Enhancing DTN capacity with Throwboxes workinprogress

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Enhancing DTN capacity with Throwboxes(work-in-p
rogress)

• Wenrui Zhao, Yang Chen,
• Mostafa Ammar, Mark Corner,
• Brian Levine, Ellen Zegura
• Georgia Institute of Technology
• University of Massachusetts Amherst

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Delay Tolerant Networks (DTN)

• DTNs non-Internet-like networks
• Intermittent connectivity
• Large delays
• High loss rates
• Examples of DTNs
• Tactical networks, disaster relief, peacekeeping
• Interplanetary networks, rural village networks
• Underwater acoustic networks
• DTN features
• Store-Carry-and-forward
• Message switching

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Capacity Limitation in DTNs

• DTNs are intermittently connected
• Potentially low throughput, large delay
• Question enough capacity for applications?
• What if not?

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Enhancing DTN Capacity

• Use radios with longer range
• Deploy a mesh network as infrastructure
• Message ferrying
• This presentation Throwboxes

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Our Work on MF/DTN

• Ferry Route Design Problem FTDCS 03
• MF with Mobile Nodes MobiHoc 04
• Efficient use of Multiple Ferries INFOCOM 05
• The V3 Architecture V2V Video Streaming PerCom
  05
• Ferry Election/Replacement WCNC 05
• MF as a power-savings device PerCom 05
• Multipoint Communication in DTNs/MF WDTN 05,
  WCNC 06
• Power Management Schemes in DTNs/MF SECON 05,
  PerCom 05
• Road-side to Road-side relaying using moving
  vehicles WCNC 06

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Throwboxes

• Basic idea add new devices to enhance data
  transfer capacity between nodes
• Deploy throwboxes to relay data between mobile
  nodes
• Throwboxes are
• small, inexpensive, possibly dispensable,
  battery-powered wireless devices
• Some processing and storage capability
• Easy to deploy and replenish

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Throwboxes
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Example DTN w/out
Throwboxes
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Example DTN w/ Throwboxes
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UMassDiesel DTN Example

• Data transmission between bus 38 and bus 45
• A single throwbox achieves an improvement factor
  of 19 for both capacity and delay

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Main Question

• How to best deploy s
• Where?
• How to route through them?
• When? -- Later work

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Throwbox Deployment Routing Framework

• Objective throughput enhancement
• Important to deliver data
• May improve delay too
• Deployment issue
• Where to place throw-boxes?
• Routing issue
• How data are forwarded?

• Contact-oblivious
• Contact-based
• Traffic and Contact based

• Single path routing
• Multi-path routing
• Epidemic routing

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Network Model

• DTN consists of mobile nodes
• Relative traffic demand between nodes bij
• Total throughput ?
• Given inherent capacity (w/out TBs) as a function
  of
• Contacts dictated by mobility patterns
• Data rate

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Throwbox Assumptions

• Sufficient energy supplies
• No interaction between throwboxes
• Deployed to a given set of potential locations
• Center of Grid Cells
• Deployment Vector (0/1 vector)

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Throwbox Deployment Routing Framework
Deployment approach
Traffic Contact based
Contact based
Contact oblivious
Random or Regular Deployment
Routing approach
Multi-path routing
Single path routing
Epidemic routing
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Throwbox Deployment Routing Framework
Deployment approach
Traffic Contact based
Contact based
Contact oblivious
Random or Regular Deployment
Routing approach
Multi-path routing
Single path routing
Epidemic routing
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Multi-Path Routing Traffic and Contact-Aware
Deployment

• Need to determine
• Deployment locations of throwboxes
• Routing paths and traffic load on each path
• Performance objective
• Given m throwboxes, maximize total throughput ?
  such that traffic load ?bij is supported from
  node i to j

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Multi-Path Routing Traffic and Contact-Aware
Deployment

• Formulated as an 0/1 linear programming problem
• Throwbox deployed at location ? 1
• Solution also gives optimal flow vector
  describing use of multiple paths
• NP-hard to solve optimally

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Greedy Heuristic

• Deploy throwboxes one by one
• Given throwbox locations, (2) is a concurrent
  flow problem
• Solved by network flow techniques or linear
  programming tools

(1) for i1 to m do (2) find location L that
maximizes ? (3) deploy a throwbox at location
L (4) end (5) compute routing
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Throwbox Deployment Routing Framework
Deployment approach
Traffic Contact based
Contact based
Contact oblivious
Random or Regular Deployment
Routing approach
Multi-path routing
Single path routing
Epidemic routing
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Multi-Path Routing Contact-Based
Deployment

• Throwbox deployment is based on contact
  information, but not traffic information
• Benefits varying traffic patterns
• May not be optimal for specific traffic
• Maximize
• Absolute contact enhancement
• Maximize absolute enhancement of contact between
  nodes
• Relative contact enhancement
• Maximize relative enhancement of contact between
  nodes

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Throwbox Deployment Routing Framework
Deployment approach
Traffic Contact based
Contact based
Contact oblivious
Random or Regular Deployment
Routing approach
Multi-path routing
Single path routing
Epidemic routing
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Single Path Routing

• Single path routing
• Data for a S-D pair follow a single path
• Adapt greedy algorithm for multi-path routing by
  enforcing the single path requirement

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Throwbox Deployment Routing Framework
Deployment approach
Traffic Contact based
Contact based
Contact oblivious
Random or Regular Deployment
Routing approach
Multi-path routing
Single path routing
Epidemic routing
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Epidemic Routing

• Epidemic routing (ER)
• Difficult to characterize traffic load among
  nodes because of flooding
• ER exploits all paths to propagate data
• Multi-path heuristic
• Proportional allocation heuristic

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Performance Evaluation

• Objectives
• Utility of throwboxes in performance enhancement
• Performance impact of various routing and
  deployment approaches

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Simulation Settings

• Node mobility models
• Predictable/constrained UMass model based on
  measured bus trace
• Random/unconstrained Random waypoint model
• Random/constrained Manhattan model
• Simulation Parameters
• 9 nodes in a 25Km x 25 Km area
• 802.11 MAC, radio range 250m, bandwidth 1Mbps
• 20 source-destination pairs, message size is 1500
  bytes, Poisson message arrival with same data
  rate
• FIFO buffer, buffer size is 50000 messages

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Delivery Ratio vs. Number of Throwboxes
Multi-path routing
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Delivery Ratio vs. Number of Throwboxes
0.45
0.4
0.35
0.3
Single path routing
0.25
Message delivery ratio
0.2
0.15
T C Aware
0.1
AbsoluteContact
RelativeContact
0.05
Random
Grid
0
0
1
2
3
4
5
6
7
8
Number of throw-boxes
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Delivery Ratio vs. Number of Throwboxes
Epidemic routing
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Delay vs. Number of Throwboxes(High Traffic Load)
Multi-path routing
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Delay vs. Number of Throwboxes(Low Traffic Load)
6000
5000
4000
Multi-path routing
Message delay (second)
3000
2000
T C
AbsoluteContact
1000
RelativeContact
Random
Grid
0
0
1
2
3
4
5
6
7
8
Number of throw-boxes
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Summary of Simulation Results
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Summary of Simulation Results (2)
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Summary

• Study the use of throwboxes for capacity
  enhancement in mobile DTNs
• Develop algorithms for throwbox deployment and
  routing
• Routing multi-path, single path, epidemic
• Deployment traffic and contact, contact-based,
  contact-oblivious
• Evaluate the utility of throwboxes and various
  routing/deployment approaches
• Throwboxes are effective in improving throughput
  and delay, especially for multi-path routing and
  predictable node mobility

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• Questions?

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Message Ferrying
MF