Transportation-aware Routing in Delay Tolerant Networks (DTNs)

1. Transportation-aware Routing in Delay Tolerant Networks (DTNs) Asia Future Internet 2008 Taekyoung Kwon Seoul National University

2. outline 1 Introduction 2 Scenario Model 3 Our Approaches 4 Summary

3. Introduction • DTN • Delay (or Disruption) Tolerant Networks • Delay? Disruption? • Interplanetary networks • Sensor networks • Nodes sleep to save power • Vehicular networks • Mobile devices getout of other devices’ radio ranges • Opportunistic networks • a sender and a receiver make contact at an unscheduled time • Underwater networks

4. Introduction • Motivation • DTNs may have to be accommodated in future networks • Intermittent connectivity • Long or variable delay • Asymmetric data rates • Heterogeneous links • High packet error rates • Limited node uptime

5. Research Issues in DTNs • Delay Tolerant Network Architecture • Overall redesign • E.g. Bundle Protocol • Routing Protocols • Delivery ratio • Reducing delay • Congestion control • Distributed Caching • Multicast/Anycast

6. E2e connectivity may not exist at the same time • Routing (e.g. MANET) performs poorly in DTN environments • Some assumptions for routing will not work • E.g. BGP leverages TCP IP routing may not work Source: Kevin Fall, IRTF DTN RG

7. Related Work (mobility) • Mobility model DTN No Mobility Mobility Routine Random Predictable Tendency-based

8. Related work (routing) • Some Routing Strategies • Epidemic routing • Flooding • Spray and wait (S&W) • Limited number of copies of a message • Important Metrics • delivery probability • delivery latency • overhead ratio

9. Motivation • Existing routing protocols use only past information like contact history, etc. • DTN Routing can leverage additional information in the future • speed, direction, destination of mobile node, etc. • We want to propose routing protocol using these additional information

10. Scenario Model • When to use DTN? • DTNs can be used for delay tolerant applications • environmental monitoring, some publish/subscribe applications • We assume that each node has location information • E.g. GPS, Navigation, localization techniques

11. Potential Approaches • Leveraging mobility information • Direction of mobile host • Speed of mobile host • Location of mobile host’s destination • Location of message’s destination • Message’s destination can be fixed or mobile • Our approaches • Direction-based • Destination-based • Transportation info-based

12. Our Approach 1 Direction-Based routing protocol Spray & Wait based Number of tokens: n Number of split tokens depends on direction difference sender’s direction 0 ° hand over -n*angle/180° tokens -90° hand over n*angle/180° tokens hand over n/2 tokens 90 ° receiver’s direction

13. Our Approach 2 Receiver’s destination distance Sender’s destination • Destination-Based routing protocol • Spray and wait based • Number of tokens for handover • n/2*( distance / max diameter ) MAP Maximum diameter

14. Hybrid of approaches 1 and 2 Direction-Distance-Hybrid (DDH) n/2*Direction(d1)*Distance(d2)*Speed(s) Direction(): function ranged [0,1] Distance(): function ranged [0,1] Speed(): function ranged [0,1] d1: direction difference of two nodes d2: distance difference of two nodes’ destinations s: difference of nodes’ speeds

15. Simulation results (1/2) • Simulator • The Opportunistic Network Environment (ONE) simulator • http://www.netlab.tkk.fi/~jo/dtn/ • Parameter settings

16. Simulation results (2/2) • Comparison btw. S&W and DDH • DDHcan deliver 18% more packets than S&W • When destination is fixed * : # of delivered packets per 1000 relayed packets

17. Problem of Previous Approaches Randomization effect problem It is caused by local view of tendency As number of contacts is increased, direction or distance is randomized Effect of our proposal gets reduced Angle = 90° ∴ handover n/2 tokens • An illustration • Some tokens can be carried in the same direction • movement information that decides the number of copies relayed becomes meaningless 1st contact 2nd contact Angle = 90° ∴ handover n/4 tokens

18. Scenario Model • A DTN area consists of a certain number of subareas or regions • There isa need of DTN between regions due to poor infrastructure or delay tolerant application • How to dissemination messages between regions efficiently Region 2 Region 1

19. Our Approach 3 • Prevention of randomization problem using history • Area is divided into several sub areas with non uniform distribution • Token handover policy • When a source creates the message, it reserves a fixed number of tokens for each sub-area • If the source meets a mobile host toward other regions, it sends the message to the host with pre-reserved tokens • Tokens can be distributed more evenly across the area 19

20. Simulation Settings • Simulator: Opportunistic Network Environment (ONE) • Area size: 45 X 34km2 • 4 sub-areas (20x15km2 each) • # of nodes: 500 • Intra-area node & Inter-area node • Tx range: 100m • Speed: 100km/h, 4~60km/h • S&W copies: 32 • Packet • # of packets: 1000 (2 packets per each node) • Packet size: ~ 30KB • Buffer size big enough

21. Simulation Results • Destination is mobile • Delivery ratio = # of delivered packets / # of originated packets

22. Overhead ratio = (# of relayed - # of delivered) / # of delivered Average number of relay nodes Simulation Results

23. Avg. latency Med. latency Simulation Results

24. Conclusions • DTNs may play a vital role in future • Routing is a key player in DTNs • We proposed • Direction-based • Distance-based • Transportation info-based • Destination’s mobility affects the routing performance • The more information, the better routing