robin kravets tarek abdelzaher department of computer science university of illinois the phoenix...
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Robin Kravets
Tarek AbdelzaherDepartment of Computer Science
University of Illinois
The Phoenix Project
The Phoenix Project
Consider the aftermath of a natural disaster No power Damaged communication
infrastructure Goal
Survivable communication and networking in post disaster scenarios
Research Challenges Heterogeneous devices Diverse resource availability Diverse mobility patterns
Robin Kravets, UIUC - January 2007
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Project Goals
Protocol Stack to support Disconnected operation Service oriented
communication Resource limited
environments
Approach Exploit topology and
mobility characteristics Adapt protocol behavior
to changing conditions
Robin Kravets, UIUC - January 2007
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Police
Robin Kravets, UIUC - January 2007
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Designing Protocols for DTNs
Challenge Lack of models to describe network
topology and mobility Question
What high-level principles guide the design of efficient routing protocols for post-disaster DTNs?
Design Principles
Conservation of popularity A node that has been popular in the recent past will continue
to be popular in the near future Ties into the role of the node in the network Police-officer, rescue worker, etc
Recurrence Many network nodes tend to perform recurrent activities
Police patrols, supply shuttles, ambulances
Clustering Nodes tend to cluster
Due to mobility At aggregation points (supply centers, distress scenes, etc)
Robin Kravets, UIUC - January 2007
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Leveraging Popularity: Encouter-Based Routing
Routing Quota-based protocols
reduce resource usage Blindly distribute quota
Approach Push quota to more
popular nodes
Protocol Every node maintains an
encounter value (EV)
Exchange EVs on contact Quota transmitted is in
proportion to EV ratio
Robin Kravets, UIUC - January 2007
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EVCWCEV )1(
BA
B
EVEV
EVM
Leveraging Popularity: Encouter-Based Routing
Routing Quota-based protocols
reduce resource usage Blindly distribute quota
Approach Push quota to more
popular nodes
Protocol Every node maintains an
encounter value (EV)
Exchange EVs on contact Quota transmitted is in
proportion to EV ratio
Robin Kravets, UIUC - January 2007
The
-Day
-Aft
er N
etw
orks
EVCWCEV )1(
BA
B
EVEV
EVM
EBR 1. Resource efficient2. Low overhead / state3. Low complexity4. High message delivery ratio
Leveraging Recurrence: Inter-Contact Routing
Dynamic, yet predictable behavior Nodes may frequently meet a few other nodes at
predictable times
New routing Metric: Inter-contact delay Track recurrent contact times Construct ‘paths’ with high delivery probability
Robin Kravets, UIUC - January 2007
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B C
A
20 AC
AB
5
15B C
A
20 min loop
5
20
Encounter graph IC-Routing
Leveraging Recurrence: Inter-Contact Routing
Dynamic, yet predictable behavior Nodes may frequently meet a few other nodes at
predictable times
New routing Metric: Inter-contact delay Track recurrent contact times Construct ‘paths’ with high delivery probability
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Inter-Contact Routing1.Reduce end-to-end delay2.Save resources by reducing the number of replicas
Leveraging Clustering: Mercury
Observation Clustering occurs even in
partitioned networks
Augment store-carry-forward routing with path-based routing Base routing mechanism:
Hop-by-hop opportunistic forwarding
Use end-to-end routing when available
Light-weight clustering Route discovery throughout
lifetime of message Inter-cluster
communication when nodes move in groups
Robin Kravets, UIUC - January 2007
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Single hop connection opportunity
Multi hop connection opportunity
Leveraging Clustering: Mercury
Observation Clustering occurs even in
partitioned networks
Augment store-carry-forward routing with path-based routing Base routing mechanism:
Hop-by-hop opportunistic forwarding
Use end-to-end routing when available
Light-weight clustering Route discovery throughout
lifetime of message Inter-cluster
communication when nodes move in groups
Robin Kravets, UIUC - January 2007
The
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Mercury:1.Improved delivery ratio2.Low control overhead
Putting It All Together
Target network is dynamic Valid principles change over time
Approach: Adaptive Routing Dynamically use principles that are valid Routing layer is composed of several routing experts
Routing expert focus on a specific principle Convert expert routing information to a common metric
Routing decisions consult all experts Experts with valid assumptions provide high-confidence
paths
Robin Kravets, UIUC - January 2007
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Resource Management: Congestion Control
Observation Congestion is a global
condition Nodes only have local
(neighborhood) information
Dynamically adjust replication rate Based on current network
conditions
Collect drop, duplicate delivery and message hop statistics Compare ratio of good (dups) over bad (drops) against
congestion threshold
Robin Kravets, UIUC - January 2007
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Congestion Decrease
Environment: Mobility Modeling
Current models All nodes to follow the
same behavior Persistent behavior
Observations Object movement is
heavily dependent on events
Object reactions are completely dependent on the current role of the object
High-level framework Event-driven
Events directly change movement patterns
Role-based Nodes assume roles,
which react to events by changing their movement patterns
Robin Kravets, UIUC – April 2009
The
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Additional Research Directions
Context-awareness Survivor-activity
recognition and distress situation detection
Application automatically identifies likely distress
Device sends an SOS signal for help
Energy saving strategies Content batching to
reduce total energy consumption
Use of heterogeneous radios to improve communication energy efficiency
Robin Kravets, UIUC – April 2009
The
Pho
enix
Pro
ject
The Phoenix Project
Robin Kravets
Tarek AbdelzaherDepartment of Computer Science
University of Illinois