1. Ramakrishna Gummadi, Ramesh Govindan, Konstantinos Psounis
Interference-Aware Fair Rate Control in Wireless Sensor Networks (IFRC)
Sumit Rangwala
Ramakrishna Gummadi, Ramesh Govindan, Konstantinos Psounis

2. Problem Definition Wireless network of N nodes
Data transmission over multiple hops to a single node
“Design a distributed algorithm to dynamically allocate fair and efficient rate to each flow”
f20
f19
f15
f11
f13 10
Neighbor 11 12 13 14 15 16 17 18 19 20 21

3. Motivation: A Wireless Sensor Network for Collecting Structural Vibrations
Nodes measured vibrations and transmitted it to a central node
Over multiple hops
Preconfigured rates for each flow
Led to congestion
More than an hour to receive 10 min of vibration data in a 15 node network

4. Assumptions consistent with current practice in sensornets
CSMA MAC (without RTS/CTS)
Link-layer retransmissions
Routing Tree
One flow originating per node
f20
f19
f15
f11
f13 10
Neighbor 11 12 13 14 15 16 17 18 19 20 21
Assumptions consistent with current practice in sensornets

5. Challenges Goal Max-min allocation Wireless Networks
Transmission rate from a node to its neighbor depends on neighborhood traffic
Flows affecting this transmission rate are not merely flows traversing a node. fi fj A m n B
Flows that affect each others' rate may not traverse a common link or node

6. Challenges Transmission rate along 16 →14
Dependent on traffic on various other links
20 → 16 (a) , 21 → 16 (b), 14 → 12 (c)
17 →14, 13 →11, 12 →10
Transmission rate along 16 →14
Dependent on traffic on various other links
20 → 16 (a) , 21 → 16 (b), 14 → 12 (c)
17 →14 (d), 13 →11 (e), 12 →10 (f)
Transmission rate along 16 →14
Dependent on traffic on various other links
20 → 16, 21 → 16, 14 → 12
17 →14, 13 →11, 12 →10
Transmission rate along 16 →14
Dependent on traffic on various other links
20 → 16 (a) , 21 → 16 (b), 14 → 12 (c)
17 →14 (d), 13 →11 (e), 12 →10 (f) 10
Neighbor
Child/Parent f 11 12 e c 13 14 15 d
The rate of flows traversing 16 →14 (flows from 20, 21, and 16)
… is affected by rate of:
Flows originating from 17, 14, 13, 12,
As well as 15, 18, 19 16 17 18 19 a b 20 21

7. Definition: Potential Interferer
Interfering links
l1 interferes with a link l2 if transmission along l1 prevents
initiation of a transmission along l2 or
successful reception of a transmission along l2.
Potential interferer
Node n1 is a potential interferer of node n2 if
flow originating from node n1 uses a link that interferes with the link n2 → parent(n2). 10
Neighbor
Child/Parent f 11 12 e c 13 14 15 d
For CSMA and many-to-one traffic
potential interferer (ni) includes
neighbors of ni
neighbors of parent(ni)
Descendents of all the above nodes 16 17 18 19 a b 20 21

8. IFRC Design Congestion Detection Congestion Sharing Rate Adaptation
Based on avg. queue length
Congestion Sharing
To all the potential interferers
Rate Adaptation
AIMD
rlocal (rate of flow from this node)
Forwarding Traffic
Queue at each node
Packet transmitted until queue is empty (with retransmission)
IFRC adapts rate of flow originating at a node,
not the rate of flows traversing the node

9. Congestion Detection and Rate Adaptation
Based on queue length calculated as
qavg = wq * qinst + (1- wq) * qavg
Thresholding
Rate Adaptation
Every 1/rate sec (Additive Increase)
rate = rate + δ / rate
On local congestion (Multiplicative Decrease)
rate = rate/2

10. Congestion Sharing Each node piggybacks on every transmitted packet
Its own rate (rlocal) and its congestion state
Rate and congestion state of its most congested child

11. These rules are sufficient to signal all potential interferers
Congestion Sharing
Rule 1:
Local rate of a node should not be greater than that of its parent
(rlocal < rparent)
Rule 2:
For any congested neighbor or congested child of a neighbor
Local rate should not be greater than the rate of the congested node
(rlocal < rcongested node) 10
Neighbor
Child/Parent 11 12 13 14 15 16 17 18 19 20 21
These rules are sufficient to signal all potential interferers

12. Parameter Selection Additive Increase
δ = rate of increase
Analytically characterize δ to ensure stability
Queue Threshold
Network size and topology
Avg. depth of the tree

13. Evaluation on Sensor Testbed
Platform
Tmote Sky
TinyOS
Setup
40 node testbed
Network diameter = 8 hops
Static routing tree
Depth of the Tree = 9 hops
Link quality varied from 66% to 96%
Each experiment was conducted for an hour 3 5 1 4 8 6 7 14 10 11 12 13 9 18 20 21 16 15 24 17 26 22 25 27 28 30 31 23 32 36 34 29 35 33 39 37 38 41 40 42 2 19
4th Floor
Base Station

14. Topology
Base Station

15. Per Flow Goodput and Packet Reception
Average goodput as well as the instantaneous goodput is fair

16. Comparison with Optimal
IFRC achieves 80% of the optimal fair rate
IFRC achieves 60% of the optimal fair rate
IFRC achieves 60-80% of the optimal fair rate

17. Rate Adaptation and Instantaneous Queue Length
Max Buffer Size = 64
Not a single drop due to queue overflow

18. Weighted Fairness IFRC works without modification
Sending rate = weight* rlocal pkts/sec
w = 1
w = 2
w = 1
IFRC assigns rate proportional to node weight

19. Multiple Sink Two base stations rooted at 1 and 41 IFRC is efficient
Nodes get rates that are fair across trees
IFRC is efficient
Node 4,5 and 6 get greater (but equal) rates
Their flows don’t traverse the most congested region.

20. Conclusions Analysis of set of flows that share congestion at a node
Potential interferers
Design and implementation of low-overhead rate control mechanism
Analysis of IFRC’s steady-state behavior
Provide guidelines for parameters selection

21. Thank You For more Information Code
Code
Tinyos contrib
tinyos-1.x/contrib/usc-ifrc
ENL public CVS

22. Backup Slides

23. Definition: Fair and Efficient Allocation
fi flow originating from node i
Fi flows routed through node I
At each node i, define Ғi to be the union of Fi and all sets Fj
where j is either a neighbor of i, or a neighbor of i’s parent. These flows are flows from i’s potential interferers.
Allocate to each flow in Ғi a fair and efficient share of the nominal bandwidth B. Denote by fl,i the rate allocated at node i to flow l.
Repeat this calculation for each node.
Assign to fl the minimum of fl,i over all nodes i. 10
Neighbor
Child/Parent 11 12 13 14 15 16 17 18 19 20 21

24. Related Work Sensornets
Graceful, fair, degradation under load [Hull et al. (Fusion), Wan et al. (CODA)]
Centralized rate allocation [Sankarasubramaniam et al. (ESRT), Ee et al.]
AIMD-based rate adaptation without congestion sharing [Woo et al.]
Unlike prior work, we precisely identify the set of potential interferers
Wireless ad-hoc networks
Congestion sharing heuristics for any-to-any communication [Xu et al. (NRED)]
These heuristics don’t precisely identify the set of potential interferers

25. Congestion Detection Based on queue length calculated as EWMA
qavg = wq * qinst + (1- wq) * qavg
Multiple thresholds
Lower threshold L
Upper thresholds U(k) = U(k-1) + I/2k-1
U(0) = U
Local Congestion L U
U + I
U + 3I/2
Local Congestion

26. Rate Adaptation Slow start Slow start ends when
Starts with rate = rinit
Every 1/ rate sec
rate = rate + Φ
Slow start ends when
node itself get congested
constrained by other nodes to reduce its rate
Congestion sharing

27. Congestion Detection and Rate Adaptation
ri remains unchanged L U
every 1/ri sec
ri = ri+δ/ri
ri = ri /2
U + I
U + 3I/2
Rate adaptation with changing queue size

28. Base Station
Maintains rbase station, like rlocal of any other node, to share congestion across nodes
Follows the same algorithm for rate adaptation with one exception
Decreases rbase station only when a child of base station is congested.
It does not decreases its rate when any other neighbor is congested or any child of a neighbor is congested.

29. Parameter Selection (Steady State)
Additive increase
Constraint on ε
U0 and U1 based on [Floyd et al.]
Rule of thumb for Fj
(n = size of network)

30. Evaluation (Tree)

31. Parameters Used

32. Comparison with Optimal
Max Queue Length
IFRC achieves 60-80% of the optimal fair rate

33. Node Addition
Nodes join

34. Node Deletion
Nodes leave

35. IFRC (No Link Layer Retransmissions)

36. Subset of node Special case of weighted fairness
nodes with no data to send ≡ weight = 0

37. Multiple Sink (Trees)
Base Stations