Wireless MACs (reprise): Overlay MAC

Wireless MACs (reprise): Overlay MAC Brad Karp UCL Computer Science CS 4C38 / Z25 24th January, 2006

Many competing schemes for MACs, even slotted ones! This paper: measure underlying problem; build real implementation; evaluate it. Context: 802.11 MAC and Forwarding • MACAW (1994) • Communication range = interference range • No carrier sense • RTS/CTS for hidden terminal problem • 802.11b standard (mid 90s) • Designed chiefly with base stations in mind • Carrier sense and RTS/CTS • Interference range > communication range • Roofnet (2005) • Multi-hop forwarding using 802.11b • RTS/CTS disabled (no help to performance) • Collisions between forwarders in a chain • Highly asymmetric packet loss rates on many links • Overlay MAC (2005) • Study pathologies when 802.11a applied to multi-hop forwarding • Propose time-slotted “overlay” for 802.11a to alleviate problems

Motivation: 802.11’s Shortcomings • Asymmetric interaction between nodes • at senders • at receivers • Rigid allocation of bandwidth among flows • no application choice of bandwidth allocation • poor fairness among flows for some traffic workloads

802.11a Testbed • Indoor, chain topology • No other 802.11 traffic in band • UDP broadcast packets • TCP

Motivation:Asymmetric Carrier Sense at Senders • All 15 node pairs: greedy broadcast UDP • Far apart nodes: • ca. 5.1 Mbps • senders send simultaneously; don’t sense one another’s carriers • Close nodes: • ca. 2.5 Mbps each • senders share fairly; sense one another’s carriers • Three cases: • one sender >= 4.5 Mbps, other <= 800 Kbps • no RTS/CTS; no ACKs; no transport protocol • only explanation: one sender can’t sense other’s carrier • doesn’t depend on receiver

Motivation: Asymmetric / Symmetric Interaction at Receivers • Sender pairs who can broadcast at full rate, each sends greedy UDP unicast • Example 1: • 1  2 3  4 • 85% packet drops from 1 to 2 • sending rate drops > 60% from 1 to 2 • Example 2: • 1  2  3 • 35% packet drops for both 1 and 2 • channel utilization: drops by 55%

Motivation: Rigid Bandwidth Allocation • How do you divide capacity when senders use auto bit-rate selection? • 802.11 answer: equal number of transmit opportunities for senders… • …but each packet may be at different bit-rate • Heterogeneous sending rates: • 1  AP  2 • 1 sends at 54 Mbps • 2 sends at {6, 12, 18, 36, 54} Mbps • Fair, but total utilization drops as node 2 slows! • Unpredictable: • Node 1 alone: 24 Mbps • Node 2 joins at 6 Mbps: Node 1 gets 3.6 Mbps

Motivation: Forwarding and Fairness • 802.11 doesn’t consider forwarding in b/w allocation • Interference range twice transmission range • N2 can’t receive during xmits of {N4, N5, N6} • N3 can’t receive during xmits of N1 • 802.11’s bandwidth allocation • N1 and N3: 1/3 each of N2’s bw • N4, N5, N6: 1/9 each (equal share of 1/3) • Fairer would be • N3: 3/7 • N1, N4, N5, N6: 1/7 N1 N2 N3 N4 N6 N5

Motivation: (More) Unfairness • Two flows: 1  2 and 3  4 • One at a time: each 4.6 Mbps • Simultaneously: one > 4 Mbps, one < 100 Kbps • Rate limiting both to 2.3 Mbps: one 2.3 Mbps,one 580 Kbps

Assumptions • Unicast and broadcast transmission supported • Promiscuous mode listening • RTS/CTS configurable “off” • Limit transmit queue to 1-2 packets • Why?

OML: Design Overview • Divide time into slots • All nodes agree on slot boundaries • Need loosely synchronized clocks • Mutually interfering nodes contend for same set of slots • Which nodes mutually interfere? • Each slot in set owned by one sender • Senders may have weights; bandwidth divided proportionally to weights

OML: Clock Synchronization • Real hardware clocks don’t tick at promised rate • oscillators in PCs are typically off by 1 – 100 μs per s • 1 – 2 μs change per degree C! • skew: difference in frequency between two clocks • Many proposed algorithms for sync’ing distributed clocks in many settings • OML solution: • single leader node broadcasts timestamps • estimate propagation delay to receivers • receivers estimate their own skew; apply correction • goal: error must be much smaller than slot length

OML: Slot Length • Constraints • longer than clock error • longer than packet transmission time • otherwise, as short as possible • Value in evaluation • 5 max-sized (1500-byte) packets • 10 ms @ 6 Mbps

OML Algorithm 1:Diameter One, Unit Weights • Pseudo-random hash function • Output uniformly random in (0, 1] • Hi = H(ni, t), for c nodes, 1 ≤ i ≤ c • ni = node ID of node i (integer, unique per node) • t = time slot ID (increasing integer) • Assume all nodes who contend know one another’s ni • Each node can locally compute Hi for all its neighbors • Biggest Hi wins; winner is r, where:

OML Algorithm 2:Diameter One, Arbitrary Weights • Suppose node i wants weight wi • Redefine Hi() in terms of wi: • Nodes must know wi of all nodes they contend with (within interference zone) • Winner r of slot is still node with greatest Hi in that slot • Proven in tech report:

OML Algorithm 3:Diameter > 1 • Only nodes that can interfere with one another must compete for slots • What set of nodes interfere with one node? • Radio ranges highly variable • No very satisfying, scalable answer! • Solution in paper: assume a fixed, k-hop interference zone • nodes broadcast for k hops intent to contend • greater k  assume more nodes mutually interfere • greater k  utilization may decrease

OML Algorithm:Diameter > 1 (cont’d) • Overlapping interference regions reduce utilization • Suppose H1 < H2 < H3 • H1 and H2 will both think they’ve “lost,” but H1 and H3 don’t interfere! 1 2 3

OML Algorithm:Slot Groups • Each slot owner relinquishes slot with probability (1-p) in each group • Nodes know locally when slot relinquished; use another pseudo-random hash function in (0, 1] • After slot relinquished, others in zone compete for it • Reduces chance of race in previous slide

Evaluation: Simulation • QualNet simulator • 802.11a, 6 Mbps fixed rate • Two-ray ground reflection model (350 m range) • RTS/CTS disabled • 50 nodes / km2, randomly placed • Slot time: 10 ms (5 1500-byte pkts) • Group size: N = 20 slots • k = 2 • AODV routing • 1 simulated minute

Metric: Fairness Index • M flows • weights w1, …, wM • Throughputs x1, …, xM • Fairness index, F: • F = 1 when all flows’ throughputs proportional to weights • F = 1/M when one flow starves all others

Simulation: Packet Transmissions • Workload: 10 UDP flows, different sources, one sink • OML successfully avoids simultaneous contending transmissions • OML is too conservative; delivers fewer packets successfully than 802.11

Simulation: Average Throughput • 5- and 10-flow workloads • Throughput comparable for OML vs. 802.11

Simulation: Fairness • Nodes set weights to number of unique source IPs in output queue; unit weight per flow • Per-source-IP queues; round-robin among queues • N.B. fairness of 1 impossible; not all flows contend with all others • OML more fair than 802.11

Simulation: Throughput and Path Length • Narrower span of throughputs for OML than for 802.11 • Improved fairness across varying path lengths, but less total capacity

Testbed: Heterogeneous Data Rates • Two senders: one fixed at 54 Mbps, one varying from 6 to 54 Mbps • Same weights at both senders; equal channel access time at each sender • Proportional sharing • Increased total throughput vs. 802.11

Testbed: Chain Topology • 5-hop chain testbed • Two one-hop flows on random links • One flow at a time • Simultaneous, no OML • Simultaneous, OML, k={1, 2} • Improved fairness at cost of reduced throughput

Testbed: Chain Topology,Throughput-Fairness Trade Off • “Oracle”: global knowledge of interference; “perfect” scheduling • OML approaches optimal fairness with k=2, at some throughput cost • 802.11 appears to favor throughput over fairness

Wireless MACs (reprise): Overlay MAC