1. An Overlay MAC Layer for 802.11 Networks Ananth Rao, Ion Stoica OASIS Retreat, Jun 2004

2. Motivation Internet Gateway 802.11 hardware provides initial ease of deployability for many applications  Mesh networks  Long haul links  Large Infrastructure Networks Are these apps stretching 802.11 beyond its design goals (Wireless LANs)?

3. Problem 1: Different Data Rates Data RateThroughput Case I A11 Mbps3.09 Mbps B11 Mbps3.36 Mbps Case II A11 Mbps0.76 Mbps B1 Mbps0.76 Mbps R BA

4. Problem 2: Unpredictability 21345

5. Problem 3: Forwarding on Behalf of Others Ethernet 1/2 1/6 1/3 1/9 This problem cannot be solved by local scheduling or queue management algorithms like WFQ

6. Case for an Overlay MAC (OML) Several new MACs have been proposed to solve these problems  We try and leverage some of these techniques in OML Hardware vs. Software MACs  Huge cost advantage over building a new MAC  Flexible and easy to implement application specific policies  Facilitates experimental research on MAC layer issues  Accurate timing not possible at the software level  Devices don’t expose all information (eg. cannot carrier-sense and obtain result)  Cannot change the physical layer (eg. spread spectrum techniques)

7. Constraints Do not want to modify the MAC protocol We have no control over a packet once it is in the card’s buffer  It may be queued behind another packet Solution: Disable buffering in the lower layers  There may be some back-off and retransmission Solution: Ensure that with high probability, there will be no back off or retransmissions Use reservation-based time slots to schedule transmissions

8. Time Slots Assume local synchronization of clocks Use coarse-grained (compared to packet transmission times) time slots  20ms slots, 2ms to transmit an MTU sized packet Clocks are synchronized by estimating the 1- way delay of packets  Assume back-off is negligible and there are no retransmissions at the MAC layer  Use the minimum delay from the previous 20 packets to reduce errors

9. Weighted Slot Allocation Algorithm to allocate time-slots to competing nodes  Only requires knowledge of the IDs of other competing nodes – no additional signaling  Uses a pseudo-random hash function For ease of explanation  Stage 1: Assume the diameter of the network is one  Stage 2: Multi-hop networks of larger diameter

10. WSA – Diameter One Network Each node keeps track of an active_list, the set of nodes with active flows  Each packet includes the current queue length in the OML header Use a pseudorandom hash function to decide the winner The node with the highest H i is allowed to transmit

11. WSA – Multi-hop Network Use the same hash-based mechanism  active_list only contains other nodes that compete with a given node  Consider only the hash values of competing nodes in deciding the winner Assume that nodes interfere only up to k-hops  k is a tradeoff between losing possible channel reuse opportunities, and using the underlying MAC to resolve contention

12. Partially Overlapping Contention Regions ijk H i > H j > H k 1-hop neighbors of the winner initiate an “inactivity timer” to detect when this happens If i is more than 1-hop away from j, it is notified using a control message Contention region of k Contention region of j

13. Persistent Allocation of Slots Time 0 ms 24 ms 48 ms 72 ms Slots maybe Available for contention Assigned to a particular node If the nodes queue goes empty, the rest of the slot is used by the node with the next highest hash 12347865 Groups of 8 slots each of length 3ms

14. Amortize the Cost of Contention Resolution Time 0 ms 24 ms 48 ms 72 ms Nodes that transmitted successfully in the previous slot with index “i” own the slot with probability (1-p) Cost is amortized because A time-slot is much longer than a packet transmission Nodes compete for an average of 1/p slots at a time Orthogonal to method used to resolve contention for a slot 12347865 C C CC C C CC CCC C C CC C

15. More Details The protocol is “optimistic” in assigning a slot to a node  If a slot is assigned to more than 1 node, 802.11 will still do its best to resolve contention  If this happens very often, resource allocation goals may not be met Queues vs. Flows  Because of TCP congestion control, queues become empty and full very often  If the queue is empty, a node will signal that other nodes may send in that slot

16. Simulation Results Qualnet Network Simulator  Commercial software from www.scalable- networks.com  Packet level simulator similar to ns2, but faster and more scalable Models collisions, interference and contention Use 802.11a at 54 Mbps 20 slots of 20 ms each, p=0.05

17. Fairness in a Multi-hop network Nearly 40% of the flows receive less that 100 kbps, while others receive up to 3 Mbps without OML The disparity between 1-hop and 4-hop flows is reduced from 8 to 2 when using OML

18. Flexibility in resource allocation Qualitative differentiation is possible by assigning different weights to flows Different allocation policies can result in very different outcomes – hence the MAC layer must be flexible

19. Test-bed Hardware ASUS Pundit barebones system Celeron 2.4 Ghz, 256 MB Netgear WAG511, 802.11a Software RH 9.0, Kernel 2.4.22 Madwifi driver for Atheros Click modular router

20. Click Architecture EncapTimestamp DecapTimestamp TimeslotEnforcer ContentionResolver FromDevice ToDevice Mixed Queue Rest of the Router 1 1 Push Pull LIFO FIFO SetTimeOffset SetOKSlots

21. Results (Test-bed – Data Rates) Equal throughput – default 802.11Equal channel access time - OML OML can achieve fairness in terms of transmission time, or in terms of throughput

22. Results (Testbed – Fairness, Flexibility) In 26% of the experiments, one flow was completely shut out by the other k=2 leads to underutilization of the channel in some cases When all nodes can hear each other, WSA guarantees weighted fairness

23. Results (Test-bed) A B C

24. Conclusions and Future Work Coarse-grained scheduling on top of 802.11 is a very powerful technique to  alleviate inefficiencies of the MAC protocol in resolving contention  overcome the lack of flexibility of assigning priorities to senders Future work  Understand performance problems better though more measurements on the test-bed  More benchmarks of OML