1 multinetwork information dissemination nalini venkatasubramanian dept. of computer science cert/...
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MultiNetwork Information Dissemination
Nalini Venkatasubramanian
Dept. of Computer ScienceCERT/ UC Irvine
UCI: Valentina Bonsi, Mayur Deshpande, Hojjat Jafarpour, Kyungbaek Kim, Sharad Mehrotra, Do Minh Ngoc, Mirko
Montanari, Jeanettte Sutton, Kathleen Tierney, Bo Xing…….&
City of LA Emergency Preparedness Dept.City of Ontario, CA
Center for Emergency Response Technologies CERT Mission
lead research, technology development IT to improving emergency response. forum for collaboration between academia, industry, and government
Interdisciplinary researchers Computer Science, Social Science, Engineering
Close partnerships with local & state agencies, industry. Cities of LA/SD/Ontario/Rancho, OCFA, LA County Fire…
Responsphere – A campus-wide testbed for technology testing
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Industrial Partners5G Wireless
Broad-ranged IEEE 802.11 networking
AMDCompute Servers
Apani NetworksData security at layer 2
Asvaco1st responder (LAPD), and threat
analysis software
BoeingCommunity Advisory Board
Member
CanonVisualization equipment SDK
ConveraSoftware partnership
Cox CommunicationsBroadcast video delivery
D-LinkCamera Equipment and SDK
Ether2Next-generation ethernet
IBMSmart Surveillance Software (S3)
and 22 e330 xSeries servers
ImageCat, Inc.GIS loss estimation in emergency
response
MicrosoftSoftware
PrintronixRFID Technology
The School Broadcasting Company
School based dissemination
Vital Data TechnologySoftware partnership
Walker WirelessPeople-counting technology
Government PartnersCalifornia Governor’s Office of Emergency
Services
California Governor’s
Office of Homeland Security
City of Champaign City of Dana Point
City of Irvine City of Los Angeles
City of Ontario
Fire DepartmentCity of San Diego
Department of Health and Human Services – Centers
for Disease Control
Lawrence Livermore
National Laboratory
Los Angeles CountyNational Science
Foundation
Orange CountyOrange County Fire
Authority
U.S. Department of
Homeland Security
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Next Generation Alerting and Warning Project
Dissemination in
the Large
Content LayerResearch
Systems and Deployments
Delivery Layer Research
Wired Networks
Wireless Networks
CrisisAlert DisasterPortalEfficient Publish
Subscribe
Content Customization
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T: 0 45 secs
Scenario: Earthquake Dissemination Timeline
Warning Damage Analysis & Response
Disseminating Public Information
2-5 mins
5-60 mins
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Flash Dissemination in Wired Networks
Early Earthquake Warning Systems (0-45 seconds) Sound sirens, backup data, avoid bridges Goals: Speed and reliability
USGS Shakecast (2-5 minutes) Highly Detailed GIS data Partial infrastructure availability
Information Portals(>1 hour) Up-to-date Information from authoritative
sources Website under heavy load: Spikes crash
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Flash Dissemination in the Large (Wired Networks)
Early Earthquake Warning Systems (0-45 seconds) Sound sirens, backup data, avoid bridges Goals: Speed and reliability Approach: Reliable ALM Protocols over
P2P Networks (FareCAST)
USGS Shakecast (2-5 minutes) Highly Detailed GIS data Partial infrastructure availability Approach: Gossip-Based Random Walker
Protocols on P2P Networks (CREW)
Information Portals(>1 hour) Up-to-date Information from authoritative
sources Website under heavy load: Spikes crash Approach: P2P WebServers (Flashback)
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FaReCast : Fast and Reliable Application Layer Multicast
1. Forest-Based M2M ALM StructureMultiple Fan-In – for reliabilityMultiple Fan-Out – for speed↑Path Diversity, ↑ reliability, ↑speed
1. Forest-Based M2M ALM StructureMultiple Fan-In – for reliabilityMultiple Fan-Out – for speed↑Path Diversity, ↑ reliability, ↑speed2. Multidirectional
MulticastingDon’t fix, trigger sends judiciouslyBackup Dissemination L2L (Leaf-to-Leaf) Dissemination
2. Multidirectional MulticastingDon’t fix, trigger sends judiciouslyBackup Dissemination L2L (Leaf-to-Leaf) Dissemination
Traditional Tree : Multiple Fan-Out Efficient and Fast, Single Point of FailureNo time to recover, ack/resend
Traditional Tree : Multiple Fan-Out Efficient and Fast, Single Point of FailureNo time to recover, ack/resend
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FaReCast: Fast Reliable Appl. Layer Multicast
No significant increase in latency
for over 99% of nodes
No significant increase in latency
for over 99% of nodes
100%reliability under
40% of failed nodes
100%reliability under
40% of failed nodes
Simulation with 100,000 nodes
Simulation with 100,000 nodes
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Richer Information (2-5 minutes)CREW (Concurrent Random Expanding Walkers) Protocol
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Basic Idea: Servers ‘serve’ data to only a few clients Who In turn become
servers and ‘recruit’ more servers
Split data into chunks Chunks are
concurrently disseminated through random-walks
Self-scaling and self-tuning to heterogeneity
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CREW Protocol: Latency, Reliability
RapIDInformation Reintegration Module
Chunk Forwarding Module Neighbor Maintenance Module
CORBA-based Middleware (ICE)
Network / OS
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An Hour and Beyond…Flashback: Scalable Dissemination of Web Pages
Spike loads crash Web sites Slashdot, Disaster-Portals
A Distributed Web Server Browsers that want the web-
page are now collectively behaving as a P2P webserver No intermediaries, setup
Medium Size Content 100KB – 1-2MBs
Repeated catastrophes!!! 10 secs – user interaction,
peer download times Roulette Protocol
Grandma-proof! Setup/configure, firewalls Diverse OS, browsers
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Performance Measurement: Basic Scalability
Flashback is highly scalable HTTP download time is linear in number of nodes Flashback download time is Log in number of nodes
Test Setup Web-server hit with a “one-shot” number of clients; server 800Kbps BW Average time for a client to get the whole file measured
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Fast, Reliable Dissemination in Wireless Networks
The problem: Broadcast of rich content data over wireless networks at crisis site
Delayed Dissemination in Disconnected Networks
Hybrid Networks for Reachability and Scalability
GoalsGoals
Reliability
Timeliness
Message Efficiency
Instant Disseminationin Connected Networks
Cellular, WiFi, MANETS, DTNs, Mesh
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RADCAST: Flash Broadcast in MANETS Concurrent dissemination of awareness and content
Data diffusion: based on a mix of push/pull (Pryer) Awareness assurance: network traversal using walkers (Peddler)
Problem: fast network traversal Minimizing cover time, termination time and transmission overhead
AwarenessAssurance
Fragmentation
DataDiffusion
ReliableContent
Dissemination
Metadata
Content Data
{{
{concurrent
Walker
Walker
concurrent
Assures reception
Pull
Push
concurrent
GuidesRetrievesmissing
Spreads
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Sticker: A Protocol for Spatial Dissemination in Disconnected Networks
Replication
ForwardingContext Sens-ing & Collection
{Purging
Fixed Number of Distinct Copies
Location-Closeness Based
Aliveness-Signi-ficance Based
Devices cache and carry messages for others,
Messages exchanged during encounters
Problem: Post messages to a geographic location without infrastructure support h
Instant Mesh Networks
Network Backhaul
Mesh Backbone
Client Latency
MobileClients
Backbone Latency Gateway
Data Network
Dynamically deployed mesh networks for providing short-term infrastructure coverage at incident/event sites
• Fast, easy deployment• Expanded coverage• External information
Gateway Designation in Instant Mesh Networks
Given:Given:
GoalGoal::
OptimizeOptimize::
A connected network formed by stationary mesh routers An initiator mesh router
Distributedly find the mesh router with maximum centrality and report it to the initiator mesh router
Transmission Efficiency: least number of transmissions Time Efficiency: least execution time
Closeness Centrality:Closeness Centrality:1
( )( , )c
t V
nC v
d v t
1( )
max ( , )g
t V
C vd v t
Graph Centrality:Graph Centrality:
-- Capturing average backbone latency-- Capturing max backbone latency
Measured based on link quality metrics
The Problem:To determine which mesh router in a given mesh backbone should serve as the gateway, so that backbone latency is minimized.
FACE: An Approximation Algorithm
CentralityMeasuring
ExtremaFinding
GatewayDesignation{
Popping up the maximum centrality along a spanning
tree rooted at initiator (PST)
Popping up the maximum centrality along a spanning
tree rooted at initiator (PST)
Centrality Approximation using spanning tree root/leaves as sample
points
Centrality Approximation using spanning tree root/leaves as sample
points
Distance Notification through Spanning trees (SSTs) for centrality
calculation
Distance Notification through Spanning trees (SSTs) for centrality
calculation
FACEFACEFACEFACE
Centrality Approximation:Centrality Approximation:Using randomly picked nodes as sample points to approximate centrality [Eppstein SODA 2001]- additive error based on number of sample points
Some Performance Results
The FACE-designated gateways significantly enhances the timeliness of disseminations of external information.
Impact of FACE on Inbound dissemination latencies (32KB data)
Mesh Network Deployments
Commercial mesh routers not good enough
5X improvement with new antenna technology
Better signal coverage better building penetration
• Some Setup effort required • Not always feasible• Vulnerable to hardware failures
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In the future
Research Geographically Correlated Failures Uncertainty and Correlations in Information Dissemination Understanding/Incorporating Social Media dissemination
Twitter, Facebook, rimoftheworld.net Multinetwork messaging Towards a Unified Warning Model and System
Implementation Standards, Multihazard warning
Testing and Deployment Partnerships, Pilot Studies
Training
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BACKUPS
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Organization PolicySpecifications
•Who will receive the notifications?
•What modalities will be used?
•School Principal:
•Receives updates
•Makes decisions
•Communicates decision to others
•All Staff
•Receives messages
CrisisAlert – A Meta Alerting System for Organizations
Crisis PolicySpecifications
Crisis Alert
•Which messages to send?
•Who should receive them?
•Personalization and Customization
Crisis Information from Emergency Operations Center
Automatic notification systems (USGS, EDIS, CAP based systems. ..)
Proprietary delivery mechanism used by the organization/school
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Implementation on Mobile Devices
Maemo
Spatial Dissemination
RADcast
Flash Broadcast
People close to the epicenterDetailed map of the damages
Location of sheltersPeople close to chemical facilities
Map of the damaged area, Location of the dangerous
chemical facilitiesInformation about the chemical
People in safe areasHospital information
General information about the emergency
Short & Long Term Warning
Part of the Disaster Portal Project: in use by the City of Ontario
Earthquake ScenarioEarthquake Scenario
Timeline
Shakecast Information
Detailed Information
Earthquake Early Warning
Visual and sound notifications of
“Duck and Cover”
Earthquake hits the area
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Map of the affected areaGeneric first-aid information