abstract models may be used only in absence of mobility
Globecomm ’99: Ahuja et al: http://pcl .cs.ucla.edu/papers
Reconciliation time [milli sec]
Stale read/write rate: No. of read/write access to
data that has since been modified by another replica
•
CSMA
4-76
18-26
150000
Without mobility
• CSMA performs poorly due to interference by neighboring and intersecting streams.
• FAMA fair due to RTS/CTS and less aggressive yield time.
• 802.11 exhibits capture.
With mobility
• CSMA and FAMA collapse due to lack of fast loss recovery facilities.
• 802.11 still operational.
•
•
•
•
replica generates a reconciliation request to when
the reconciliation completes.
Frequency of reconciliation?
2-74
RRFS shares data through peer replication
• Every unit gets its own copy of the data
• Every unit can make updates to its copy
Use periodic update propagation for data reconciliation
Use opportunistic update propagation between any replicas
Contrast with client server architecture
•
• Average Reconciliation time: Time from when a
•
•
200000
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Application performance Metrics:
Scalability of design with no. of replicas, nodes, traffic,
deployment area, …?
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
54-62
36-44
The Replicated File System (RRFS):
Distributed Data Replication
Application Performance in AdHoc
Networks
•
100000
50000
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
•
•
•
•
18-26
MAC Protocol
80
Mobility: 10 meters per second in a random direction with a probability of 0.5.
Routing:
•
200000
150000
0
81 nodes;
radio range : 30m;
bandwidth: 2Mbps
•
•
•
250000
8
9
9 X 9 Grid Experiments with Mobility
9 X 9 Grid Experiment with No Mobility
Throughput
(bps)
•
TCP/MAC Performance
800000
600000
CSMA
MACA
400000
FAMA
802.11
200000
0
0
2
4
Mobility [kmph]
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Page 6
6
8
Replicated File System: Results
Replicated File System: Results
Impact of transmit power on recon time
•
•
•
Simulation of replication service with a detailed stack model: TCP, Bellman Ford,
CSMA, radio
•
•
Topology: 20 mobile nodes; 6 Rumor nodes; ring topology.
Reconcilitation interval: 4 hours
•
Impact of varyingTCP window size from 1 to 32 packets
Increasing window size causes more collissions between data
packets and ACKs travelling in opposite directions
Again, difference with mobility is much more than no mobility
Abstract models may have errors upto 400% in presence of mobility.
Reconciliation time(s)
•
Reconciliation time
2500000
2000000
50m power
1500000
40m power
1000000
30m power
800
600
1 packet
400
32 packets
200
0
500000
0
2
4
6
8
Mobility(km/hr)
0
0
2
4
6
8
Mobility (kmph)
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Scalability via Parallel Execution
1
5
n
Rumor Servers in Ring Topology
7
8
3
4
Ring Topology
9
60 Servers
120 Servers
4
Speedup
4
3
2
1
3
2
2
3
4
5
6
7
8
1
Number of Processors
2
3
4
5
6
7
Accomplishments
•
•
•
0.02
0.01
Design & development of GloMoSim framework for detailed
simulation of networks with tens of thousands of nodes.
Demonstrated hybrid simulations with integration of real
applications running with virtual protocol stack.
Direct comparison of alternative unicast and multicast
wireless protocols for GloMo scenarios
Design of scaleable unicast & multicast wireless protocols
GloMoSim and PARSEC integrated into SEAM-LSS
GloMoSim commercialized by Scalable Simulation Solutions
Commercial version of GloMoSim being used in M&S study
for JTRS program
Wide distribution (close to 3000 downloads) of public domain
simulation software
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Page 7
0.01
0
40
60
80
100
120
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
Conclusion
0.02
0.015
0.005
Number of Processors
Technology Transfer:
•
•
•
0.03
Number of Servers
8
DOMAINS; July 2000; R. Bagrodia; rajive@cs.ucla.edu
•
0.04
0
1
0
1
•
0.025
20
0
Ring Toplogy
0.05
Rumor Servers in Tree Topology
120 Servers
5
Speedup
6
2
Scaling Replicas
Consider a set of servers in ring topology with
reconciliation interval of four hours.
Stale Write Rate
0
60 Servers
•
0
3
Stale Read Rate
2
1
20
40
60
80
100
Number of Servers
120