Multi-Channel Protocols
for Wireless Mesh
Networks
Yu-Chee Tseng
CS/NCTU
1
Outline
Introduction to MANET
 Review of 3 Multi-channel Protocols
 Summary

2
Wireless Mesh Network
3
Observation: Multi-channel MANET

IEEE 802.11 provides several nonoverlapping channels which could be used
simultaneously within a neighborhood.
Ex: (Assume Channel Capacity = 100Mbps)
Can simultaneously operate
Interference
A
A
44 /50
Ch1
Expected
Load
C
B
43/ 50
Ch1
Goodput = 87Mbps
Single-Channel
81/100
B
Ch1
Link Capacity
=100/2
C
84/100
Ch2
Goodput = 165Mbps
Multi-Channel
4
Motivation
The idea of exploiting multiple channels
is appealing in wireless mesh networks
because of their high capacity
requirements to support backbone traffic.
 However, the channel assignment problem
is NP-hard.

5
A Multi-channel Example
6
Problem Spectrum

number of interfaces per node
 single interface
 fixed at a particular channel (traditional solution)
 may switch among different channels
 multiple interfaces
 each fixed at a particular channel
 may switch among different channels

channel assignment algorithm
 Centralized
 assignment is done in longer period
 Distributed
 assignment can be done is shorter period
 more flexible and dynamic, depending on current loads
7
Review 1:
A Centralized Greedy
Solution

Ashish Raniwala, Kartik Gopalan, and Tzicker Chiueh, “Centralized Channel
Assignment and Routing Algorithms for MultiChannel Wireless Mesh Networks,” Mobile
Computing and Communications Review, vol.
8, no. 2, pp. 50–65, April 2004.
8
Problem Statement

Input: expected load on each link

Output: assignment of channels to network
interfaces

Goal: to reduce interference between
neighboring interfaces
9
An Example



Number of channels: 4 (1,2,3,4)
Number of interface per node:
2
Per Channel Capacity: 100
units
Internet
B
30
A

Definition: degree of
interference

C
40
G
50
15
D
The sum of expected load that
a link may experience on a
particular channel in its
interference region.
20
E
25
F
expected load
on this link
10
Example of Degree of Interference
Degree of Interference for link E-F
on different channels
Internet
Ch1
50+25=75
Ch2
25+20+15=60
B
Ch3
25
Ch4
25
30
Ch3
C 15
A
40
Ch1
link E-F will only experience
interferences from links
D-E, C-D, and D-G,
but not from
links B-C, A-C
coverage
of node F
G
Ch2 D
E
50
Ch1
20
Ch2
25
F Ch1
coverage
of node E
11
Outline of the Algorithm
Links are sorted, and then visited in the
decreasing order of their link loads.
 A greedy approach:

 When
a link is visited, it is assigned to a
channel with the lowest degree of interference.
 Special cases:


If the interfaces of the incident nodes are all used out, we
may need to change one interface to a used channel.
If the interfaces of the incident nodes are all used out but
they have a common channel, then assign the link to the
common channel.
12
A Running Example




Number of channels: 4 (1,2,3,4)
Number of interface per node:
2
Per Channel Capacity: 100
units
Internet
B
30
A
C
40
First:
sort links according to their link
loads (in a decreasing order)
G
50
15
D
20
E
25
D-G
A-C
B-C
E-F
D-E
C-D
50
40
30
25
20
15
F
13
Connect (D,G)
Channel List
D-G
A-C
B-C
E-F
D-E
C-D
50
40
30
25
20
15
Degree of Interference
A
Ch1 050
B
Ch2 0
C
Ch3 0
D
1
Internet
B
A
G
Ch4 0
C
E
D
50
Ch1
F
G 1
E
F
14
Connect (A,C)
Channel List
A
2
B
D-G
A-C
B-C
E-F
D-E
C-D
50
40
30
25
20
15
Degree of Interference
Internet
Ch1 50
B
Ch2 040
C
2
Ch3 0
D
1
Ch4 0
E
A
G
40 C
Ch2
D
50
Ch1
F
G 1
E
F
15
Connect (B,C)
Channel List
D-G
A-C
B-C
E-F
D-E
C-D
50
40
30
25
20
15
Degree of Interference
Internet
A
2
Ch1 50
B
3
Ch2 40
B
C
2,3
Ch3 030
D
1
Ch4 0
30
Ch3
C
E
A
40
Ch2
G
D
50
Ch1
F
G 1
E
F
16
Connect (E,F)
Channel List
D-G
A-C
B-C
E-F
D-E
C-D
50
40
30
25
20
15
Degree of Interference
Internet
A
2
Ch1 50
B
3
Ch2 0
B
C
2,3
Ch3 025
D
1
Ch4 0
30
Ch3
C
E
3
F
3
A
40
Ch2
G 1
G
D
50
Ch1
E
25
F Ch3
17
Connect (D,E)
Channel List
D-G
A-C
B-C
E-F
D-E
C-D
50
40
30
25
20
15
Degree of Interference
Internet
A
2
Ch1 50
B
3
Ch2 40
B
C
2,3
Ch3 30+25
D
1,4
Ch4 020
30
Ch3
C
E
3,4
F
3
A
40
Ch2
G 1
G
D
E
50
Ch1
20
Ch4
25
F Ch3
18
Connect (C,D)
Channel List
D-G
A-C
B-C
E-F
D-E
C-D
50
40
30
25
20
15
Degree of Interference
A
2
Ch1 50
B
3
Ch2 40
C
2,3
Ch3 55
B
D
1,4
Ch4 20
E
3,4
F
3
30
Ch3
C 15
G 1
Internet
A
40
Ch2
Switch from ch. to ch.
E
interference of new ch.
12 13 21 24 31 34 42 43
90
105 90
??
60
80
50
60
G
D
50
Ch1
20
Ch4
25
F Ch3
75
Explanation next page19
Connect (C,D)
Channel List
D-G
A-C
B-C
E-F
D-E
C-D
50
40
30
25
20
15
Degree of Interference
Internet
A
2
Ch1 50
B
4
Ch2 40
C
2,4
Ch3 5525
D
1,4
Ch4 2050
E
3,4
F
3
B
A
switch ch 3 to ch 4
(不含本身的15)
G 1
E
12 13 21 24 31 34 42 43
90
105 90
30
G
Ch3Ch4
50
40 C 15
Ch1
Ch2
?? D
60
80
50
60
20
Ch4
25
F Ch3
75
20
Connect (C,D)
Channel List
D-G
A-C
B-C
E-F
D-E
C-D
50
40
30
25
20
15
Degree of Interference
Internet
A
2
Ch1 50
B
4
Ch2 40
B
C
2,4
Ch3 25
D
1,4
Ch4 5065
30
Ch4
C 15
E
3,4
F
3
A
40
Ch2
Ch4 D
G 1
E
12 13 21 24 31 34 42 43
90
105 90
60
80
50
60
G
50
Ch1
20
Ch4
25
F Ch3
75
21
select the one with min. int.
Final Result
Channel List
A
2
B
4
C
2,4
D
1,4
E
3,4
F
3
G 1
Internet
B
A
40
Ch2
30
Ch4
C 15
G
Ch4 D
E
50
Ch1
20
Ch4
25
F Ch3
22
A Short Summary


Adv.: quite simple
Disadv.
need initial expected load on every link
2. centralized algorithm (must know network
topology)
3. static network topology
4. static traffic load
1.
23
Review 2: (SSCH)
A distributed, single-interface
solution

Paramvir Bahl, Ranveer Chandra, and John
Dunagan, “SSCH: Slotted Seeded Channel
Hopping for Capacity Improvement in IEEE
802.11 Ad-Hoc Wireless Networks,” in ACM
Mobicom, 2004.
24
Protocol Outline: SSCH

Single interface hopping on multiple channels.



time is slotted
SSCH (Slotted Seeded Channel Hopping)
1. Each node has its own channel hopping schedule.
2. Each node transmits its schedule to neighboring
nodes in the beginning of each slot.
3. To transmit data, a node has to change its hopping
schedule to adapt to receiver’s hopping patterns.
The seeded hopping ensures through number theory
that every pair of nodes have a common channel to
exchange their schedulers.
25
原理1: Channel Hopping Scheduling

Time is slotted.
 Continuous slots are framed together.
 The i-th slots of all frame form the i-th virtual

channel.
Each virtual channel is represented by a
(channel, seed) pair, denoted by (xi , ai ).
 xi
= current channel;
 ai=hopping distance
 hopping rule: xi ← (xi + ai) mod 3

Also, there is a special slot called “parity slot”.
a
common channel must be used.
26
Channel Schedule Example
1
0
2
(channel,seed) 1
(channel,seed) 2
(mod 3)
(channel,seed) 1
(channel,seed) 2
(mod 3)
27
Mathematical Properties

For two nodes with an identical seed
 if they have identical channel:

 if
they have different channels:


these two nodes are always synchronized.
they only overlap in the parity slots
For two nodes with different seeds
 they overlap exactly once every 3 slots

prime number theory
 These overlapping slots ensure that stations can exchange
schedulers.
28
原理2: Optimistic Synchronization

If node A has packets to be sent to node B,
A will select a virtual channel and match it
with B’s corresponding virtual channel.
 receiver-based
rule
(channel-A,seed-A)
 (channel-B,seed-B)
A
(channel-B, seed-B)
B
29
原理3: Partial Synchronization

For a multi-hop path, partial
synchronization is used.
 Node
B follows node C’s hopping schedule in
some virtual channels, and leave some virtual
channels to be synchronized by node A.
 goal: better spatial reuse
B
A
C
30
A Naive Synchronization
31
Solution (現有AB,加入BC)
Receiving ch.: If a slot always receives data,
it is marked as receiving slot.
Case 1:
B preserves its receiving ch.
and uses its idle virtual ch.
B
to sync. with C
4 (channel,seed)
(x1,a1)
(x2,a2)
(x3,a3)
(x4,a4)
Case 2:
all slots are
receiving,
partial sync.
A
B
C
B
A
C
A
B
C
A
C
32
原理4: De-synchronization

To reduce interference, if too many nodes use the same
(channel, seed) is the same virtual channel, desynchronize some of them.

simply choose a new (channel, seed) at a node’s own decision
may choose to
de-sync.
Example:
3 pairs use the same
(channel, seed) in
the 2nd virtual channel
(0,3)
(0,1)
(2,1)
(1,2)
(0,1)
(0,2)
(1,0)
(0,1)
(1,3)
(2,2)
(0,1)
(1,1)
(1,4)
(0,1)
(3,1)
(0,2)
(0,1)
(2,3)
33
Short Summary

Adv.
1.
2.

an interesting partial synchronization technique
an interesting de-synchronization technique
Disadv.
1.
2.
need global time synchronization
only designed for one interface
34
Review 3: (MCR)
A multi-interface channel
assignment protocol

Pradeep Kyasanur and Nitin H.
Vaidya, "Routing and Interface
Assignment in Multi-Channel MultiInterface Wireless
Networks", WCNC 2005.
35
Main Idea

Each node has multiple interfaces.
 Fixed
Interface: assigned to some fixed channel for
long intervals of time
 Switchable Interface: dynamically assigned to
channels over short time scales

Transmission Rules:
 receiver-based
a
sender adapts to a receiver by changing its
switchable interface to the receiver’s fixed interface
36
Example

2 interfaces per node
1
fixed, 1 switchable
3 channels are available.
Routing Path: ABC

Fixed = 1
Fixed = 2
Fixed = 3
A
B
C
Initially:
switchable = 3
Step 1:
switchable = 2
Step 2:
switchable = 1
switchable = 3
switchable = 2
37
Fixed Interface assignment

Goal:


to ensure that fixed interfaces of nodes in a
neighborhood have better spatial reuse.
A localized protocol, where each node
maintains two tables:


NeighborTable: containing the fixed channels
being used by its neighbors
ChannelUsageList (CUL): keeping the number
of nodes using each channel by their fixed
channels
38
Distributed Algorithm
1. Initially, each node chooses a random channel as its
fixed interface.
Example: All nodes are neighbors (3 channels)
CUL
1
B
3
1
A
1
B
Fixed=1
2
CUL
CUL
A
Fixed=1
D
Fixed=1
C
Fixed=1
CUL
2
1
3
2
3
C
D
2
3
E
Fixed=1
CUL
1
E
2
3
39
Distributed Algorithm
2. Periodically, each node broadcasts on every
channel its current fixed channel.
Example:
“Hello”
CUL
1
B
1
B
Fixed=1
2
3
“Hello”
CUL
1
A
CUL
A
Fixed=1
D
Fixed=1
2
3
C “Hello”
E
Fixed=1
Fixed=1
CUL
2
1
3
2
3
C
D
CUL
1
E
2
3
40
Distributed Algorithm
3. On receiving a hello packet, a node updates its
NeighborTable and ChannelUsageList.
Example:
CUL
1
ABCDE
3
1
ABCDE
1
B
Fixed=1
2
CUL
CUL
A
Fixed=1
D
Fixed=1
C
Fixed=1
CUL
2
1
3
2
3
ABCDE
ABCDE
2
3
E
Fixed=1
CUL
1
ABCDE
2
3
41
Distributed Algorithm
4. Each node periodically consults its CUL (relatively long period). If its
fixed channel is detected to be too crowded, it has a probability p to
change its fixed channel to a less crowded channel.
Example:
CUL
1
ABCDE
3
1
ABCDE
1
B
Fixed=1
2
CUL
CUL
A
Fixed=1
D
Fixed=1
C
Fixed=1
CUL
2
1
3
2
3
ABCDE
ABCDE
2
3
E
Fixed=1
CUL
1
ABCDE
2
3
42
Distributed Algorithm
4. Each node periodically consults its CUL (relatively long period). If its
fixed channel is detected to be too crowded, it has a probability p to
change its fixed channel to a less crowded channel.
Example: C decides to change to channel 2
CUL
1
ABCDE
3
1
ABCDE
1
B
Fixed=1
2
CUL
CUL
A
Fixed=1
D
Fixed=1
ABCDE
2
3
C Change
E
Fixed=1
Fixed=1
CUL
2
1
3
2
3
ABCDE
CUL
1
ABCDE
2
3
43
Distributed Algorithm
4. Each node periodically consults its CUL (relatively long period). If its
fixed channel is detected to be too crowded, it has a probability p to
change its fixed channel to a less crowded channel.
Example: C broadcasts to neighbor
CUL
1
CUL
ABCDE
1
B “Hello” D
Fixed=1
Fixed=1
2
3
“Hello”
CUL
1
ABCDE
A
Fixed=1
ABCDE
2
3
C
“Hello”
E
Fixed=2
Fixed=1
CUL
CUL
1
2
1
ABDE
2
3
2
C
3
3
ABCDE
44
Distributed Algorithm
4. Each node periodically consults its CUL (relatively long period). If its
fixed channel is detected to be too crowded, it has a probability p to
change its fixed channel to a less crowded channel.
Example: after broadcast
CUL
1
ABDE
2
C
3
CUL
1
ABDE
2
C
3
A
Fixed=1
CUL
B
Fixed=1
D
Fixed=1
C
Fixed=2
CUL
1
ABDE
2
C
3
E
Fixed=1
CUL
1
ABDE
C
1
ABDE
2
2
C
3
3
45
Distributed Algorithm
4. Each node periodically consults its CUL (relatively long period). If its
fixed channel is detected to be too crowded, it has a probability p to
change its fixed channel to a less crowded channel.
Example: E checks its CUL, but does not change
CUL
1
ABDE
2
C
3
CUL
1
ABDE
2
C
3
A
Fixed=1
CUL
B
Fixed=1
D
Fixed=1
C
Fixed=2
CUL
1
ABDE
2
C
3
1
ABDE
2
C
3
E
Fixed=1
Nothing
CUL
1
ABDE
2
C
3
46
Distributed Algorithm
4. Each node periodically consults its CUL (relatively long period). If its
fixed channel is detected to be too crowded, it has a probability p to
change its fixed channel to a less crowded channel.
Example: D changes to channel 1
CUL
1
ABDE
2
C
3
CUL
1
ABDE
2
C
3
A
Fixed=1
Change
B
Fixed=1
D
Fixed=1
C
Fixed=2
CUL
CUL
1
ABDE
2
C
3
E
Fixed=1
CUL
1
ABDE
C
1
ABDE
2
2
C
3
3
47
Distributed Algorithm
4. Each node periodically consults its CUL (relatively long period). If its
fixed channel is detected to be too crowded, it has a probability p to
change its fixed channel to a less crowded channel.
Example: D broadcasts
CUL
1
ABDE
2
C
3
CUL
1
ABDE
2
C
3
A
Fixed=1
CUL
“Hello”
B
Fixed=1
D
Fixed=3
1
ABE
2
C
3
D
C “Hello”
E
Fixed=2
Fixed=1
CUL
CUL
1
ABDE
C
1
ABDE
2
2
C
3
3
48
Distributed Algorithm
4. Each node periodically consults its CUL (relatively long period). If its
fixed channel is detected to be too crowded, it has a probability p to
change its fixed channel to a less crowded channel.
Example: after D’s broadcast
CUL
1
ABE
2
C
3
D
CUL
A
Fixed=1
CUL
B
Fixed=1
D
Fixed=3
C
Fixed=2
CUL
1
ABE
2
C
3
D
E
Fixed=1
CUL
1
ABE
ABE
2
C
2
C
3
D
3
D
1
ABE
2
C
1
3
D
49
Distributed Algorithm
4. Each node periodically consults its CUL (relatively long period). If its
fixed channel is detected to be too crowded, it has a probability p to
change its fixed channel to a less crowded channel.
Example: B changes to channel 2
CUL
1
ABE
2
C
3
D
CUL
A
Fixed=1
CUL
Change
B
Fixed=1
D
Fixed=3
C
Fixed=2
CUL
1
ABE
2
C
3
D
E
Fixed=1
CUL
1
ABE
ABE
2
C
2
C
3
D
3
D
1
ABE
2
C
1
3
D
50
Distributed Algorithm
4. Each node periodically consults its CUL (relatively long period). If its
fixed channel is detected to be too crowded, it has a probability p to
change its fixed channel to a less crowded channel.
Example: B’s broadcast
CUL
1
AE
2
CB
3
D
CUL
“Hello”
B
Fixed=2
“Hello”
CUL
A
Fixed=1
D
Fixed=3
C
Fixed=2
CUL
1
ABE
2
C
3
D
E
Fixed=1
CUL
1
ABE
ABE
2
C
2
C
3
D
3
D
1
ABE
2
C
1
3
D
51
Distributed Algorithm
4. Each node periodically consults its CUL (relatively long period). If its
fixed channel is detected to be too crowded, it has a probability p to
change its fixed channel to a less crowded channel.
Example: after B’s broadcast
CUL
CUL
1
AE
2
CB
3
D
A
Fixed=1
CUL
B
Fixed=2
D
Fixed=3
C
Fixed=2
CUL
1
AE
2
CB
3
D
E
Fixed=1
CUL
1
AE
AE
2
CB
2
CB
3
D
3
D
1
AE
2
CB
1
3
D
52
Distributed Algorithm
Threshold to determinate whenever a
channel is too crowded:
neighbors
channels
No more change!
CUL
CUL
1
AE
2
CB
3
D
A
Fixed=1
CUL
B
Fixed=2
D
Fixed=3
C
Fixed=2
CUL
1
AE
2
CB
3
D
E
Fixed=1
CUL
1
AE
AE
2
CB
2
CB
3
D
3
D
1
AE
2
CB
1
3
D
53
Scheduling Rules for Interfaces


Each node maintains a
separate queue for each
channel.
When a packet arrives,


Fixed
2
Switchable
3
N
Fixed=1
The use of each switchable
channel is bounded by two
parameters BurstLengh and
MaxSwitchTime.

1
…

if the sender has the same fixed
channel as the receiver, enqueue
to the fixed channel.
otherwise, enqueue to the
switchable channel.
Queue
For broadcast, add a packet to
each queue.
D1
Fixed=3
D2
S
D3
Fixed=N
54
Summary

Adv.:


a simple rule to use multiple interfaces and
multiple channels
Disadv.

If a node always receives but doesn’t send,
the fixed interface may be overloaded while
the switchable interface is always idle.
55
Review 4:
A multi-interface routing
protocol

Richard Draves, Jitendra Padhye,
and Brian Zill, “Routing in MultiRadio, Multi-Hop Wireless Mesh
Networks,” in ACM Mobicom, 2004.
56
Route Selection Metric
Which is the best routing path?
10ms
A
B
10ms
S
40ms
30ms
less delay, but
using one channel?
10ms
D
C
10ms
10ms
10ms
E
Ch2
longer delay,
but shortest?
F
using multiple
channel? 57
How to Select a Good Path

A good routing protocol should take the loss rate,
the bandwidth of a link, and channel diversity
into account.
 For
a multi-channel MANET, the path metric should
explicitly account for the interference among links that
operate on the same channel.

Multi-Radio Link-Quality Source Routing
a
combination of the LQSR protocol with a new metric
that we call WCETT (Weighted Cumulative Expected
Transmission Time).
58
Original WCETT

Sum of expected time to successfully transmit a packet
on the route
n
WCETTorg   ETTi
i 1
Note:值愈小愈好
Example:
20ms
15ms
5ms
10ms
5ms
WCETT=10+15+5+5+20=55
59
WCETT by Channel Diversity

Xj: sum of transmission times of hops on
channel j
Xj =Hop i
Σ
ETT
i
is on channel j
WCETTch  diversity  max1 j  k X j
Example:
20ms
Ch2
15ms
Ch2
10ms
Ch1
5ms
Ch3
5ms
Ch1
10ms
Ch2
1≦j≦k
X1 = 10+5 = 15
X2 = 15+20+10 = 45
X3 = 5
WCETT = max(X1,X2,X3)
= max(15,45,5)
=45
60
Proposed: Combined WCETT
WCETT  (1   )  WCETTorg    WCETTch diversity
Example:
1:
2:
3:
4:
S
S
S
S
ETT=10
ETT=5
ETT=12
ETT=10
ETT=5
ETT=12
ETT=6
ETT=9
ETT=7
ETT=11
ETT=7
ETT=2
ETT=2
ETT=2
ETT=2
Ch1
D
Ch2
D
D
D
Path
Sum
Max
WCETT (β=0.9)
WCETT (β=0.1)
1
27
22
22.5
26.5
2
33
22
23.1
31.9
3
34
20
21.4
32.6
4
8
8
8
8
61
Conclusions

Layer 2: Channel Assignment
a
centralized greedy Algorithm
 a distributed single-interface protocol


a
distributed multi-interface protocol



hopping + seed
receiver-based channel switch
fixed and switchable interfaces
using switchable to adapt to fixed channel
Layer 3: Multi-Channel Routing
a
new metric WCETT with channel diversity
62
References
1.
2.
3.
4.
5.
Ashish Raniwala, Kartik Gopalan, and Tzi-cker Chiueh, “Centralized
Channel Assignment and Routing Algorithms for Multi-Channel Wireless
Mesh Networks,” Mobile Computing and Communications Review, vol. 8,
no. 2, pp. 50–65, April 2004.
Paramvir Bahl, Ranveer Chandra, and John Dunagan, “SSCH: Slotted
Seeded Channel Hopping for Capacity Improvement in IEEE 802.11 AdHoc Wireless Networks,” in ACM Mobicom, 2004.
Pradeep Kyasanur and Nitin H. Vaidya, "Routing and Interface
Assignment in Multi-Channel Multi-Interface Wireless
Networks", Technical Report, October 2004 (A version will appear in
WCNC 2005)
Richard Draves, Jitendra Padhye, and Brian Zill, “Routing in Multi- Radio,
Multi-Hop Wireless Mesh Networks,” in ACM Mobicom, 2004.
Shih-Lin Wu, Chih-Yu Lin, Yu-Chee Tseng, and Jang-Ping Sheu, “A New
Multi-Channel MAC Protocol with On-Demand Channel Assignment for
Multi-Hop Mobile Ad Hoc Networks,” in International Symposium on
Parallel Architectures, Algorithms and Networks (ISPAN), 2000.
63