1 / 27

Delay Tolerant Mobility Aware Routing/Mobility Dissemination Protocol for the Airborne Network

Delay Tolerant Mobility Aware Routing/Mobility Dissemination Protocol for the Airborne Network. Kevin Lee & Adam Piechowicz 10/10/2009. Problem Statement. An end-to-end path is not always guaranteed Packets have to be delivered in a delay-tolerant fashion

reba
Download Presentation

Delay Tolerant Mobility Aware Routing/Mobility Dissemination Protocol for the Airborne Network

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Delay Tolerant Mobility Aware Routing/MobilityDissemination Protocol for the Airborne Network Kevin Lee & Adam Piechowicz 10/10/2009

  2. Problem Statement • An end-to-end path is not always guaranteed • Packets have to be delivered in a delay-tolerant fashion • How to use planned AN backbones’ trajectories to deliver packets to minimize: • Packet failure rate • Delay • Local buffer

  3. Contributions • Provide best next forwarding hop in the delay tolerant network based on current network condition • Provide congestion avoidance and load balancing by local queuing awareness mechanism

  4. MARP/MDP+DTN Design • Think of the topology as a time-varying graph • We can select the best next hop given a specified metric (minimum delay) • Use modified Dijkstra’s algorithm with time-varying edge costs • w(e(u,v), t) indicates the cost of using edge (u, v) after time time t • The cost is predominantly the time after t that (u, v) is up • Propagation delay negligible • Transmission rate not considered

  5. Example 1 • Source node at 1 and each edge cost is 1

  6. Example 2

  7. Predecessor Computation • Take Node 3 from Example 2 • 2, 2 means: • It will take Node 1 to reach Node 3 with cost of 2 (the first 2) • The predecessor of Node 3 is Node 2 (the second 2) • One can then trace back to get the complete route traversal and the time at which the packet should be sent

  8. Local Queuing Aware Scheduling • Network disconnectivity increases queuing delay • Queuing delay increases congestion • Route around congestion by considering neighbors’ queue size • w(e, L[u] + T) will incorporate: • The cost of sending packets already in the queue plus, • The cost of sending the last packet scheduled to use u to deliver to v

  9. Importance of Encountering for Queuing Awareness • The more frequently a node encounters with another node, the more packets the node can offload to that node • Intuitively, the link between these two nodes provide lower delay to the destination • Two types of encountering: • Single • Multiple

  10. Single Encountering • A node A single encounters another node B if node A meets node B only once in a period • Where time(1,e,L[u]+T) indicates the time Node u meets Node v at which time one packet in Node u’s queue is delivered since L[u] + T • P is the period of the time-varying graph • Qsize is the queue size at Node u

  11. Single Queuing Example • Assume there are 2 messages in Node 2’s queue

  12. Single Queuing Example (cont.) • w(e(2,3), 1) = 5 + 6 + 6 because it takes • 5 more seconds to dequeue the first packet, • 6 seconds to dequeue the second packet, • another 6 seconds to dequeue the last packet • By the eqn, w(e(2,3), 1) = 5 + 6 * 2 = 17 • Packets in Node 2’s queue will use the same edge in consideration, e.g., • w(e(2,3),1) considers first two packets going to Node 3 • w(e(2,4),1) considers first two packets go to Node 4

  13. Multiple Encountering • A node A multiple encounters another node B if node A meets node B more than once in a period • Tx(e,t) is the # of times e is up during the remaining time t of one period

  14. Multiple-Encounter Queuing Example • Assume there are 2 messages in Node 2’s queue

  15. Multiple-Encounter Queuing Example (cont.) • w(e(2,3), 1) = 3 + 2 + 4 because it takes • 3 more seconds to dequeue the first packet, • 2 more seconds to dequeue the second packet, • 4 seconds to dequeue the last packet • Since Qsize (=3) > Tx (=2), eqn (2) is used: • w(e(2,3), 1) = (6 – 1) + 0 + 4 = 10

  16. Handling Multiple-Traffic Flows • Contacts (the time-varying at any given point in time) is known • Local queuing is known; approximate global queuing by keeping track of messages along each routing path • Traffic demand is known, • It is a set of messages • Each message is a tuple (u,v,t,m), where u is the source of the msg, v is the destination, t is the time the msg is sent, m is size • Buffer constraints are given • THE ORACLE HAS COMPLETE KNOWLEDGE! – A linear programming exercise

  17. Approximate Optimality • LP is computationally expensive! – Computation become too large for practical example • Use contacts and queuing oracle (EDAQ) instead • “EDAQ compares favorably, in terms of average delay, with the optimal solution.” • However, • Global knowledge may not be required for good performance in many cases • Implementing the queuing oracle, in particular, may not be worthwhile

  18. Approximate Optimality (contd.) • Contact oracles (ED) might just be enough for our scenarios! • Lesson: TOO MUCH KNOWLEDGE MAY NOT ALWAYS BE GOOD!

  19. Evaluation

  20. MARP/MDP vs. MARP/MDP+DTN • Network Flow from GlobalHawk to AWACs 2 • Solid arrow shows the desired network flow • Dotted lines shows current available connections • 3 experimental variables • Radio range • Delay tolerance • Flow volume

  21. Results • Delay tolerance represents largest improvement in packet delivery, 52% (col1 &2) • Fixed range: Low flow has higher delivery and lower latency (col 1 & 3) • Fixed flow: High radio range has higher delivery ratio and lower latency than low radio range

  22. MARP/MDP+DTN vs. MARP/MDP+DTN+QC • Two separate rate flows from 1 and 2 to 5 • Transmission rates range from 2.048 Mbps to 1024 kbps

  23. Results • When transmission rate is high, PDR for MARP/MDP+DTN is 0%

  24. Packet Difference between Node 3 and 4 • Both flow forward to Node 3 heavily in MARP/MDP+DTN • MARP/MDP+DTN+QC is able to divert traffic and achieve load balancing

  25. Latency • Delay extremely long in MARP/MDP+DTN • Result indicates the need for local queuing awareness

  26. Conclusion & Future Work • MARP/MDP+DTN shows the benefit of delay tolerance • MARP/MDP+DTN+QC shows the benefit of local queuing awareness • Congestion scenario configuration to verify local queuing aware scheduling • Tune parameters/routing metrics of MARP/MDP+DTN+QC protocol in accordance with flight and link data obtained from real flight tests like Capstone II

More Related