Wireless MACs (reprise): Overlay MAC

Brad KarpUCL Computer Science

CS 4C38 / Z2524th January, 2006

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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

Many competing schemes for MACs, even slotted ones!This paper: measure underlying problem; build real implementation; evaluate it.

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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

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802.11a Testbed

• Indoor, chain topology

• No other 802.11 traffic in band

• UDP broadcast packets

• TCP

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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

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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%

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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

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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 N5 N6

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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

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Assumptions

• Unicast and broadcast transmission supported

• Promiscuous mode listening• RTS/CTS configurable “off”• Limit transmit queue to 1-2 packets

– Why?

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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

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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

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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

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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:

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• 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 2:Diameter One, Arbitrary Weights

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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

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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

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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

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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

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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

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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

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Simulation: Average Throughput

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

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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

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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

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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

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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

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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