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

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

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

Problem 2: Unpredictability 21345

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

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)

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

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

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

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

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

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

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 Groups of 8 slots each of length 3ms

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 C C CC C C CC CCC C C CC C

More Details The protocol is “optimistic” in assigning a slot to a node  If a slot is assigned to more than 1 node, 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

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

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

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

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

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

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

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

Results (Test-bed) A B C

Conclusions and Future Work Coarse-grained scheduling on top of 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