Event-driven, Role-based Mobility in Disaster Recovery Networks

The Phoenix Project

Robin KravetsDepartment of Computer ScienceUniversity of Illinois

Robin Kravets, UIUC - January 2007

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Day After Networks

Consider the aftermath of a natural disaster No power Damaged communication

infrastructure Cell towers Switching stations Emergency response

Goal Survivable communication

and networking in post disaster scenarios Support disaster

recovery efforts Provide connectivity to

survivors

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Communication in DANs

Emergency personnel Police, Fire, EMS, FEMA, … Intra-agency communication

Dedicated pre-configured networks

Inter-agency communication Civilians

Survivors Communication with

emergency personnel Communication with family

Police

Fire

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Post-disaster Communications

Challenge Disconnected operation Service oriented More resources may not help No fixed infrastructures

Approach Hop-by-hop communication paradigm Group based communication Take advantage of all available resources

Personal wireless devices Cell-phones in P2P mode Car-battery-operated WiFi mesh nodes Traditional Radio

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DAN Network Model

Internet

WLAN

2/3 G

MESH

DAN Cluster

WLAN

2/3 G

MESH

DAN Cluster

BT

DAN Cluster

WLAN

2/3 G

MESH

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Mapping the Network

Network nodes Static and dynamic Locally roaming

relief workers assigned a location

Globally roaming Patrolling police

vehicles A notion of recurrence

Workers tend to perform repetitive tasks

Chain of command entails fixed reporting hierarchies

Research challenges Mobility and

connectivity patterns Take advantage of

recurrence predictions to maximize delivery ratio

Provide resource sharing incentives

Detect and protect against malicious behavior

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Challenges

Network Topology Inherently partitioned

Response personnel are close to event People stand around far from event

Node Behavior Role-based

Responders act differently then civilians Vehicles may oscillate between events and bases

Event-based Behavior may change based on specific events

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Mobility Models

Fixed Models Random Movement

Walk in a randomly chosen direction Object Avoidance

Walk around objects, buildings, etc. Flocking

Walk with others in your group

Challenge Current models require all nodes to follow the same

behavior Although mobility is random, there is no support for

reaction to events

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Event-driven, Role-based Mobility

Observation Object movement is heavily dependent on

events Event characteristics Proximity to event

Object reactions are completely dependent on the current role of the object Civilians flee from events Police gravitate towards them Ambulances move between events and hospitals

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Disaster Events

Events are stimuli for object reaction

Event

Damage RadiusObjects become immobile

Event HorizonCivilians stop here heavy clustering

Immediate Reaction area becomes sparse, partitioning the network

Radio Contactreact only after radio contact occurs

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Objects and Roles

Roles define movement patterns for similar objects

Event

C

C

C

C

P

P

A

HospitalPolice and Ambulances outside of EH do not react before radio contact

C: CiviliansP: PoliceA: Ambulance

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Gravity-Based Reaction

Use gravity to model flee and approach F = I / d2 where I is the event intensity Sum of all forces affects velocity vectors

Can quickly and dynamically handle any number of events acting on objects

Event Event

C

Resulting velocity vector

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Topological Metrics

Common metrics Average node density Average path length

Problem These do not capture the characteristics of disaster

networks Better metrics

Time based Is graph partitioned at a given time? How clustered is the graph at a given time? Average, maximum, and variance of node density over time

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Simulation Tools

Two tools help generate ns2 mobility trace files from simple input parameters

paramGen > paramFile Input: size, #civilians, #police, #ambulance Output: Structured list of randomized and deterministic

parameters

disasterSim [-d] < paramFile > nsMobilityTrace Input: paramFile Output: runs complete simulation with our disaster mobility

model and produces nsMobilityTrace file

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Simulation Setup

1500 seconds long on 1000m2 grid 4 events, 75 civilians, 10 police, and 15 ambulances

randomly placed 10 sets of simulations, each set containing 2

simulations: One with events (simulating our disaster mobility model) One without events (simulating Random Walk) Same parameters used within a set

Events & radio contact occurs between 100 and 355 seconds

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Network Snapshots

0 50 100 150 200 250 300 350 400 500 600 800 1000 1200 14000 50 100 150 200 250 300 350 400 500 600 800 1000 1200 14000 50 100 150 200 250 300 350 400 500 600 800 1000 1200 14000 50 100 150 200 250 300 350 400 500 600 800 1000 1200 14000 50 100 150 200 250 300 350 400 500 600 800 1000 1200 14000 50 100 150 200 250 300 350 400 500 600 800 1000 1200 14000 50 100 150 200 250 300 350 400 500 600 800 1000 1200 14000 50 100 150 200 250 300 350 400 500 600 800 1000 1200 14000 50 100 150 200 250 300 350 400 500 600 800 1000 1200 14000 50 100 150 200 250 300 350 400 500 600 800 1000 1200 14000 50 100 150 200 250 300 350 400 500 600 800 1000 1200 14000 50 100 150 200 250 300 350 400 500 600 800 1000 1200 14000 50 100 150 200 250 300 350 400 500 600 800 1000 1200 14000 50 100 150 200 250 300 350 400 500 600 800 1000 1200 14000 50 100 150 200 250 300 350 400 500 600 800 1000 1200 1400

Events Occur

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Average Node Density

Connected components are “more connected” in the disaster mobility model

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Disaster Mobility Model Random Walk

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Clustering Coefficient

How well a node’s neighbors know each other. Disaster mobility model topology is more clustered,

and becomes clustered quickly after events.

0.6

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Disaster Mobility Model Random Walk

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Network Partitioning

1 = partitioned, 0 = not partitioned Indicates DTN-style routing may be necessary, with

ambulances acting as bridges.

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Random Walk Disaster Mobility Model

Event-driven, Role-based Mobility in Disaster Recovery Networks

Robin KravetsDepartment of Computer ScienceUniversity of Illinoishttp://mobius.cs.uiuc.edu/

The Phoenix Projecthttp://mobius.cs.uiuc.edu/phoenix.htm