Adaptive Split Transmission for
Video Streams in Wireless Mesh
Networks
指導教授：許子衡 老師
學生：王志嘉
Introduction (i)
The interest of wireless mesh networks (WMNs) has
been greatly spurred by a number of potential
commercial applications.
In this paper, we study video transmission in WMNs.
A WMN replaces access points in WLAN and WiFi
and base stations in cellular networks with
inexpensive mesh routers that have minimal mobility
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Introduction (ii)
Video applications, such as online games, wireless
video conferences ,real-time monitoring of activities
at homes and in offices, and online exchange, generate
high rate traffic and have stringent requirement for
short delay and small delay jitter performance.
Layered transmission adapts to congestion through
encoding a video flow onto multiple layers and
deciding to transmit a layer suiting to link capacity.
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Introduction (iii)
This paper addresses the problem of qualityguaranteed video transmission when a basic layer
transmission causes channel overload.
We present a new WMN traffic control algorithm, the
adaptive split transmission algorithm, that fully
utilizes unused capacities in the WMN system to
transmit a basic layer video when the basic layer
transmission is not suitable for any single channel.
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Introduction (iv)
The adaptive split transmission algorithm holds the
following characters.




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Pro-activity
Adaptively
Efficiency
Deploy ability
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Adaptive Split Transmission&Network
model
Adaptive split transmission algorithm is presented for
quality guaranteed video when a basic layer
transmission causes overload.
We use an undirected graph G = (V (R),E) to represent
a wireless network, where V (R) is a set of nodes, R is
a set of radio interfaces used by wireless mesh nodes,
and E is a set of wireless links
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Network Model (ii)
Without loss of generality, we denote any node in the
wireless mesh as v (r), where v (r) ∈ V (R) and r ∈ R.
Fig. 1 to illustrate the assignment of control channels
in the wireless system. When the node 0 selects the
channel N − 2 as its control channel, its neighbor (i.e.,
the node 1) will select the other channel (i.e., the
channel N −1) as its control channel.
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Fig. 1. An example of assigning listening
channels
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Overload Detection (i)
One of the key problems of the adaptive split
transmission algorithm is to detect a coming overload
to conduct effective traffic control.
Overload detection adopts a pro-active way to detect
overload for effective traffic control.
Suppose there are F (F ∈ N) flows that v (r) needs to
send/forward through a data channel n (n ∈ [0,N − 3]).
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Overload Detection (ii)
flows’ incoming rates
channel n’s instantaneous available capacity
rj is the jth flow’s incoming rate
queue length
t is the time at which the new flow f inputs
We use 0+ to represent the time at which at least one
of the F flows begins occupying channel n. If Cn ≥ rf ,
v (r) thinks that channel n is able to carry f; otherwise,
if Cn < rf , v(r) employs the adaptive split
transmission algorithm to release overload.
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Overload Detection (iii)
Overload detection observes each channel’s status
instead of bottleneck in a multi-hop path. It holds the
advantage of fully utilizing each channel’s capacity.
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Adaptive Split Transmission (i)
When v (r) detects that channel n is going to carry
heavy traffic, it adopts the adaptive split transmission
algorithm to avoid a coming overload.
The basic idea of the adaptive split transmission
algorithm is to aggregate the unused capacities of the
data channels to transmit f.
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Adaptive Split Transmission (ii)
It can be seen that selecting channels is a key step for
the algorithm .To evaluate channel quality, we define a
measurement η.
Cˆ (i) is the ith channel’s unused capacity
A(i) is the availability of the ith channel.
In the algorithm, channels with larger η value have the
priority to be selected as transmission channels.
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Adaptive Split Transmission (iii)
We now present the channel capacity collection and
the channel availability detection to achieve these
two goals.
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Channel Capacity Collection (i)
Channel capacity collection is proposed to achieve Cˆ
(i). v(r) classifies the data channels into two groups:
occupied channels and unoccupied channels.
For the occupied channels, the same way as overload
detection does is employed to calculates unused
capacities. v (r) maintains a employed queue for each
occupied channel, and calculates the unused capacity
of each occupied channel by the following equation.
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Channel Capacity Collection (ii)
F is the number of flows currently sent/forwarded by v(r) through the ith
channel.
l (i, t) is the length of the queue for the ith
channel at the time t
rj is the j th flow’s incoming rate
t is the time at which v(r) collects capacities
The information exchanged includes not only the
mesh node’s unused capacities in its occupied
channels but also the unoccupied channels’ unused
capacities that the mesh node knows
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Channel Capacity Collection (iii)
The information exchanged includes not only the
mesh node’s unused capacities in its occupied
channels but also the unoccupied channels’ unused
capacities that the mesh node knows
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Channel Availability Detection
The channel availability detection is designed to
avoid confliction when using the unoccupied
channels to transmit data.
When v (r) detects a coming overload, it checks the
availability of its unoccupied channels with its
neighboring nodes. More specifically, through the
control channel, v (r) sends CONFLICTION
DETECTION to its neighboring nodes.
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Algorithm Description (i)
To decrease the number of channels that v (r) will
occupy, the adaptive split transmission algorithm
assigns the minimum number of channels that has an
enough aggregative unused capacities to v (r).
The channel number, m ≥ r, in the selected
transmission channel set is calculated by
t is the time at which v(r) collects unused capacities
rf is the basic layer transmission rate of the flow f.
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Algorithm Description (ii)
After deciding m transmission channels, v (r) splits the
basic layer video into m sub-flows. We use the
following equation to calculate the size of the jth subflow Sj (j ∈ [0,m − 1]).
H is the header added to each sub-flow to show the information of the sender
Cˆj is the unused capacity of the jth channel in the selected transmission channel set
Sf is the total amount of video packets queueing at v(r)
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Algorithm Description (iii)
An example of the adaptive split transmission
algorithm. m channels are selected by v(r) to transmit
f’s sub-flows in parallel. Channels 0 ∼ r − 2 are v(r)’s
occupied channels. Channel r − 1 has the largest η
value and channel (m − 1) has the smallest η value
among other m − r + 1 channels.
Fig. 2 illustrate such split transmission. Channels
illustrated in the figure are the m selected channels.
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Fig.2
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Adaptive Split Transmission Algorithm
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Adaptive Split Transmission Algorithm
(續)
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Simulation Evaluation
We use a set of simulations run in ns-2 to evaluate
video transmission performance with and without the
adaptive split transmission algorithm.
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Simulation Metrics (i)
Average packet delay (APD). Average packet delay at
the jth receiver is calculated by
，pj is the
number of received packets, and di is the delay of the
ith packet.
APD for all receivers is calculated by
n is the number of receivers in the network. APD
shows whether most of the receivers are satisfied with
the delay performances or not.
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Simulation Metrics (ii)
Improved quality (IQ). The best video quality that the
network transmission can guarantee is measured by
the maximum video rate without incurring overloaded
channels and unacceptable delays. IQ is calculated by
and Q are the best video qualities with and without
the adaptive split transmission algorithm respectively.
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Simulation Metrics (iii)
Average delay jitter (ADJ). Delay jitter is the delay
variance between consecutive packets which is
calculated by Jj,i =|Dj,(i+1)−Dj,i|
Dj,(i+1) and Dj,i are the delays of the (i + 1)th and the ith
packets at the jth receiver, and Jj,i is the ith delay jitter
at the jth receiver.
The average delay jitter at the jth receiver is ADJj =
pj is the number of packets received by the jth receiver
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Simulation Metrics (iv)
Average delay jitter ADJ in the network is
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Simulation I: Single Receiver (i)
Fig. 3 shows the network topology. The wireless
network includes 2 mobile nodes (s and r). s is the
traffic sender and r is the traffic receiver.
Wireless communication adopts 802.11 protocol.
Channel bandwidth is set as 2Mb.
Video transmission rate is set as 128Kbit/s. In the
simulation, we import disturbance traffic to generate
network load.
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Fig. 3. Network topology for the single
receiver simulation
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Simulation I: Single Receiver (ii)
Fig. 4 gives the average packet delay curves. In this
figure, each point is an average value of 20 runs of the
simulation. The curves illustrate that the adaptive split
transmission algorithm decreases packet transmission
delay greatly when network traffic load becomes
larger than 600Kbit/s.
We use
to evaluate the degree of delay
decrement, where
and ATD are average packet
delays with and without the adaptive split
transmission algorithm.
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Fig. 4. Performance of average packet delays
in the single receiver network shown in Fig. 3.
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Simulation I: Single Receiver (iii)
The first line in Table I gives the comparison of the
highest video qualities (represented by data rate) that
guarantee acceptable delays in the single receiver
WMN. The adaptive split transmission algorithm
aggregates capacities of multiple non-interfering
channels to guarantee higher quality video
transmission. According to the results, IQ in this
simulation is 2.4.
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TABLE I
Comparison of The Highest Video Quality
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Simulation I: Single Receiver (iv)
Fig. 5 illustrates the average delay jitter performance
in this simulation.
ADJ increases with the increasing of network traffic
load. Traffic controlled by the adaptive split
transmission algorithm suffers from a bit larger ADJ
when network traffic load becomes heavy (heavier
than 950Kbit/s in our simulation).
It show that the delay jitter generated by the adaptive
split transmission algorithm is low enough to
guarantee continuous and synchronizing reception.
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Simulation II: Multiple Receivers (i)
Fig. 6 shows the network topology. In the wireless
mesh network, there are 25 nodes who have an
identical set of six radio interfaces.
Node 0 is the sender, and nodes 8, 11, 12, and 24 are
receivers who are randomly selected by the program.
Node 0 sends one video flow with the rate of
128Kbit/s to each receiver as shown by the arrowed
lines in the figure.
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Fig. 6
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Simulation II: Multiple Receivers (ii)
Fig. 7 gives the average packet delay curves in the
simulation. Each point in the curves is an average
value of 20 runs of the simulation. The figure shows
that the adaptive split transmission algorithm
achieves stable variance in the average packet delay,
and also it decreases packet transmission delays
greatly when network traffic load becomes heavy
(heavier than 144Kbit/s in the simulation).
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Fig. 7. Performance of average packet delays
in the single receiver network.
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Simulation II: Multiple Receivers (iii)
The second line in Table I shows the comparison of
the highest video qualities (represented by data rate)
that guarantee acceptable delay transmission in the
multiple receiver WMN. IQ in this simulation is 4.67.
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TABLE I
Comparison of The Highest Video Quality
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Simulation II: Multiple Receivers (iv)
Fig. 8 illustrates the average delay jitter performance
in the multiple receiver network.
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Conclusion
We studied a novel and simple algorithm, the adaptive
split transmission algorithm, to distribute real-time
and quality-guaranteed video flows in wireless mesh
networks.
The algorithm is a complimentary traffic control
scheme for the layered transmission.
The algorithm has no requirement for underlying
network architecture and can be easily developed on
top of current wireless hardware and MAC protocols.
We believe that the algorithm is useful for wireless
interactive real-time video applications
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