Trading Structure for Randomness in Wireless Opportunistic Routing

1. Trading Structure for Randomness in Wireless Opportunistic Routing Szymon Chachulski, Michael Jennings, Sachin Katti and Dina Katabi MIT CSAIL SIGCOMM 2007 Presenter: Hongyu Huang 6/28/2007

2. Outline • Introduction to ExOR • Motivation of MORE (MAC-independent Opportunistic Routing & Encoding) • Design challenges of MORE • Experimental results

3. Introduction to ExOR • A Link/Network Layer diversity routing technique that uses standard radio hardware. • Achieves substantial increase in throughput for large unicast transfers in mesh network. • Since the wireless network is inherently broadcast, it is useful to take advantage of long and lossy link.

4. Comparison of Traditional Routing and ExOR S S D D Traditional routing ExOR

5. Why ExOR might work…… • Assume independent losses • Traditional routing: 1/ 0.25 + 1 = 5Tx • ExOR: 1 / (1 – (1 – 0.25)4) + 1 = 2.5Tx N1 100% 25% N1 25% 100% Src Dst 100% N1 25% 25% N1 100%

6. Design Challenges of ExOR • The nodes must agree on which subset of them received each packet. • A metric to measure the probable cost of moving packet from any node to destination. • Choosing most useful participants. • Avoid simultaneous transmission to minimize collisions.

7. ExOR Design • Before: Source organizes all packets that need to be routed to the same destination into a batch. • Initialization: Sender broadcasts a request to see which node will take participate in ExOR. • Sorting: Source includes a priority list of forwarders, ordered by “distance” to destination in every packet header. • Scheduling: Lower priority nodes wait for higher priority nodes before transmitting. • Batch map: A “batch map” is used for agreement. • Included in every packet header. • Updated from higher priority nodes back towards lower priority nodes. • Provides an acknowledgement. ETX: Estimated Transmission Counter. D. S. J. De Couto, D. Aguayo, J. Bicket and R. Morris. “A high-throughput path metric for multi-hop wireless routing,” In MOBICOM’03.

8. 1 2 3 4 5 6 7 8 9 10 Example of ExOR 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 80% B C 90% 85% 10% 20% A 35% 35% E 1 4 5 8 10 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 60% 50% D 1 2 3 4 5 6 7 8 9 10

9. Motivation of MORE • Drawbacks of ExOR • Prevents spatial reuse and thus underutilize the wireless medium. • Eliminates the layering abstraction, making the protocol less amenable to extensions of alternate traffic type such as multicast. • Throughput decreases when number of hops increase.

10. Motivating Examples • Network coding offers elegant solution to the aforementioned problems. S 50% 50% 50% 50% S R D D1 D2 D3 100% 100% P1 P1 P1 P2 P3 P2 P2 P3 P4 Unicast Multicast

11. Design Challenges of MORE • How many packets to send? • Stop and purge? • Efficient coding?

12. How Many Packets to Send? • Rule 1: Every forwarder node i keeps a credit counter for packet and forward it iff the credit counter is positive. • Rule 2: When node i receives a packet from upstream node, it increments the credit counter by its TX_credit. • Rule 3: After node i broadcasts a packet, it decrements the credit counter by 1.

13. Stopping Rule • Once the destination receives the Kth innovative packet, and before fully decoding the batch, it sends an ACK to the source. • Innovative packet: A packet is innovative if it is linearly independent from its previously received packets. • ACK are sent on shortest path reliably as soon as possible.

14. Fast Network Coding • Code only innovative packets • When a MORE forwarder receives a new packet, it checks if the packet is innovative and throws away non-innovative packets. • Operate on code vectors. • The forwarder simply checks if code vectors are linearly independent using Gaussian elimication. • Pre-coding. • MORE exploit the time when the wireless medium is unavailable to pre-compute linear combination.

15. Multicast • The source nodes does not proceed to the next batch until all destinations have received the current batch. • The forwarder list and their TX_credits for every destination are different. • TX_credit of a forwarder takes a dynamic nature.

16. Testbed • Characteristics: 20-node wireless testbed. Path between nodes are 1-5 hops in length, and the loss rates of links on these paths vary between 0% and 60%, and averages to 27%. • Hardware: Each node is a PC equipped with a NETGEAR WAG311 wireless card. They transmit at a power level of 18dBm, and operate in the 802.11 ad hoc mode with RTS/CTS disabled.

17. Major experimental results • On average, MORE achieves 20% better throughput than ExOR. In comparison with traditional routing, MORE improves the average throughput by 70%, and maximum throughput gain exceeds 10x. • When traverse paths are with 25% chance of concurrent transmissions, MORE’s throughput is 50% higher than ExOR. • For multicast traffic, MORE’s throughput gain increases with the number of destinations. For 2-4 destinations, MORE’s throughput is 35%-200% larger than ExOR’s and can be as high as 3x comparing with traditional routing. • In MORE, 90% of the flows achieve a throughput higher than 50 packets/second while 10% is only 10 packets/second in traditional routing. • MORE is insensitive to the batch size.

18. Main Contribution MORE improves the opportunistic routing gains while maintaining the clean architectural abstraction between the routing and MAC layers.

19. Thanks!