1. Enhancing DTN capacity with Throwboxes (work-in-progress)
Wenrui Zhao, Yang Chen,
Mostafa Ammar, Mark Corner,
Brian Levine, Ellen Zegura
Georgia Institute of Technology
University of Massachusetts Amherst

2. 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
Represent some of the most critical cases of networking

3. Capacity Limitation in DTNs
DTNs are intermittently connected
Potentially low throughput, large delay
Question: enough capacity for applications?
What if not?

4. Enhancing DTN Capacity
Use radios with longer range
Deploy a mesh network as infrastructure
Message ferrying
This presentation: Throwboxes MF S M D

5. Our Work on MF/DTN MF with Mobile Nodes [MobiHoc 04]
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]

6. 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
No need to maintain a connected network

7. Throwboxes Processor Intel PXA255 400MHz Memory 64MB SDRAM 32MB Flash
Power consumption
< 500mA
Size
3.5’’ x 2.5’’
Weight
47g

8. Example: DTN w/out Throwboxes

9. Example: DTN w/ Throwboxes

10. UMassDiesel DTN Example
w/out TB
w/ TB
Total contact duration (sec)
631
11927
Effective capacity (Kbps)
3.5
66.3
Delay (sec)
63012
3120
Data transmission between bus 38 and bus 45
A single throwbox achieves an improvement factor of 19 for both capacity and delay

11. Main Question How to best deploy ‘s Where? How to route through them?
When? Later work

12. 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

13. Network Model DTN consists of mobile nodes
Relative traffic demand between nodes bij
Total throughput λ
Given inherent capacity (w/out TBs) as a function of:
Contacts – dictated by mobility patterns
Data rate

14. 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)

15. 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

16. 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

17. 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 λ such that traffic load λbij is supported from node i to j

18. 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

19. 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 i=1 to m do
(2) find location L that maximizes λ
(3) deploy a throwbox at location L
(4) end
(5) compute routing

20. 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

21. 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
As shown in UMass example

22. 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

23. 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

24. 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

25. 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

26. Performance Evaluation
ns simulation
deployment/routing
computation
traffic demand
node mobility
throwbox locations
routing path/load
Objectives
Utility of throwboxes in performance enhancement
Performance impact of various routing and deployment approaches

27. Simulation Settings Node mobility models Simulation Parameters
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
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 messages

28. Delivery Ratio vs. Number of Throwboxes
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8 1 2 3 4 5 6 7 8
Message delivery ratio
Number of throw-boxes
T &C Aware
AbsoluteContact
RelativeContact
Random
Grid
Multi-path
routing

29. 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 1 2 3 4 5 6 7 8
Number of throw-boxes

30. Delivery Ratio vs. Number of Throwboxes
0.05
0.1
0.15
0.2
0.25
0.3
0.35 1 2 3 4 5 6 7 8
Message delivery ratio
Number of throw-boxes
MultiPath
Proportional
AbsoluteContact
RelativeContact
Random
Grid
Epidemic
routing

31. Delay vs. Number of Throwboxes (High Traffic Load)
2000
4000
6000
8000
10000
12000
14000 1 2 3 4 5 6 7 8
Message delay (second)
Number of throw-boxes
T & C
AbsoluteContact
RelativeContact
Random
Grid
Multi-path
routing

32. 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 1 2 3 4 5 6 7 8
Number of throw-boxes

33. Summary of Simulation Results
RWP
mobility
Manhattan
UMass
Multi-path
routing
Single path
Epidemic
Delay improvement
(high traffic load)
Throughput
improvement
(low traffic load)

34. Summary of Simulation Results (2)
Contact based
T & C
Multi-path
routing
Single path
Epidemic
Contact
oblivious
T & C/
T & C /
High
Low
Throughput
improvement
Routing
approach

35. 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

36. Questions?

37. Message Ferrying MF S S M MF D D M