1. Congestion Detection for Video Traffic in Wireless
Sensor Networks
Hemmat Sheikhi Mousa Dashti Mehdi Dehghan
Dept. of Computer Eng., Amirkabir Dept. of Computer Eng., Amirkabir Dept. of Computer Eng., Amirkabir
University of Technology University of Technology University of Technology
Tehran, Iran Tehran, Iran Tehran, Iran
hemat.sheikhi@aut.ac.ir dashtimehran@aut.ac.ir dehghan@aut.ac.ir
Abstract— Congestion control mechanisms include three phases: retransmitted packet burdening excessive delay may be
congestion detection, congestion notification and rate adjustment. unacceptable. So it is obvious in WMSNs that achieving
So far diverse congestion detection methods for sensor networks reliability by congestion control approach is of great priority.
are proposed. In this paper we introduce numerous congestion
detection parameters and examine them in various respects; Among multimedia applications those that have video
finally we choose one of them as the best parameter for video traffic due to high amount of data rate and also because of
traffic in wireless sensor networks. Some of intended criteria for burst nature are more in congestion danger (Typically
comparing the parameters are cost, relation to quality of video, transmission rate in sensor networks is 40 kbps but audio
locality or being global in the network, accuracy and speed of traffic rate in constant data rate is 64 kbps and burst of video
congestion detection. We simulated and concluded that average traffic is about 500 kbps [4]). So any proposed mechanism for
delay is the most suitable parameter for congestion detection in congestion control in WMSNs must be respondent to video
these networks. applications requirements and complying this condition will
be suitable to other multimedia applications.
Keywords: Wireless Networks; Sensor; Congestion detection;
Video; Delay. Congestion control is conducted in three phases:
congestion detection, congestion notification, and rate
adjustment. In this paper we focus on first phase of congestion
I. INTRODUCTION control that is congestion detection. In section II we introduce
Advent of new technologies in sensors, camera and main congestion detection parameters and then we compare
microphones in smaller scales and with lower energy them in various respects.
consumption led to the design of wireless sensors with the
ability to sense their around environment. Nowadays there is II. CONGESTION DETECTION
widespread research in this area and new applications of these
sensors are becoming popular. An example of these So far, various methods are proposed in WSNs each of
applications is utilization of these sensors to monitor around which using one parameter for congestion detection. Selecting
environment that led to the advent of Wireless Multimedia this parameter is based on various factors, some of which
Sensor Networks (WMSNs) [1]. Designing these networks has being: network structure, data transmission rate, traffic
many challenges such as nature of wireless media and pattern, congestion probability, type of network applications
multimedia information transmission. Consequently traditional and QoS requirements of them, congestion effect on
mechanisms for network layers are no longer acceptable or applications and network resources [3].
applicable for these networks. Transport layer is one of the Table 1 shows congestion detection parameters along with
main layers in WMSNs which has greatly influenced the their related protocols. Besides, it is illustrated that which
overall performance of received packets. This is because of parameter is applied to what type of nodes. In each method to
limited bandwidth, high data transmission rate, burst nature of make out which node is in charge of congestion detection is
this multimedia traffic and high effect of congestion on these dependent on the parameter nature. For example using queue
packets [2]. Proposed methods for transport layer of sensor length is tapped only in intermediate nodes and in networks
networks are classified in two categories [3]: with end to end retransmission, retransmission time is only
used in Sink to detect congestion. Naturally parameters that
• Methods that provide reliability by retransmission are applicable to all of nodes are more flexible since
approach depending on network conditions and requirements it is
• Methods that reliability is achieved by congestion possible to determine location of detecting congestion. For
control example, if speed of congestion detection is at question, we
Retransmission causes excess power consumption and is can do it in intermediate nodes and if reducing load of sensor
not convenient for WMSNs. On the other hand because nodes is aimed, it is possible to use sink node for congestion
multimedia applications are sensitive to delay, reception of detection.
This work is partly sponsored by a research grant awarded by Iran
Telecommunication Research Center (ITRC).
978-1-61284-459-6/11/$26.00 ©2011 IEEE
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2. TABLE I. CONGESTION DETECTION PARAMETERS first classes consume large amount of energy and so are not
Parameter Location Protocol suitable for WMSNs.
STCP[5], Fusion[6],
Internal queue length Intermediate nodes Siphon[7], DECbit[8],
Some of congestion detection methods require
ESRT[9] synchronization. In this paper we have not considered
Inter packet arrival Sink and intermediate synchronization between sensor nodes. The methods described
PCCP[10]
time nodes here may be used without synchronization between nodes by
Service time of packets Intermediate nodes PCCP, CCF[11] some heuristics. In what follows we examine remaining
Load existing in parameters in two last classed of the table.
Intermediate nodes CODA[12]
channel
Sink and Source
Rate of logging packets ESRT, CODA B. Effect of congestion detection on quality of received video
nodes
Sensing packets( One of the main criteria that are important for selecting
without congestion congestion detection parameters is the way that parameter
Intermediate nodes ARC[13]
detection or
notification) affects the quality of received video in Sink. The more that
parameter affects the quality of video; the better is to use it in
Retransmission time of
packets
Sink RCRT[14] WMSNs. As we know delay, jitter and packet loss are metrics
of quality of service. Among the parameters remaining from
Sink and intermediate
Delay
nodes
no protocol previous section, delay and jitter comply with quality of
Sink and intermediate service. Other parameters such as queue length, service time
Jitter no protocol of packets or inter-arrival time of packets are indirectly affect
nodes
Power variance Intermediate nodes no protocol the quality of service. Reducing these parameters causes the
decrease of delay and as a result enhancement of the quality of
received video. Every protocol that is proposed for WMSNs
In what follows, all of congestion detection parameters are
should take these parameters into account. By bringing these
examined and eventually we select the most suitable
parameters into consideration we can provide quality of
parameter. Metrics of comparison is the cost, impact on
service of applications in transport layer. For example if delay
quality of video, locality or being global in the network and
is used for congestion detection, threshold of delay can be
false positivity and speed of congestion detection.
adjusted to comply to play-out time in receiver. In TABLE
III. each of the remaining parameters of previous section is
classified based on effect on quality of service.
A. Cost of congestion detection
One of the comparison metrics in congestion detection is C. Locality or globality of parameter
the cost. Some methods have overhead cost. Method with Among parameters of congestion detection, some of
lower cost is most convenient in sensor networks. This cost is parameters detect congestion only through local information
evaluated in two aspects: power overhead and processing that is available in node. For example when queue length is
overhead. used, each of the nodes detects congestion only based on its
Processing overhead: According to TABLE I. the own queue length. But some other parameters use more
parameters that are involved in intermediate nodes such as information and do not rely on their own information. Among
queue length, channel load or power variance have more them, delay parameters use the sum of delay of all nodes in the
processing overhead because of large amount of load on path. Needless to say that parameters that use global
intermediate nodes. information are better than those using local information. In
TABLE IV. we classified parameters based on this criteria.
Power overhead: This cost is the amount of energy that is
consumed for congestion detection. These parameters are D. Congestion Misdetection
classified in three categories:
Another criterion for congestion detection parameter
• Sensing the channel: Among methods that are listed assessment is that how accurately that parameter detects
in the TABLE I. those that have the cost of sensing congestion. The more that parameter accurately detect
channel have higher energy consumption and so they
are not suitable for WMSNs.
TABLE II. COST OF CONGESTION DETECTION
• Using extra packets: Using retransmission time of
dropped packets includes not only retransmission Congestion detection
Cost
request but also transmission of dropped packet. parameters
These methods waste a great amount of energy for Sensing channel Exponential power overhead
Retransmission time Extra packet transmit
congestion detection in sensor nodes. Energy variance, queue length,
• Low cost: Some methods do not necessitate extra service time of packets, overall Processing overhead (Intermediate
cost for congestion detection. These methods are the service time, delay, delay nodes are also in charge of
most suitable for congestion detection in WMSNs. variance, Inter arrival time of congestion detection)
In TABLE II. all methods are classified based on cost. packet
Congestion detection parameters that are classified under two Delay, jitter, inter arrival time of Low cost (only destination node is in
packets charge of congestion detection)
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3. TABLE III. CONGESTION DETECTION PARAMETER AND QUALITY OF Davg = * Davg + (1- ) * d (1)
VIDEO
Javg = * Javg + (1- ) * (d – Davg) (2)
Parameters Effect on quality of video
Energy variance No effect In these formulas d is delay of current packet and is
queue length, inter arrival time, Indirect effect weight that is assigned to delay in weighted average delay.
service time
delay, jitter Indirect effect
Davg is average delay of packets of a flow. In above equation
for computing average jitter instead of using absolute value of
TABLE IV. LOCAL OR GLOBAL jitter, the unchanged jitter is used. This is because when
congestion is terminated and delay is reduced using absolute
Parameter Information Type jitter causes that average jitter is increased and a misdetection
queue length, energy variance, service local
of congestion is produced. If we do not use absolute value
time
delay, jitter, Inter arrival time global when congestion is passed average jitter is decreased.
In the above equations the more be closed to 1 means
congestion the more is convenient for this task. Misdetection that we gave a more weight to previous average delay. So
occurs in two cases: upcoming congestion is not detected and average delay gained a slower pace than change of delay and
a notified congestion is not an actual congestion that is going so reaction to congestion is slow. Advantage of this behavior
to occur. For investigating this issue firstly we should get is that when delay of some packets is not because of
traffic pattern and then we should consider change in congestion situation and is transient, this method does not
congestion detection parameters so that accuracy or have congestion misdetection. The more is close to 0, it
misdetection of them is recognized. means that more weight is used for delay of current packets.
As we know video files with MPEG format consist of 3 So a small increase in delay of current packets increases the
types of frames named B, P, I. Distance between two I frames average. In this case congestion is detected more rapidly but in
is called GOP. B and P frames are between I frames. Number some cases there is a misdetection of a nonexistent congestion.
of these frames depends on encoding of frames. Length of We know that by the advent of congestion in network,
each type of frame and number of them in network are queue length in intermediate nodes is increased and as a result
different. I frame has the largest length and when transmitting delay of packets is increased. Having a scrutiny in above
this type of frame, rate of transmission is high. B and P frames equations we come to the conclusion that delay of each packet
have lower length although B frame has lower length than P. has a direct effect on average delay. But difference of delay of
Occurrence of congestion in network is proportionate to each packet versus average delay makes jitter. So by increase
number of resources that at the same time or in a low interval of delay, average of delay grows quicker than average of jitter
transmit I packets in one route. Variance of most of the and therefore congestion is detected and controlled quicker
congestion detection parameters is proportionate to traffic consequently.
pattern. This means that with increasing transmission rate, The other problem of average jitter is that when congestion
variance of them are increased and reducing rate decreases frequently occurs in network and network is often in
their variance. The only parameter that does not show this congestion state, average jitter is reduced instead of increasing
behavior is inter-arrival time of packets. This parameter is or remaining constant and as a result congestion is not
useful when inter transmission time of packets are equal and detected. On the other hand average delay in these situations
in such a condition it is recognized that if inter reception of always is above its threshold and always detects the
them changed we infer that there is a congestion in the path. congestion.
But source node in video traffics transmit packet in different
intervals (packets belonging to different frame types) and so To sum up, average jitter is not a suitable parameter for
sink cannot determine whether the interval between receiving video traffic congestion detection. In the following we
packets are due to congestion or for another reason. So this simulate a congested network to verify the discussion and
parameter is not convenient for our video network. select the best congestion detection parameter in accuracy and
quickness. The parameter that responds quicker to congestion
Accordingly some parameters are more suitable to our is the most convenient. Remaining congestion detection
network. These parameters are: delay, jitter, queue length and parameters are: average delay, average service time, queue
service time of packets. In the following we examine these length of nodes.
parameters and then we select best of them.
III. SIMULATION
E. Speed of congestion detection
We use NS2[15] and Evalvid[16] tool in our simulation.
Quick congestion control depends on two factors: quick Simulation parameters are shown in TABLE V. Five nodes are
congestion detection and suitable rate adjustment. One considered in our simulation arrangement of which are
important criteria comparison among congestion detection depicted in Figure 1. Node 5 is sink. Initially consider that
methods is that which method can detect congestion more node 1 sends packets of Foreman video file with MPEG
instantaneously. One of the most useful criteria is that which format. In Figure 2 we have shown change process of delay
parameter has more change in case of network congestion. For parameter for node 5. Average service time and queue length
example comparing two parameters of delay and jitter we have for node 3 is also shown in Figures 3 and 4. We assume that
the following averages for them.
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4. our network can tolerate one single burst and applications
would not be affected in such a burst. But our network will not
be respondent if two or more flows simultaneously go to a
burst. So packets will be late in sink or will be discarded. Thus
congestion will occur and we must detect it. We want to use
the parameter that detects it quicker and with more
probability.
For evaluating threshold value we use the following
method. Maximum amount of that parameter in case of one
single burst of a flow will be our threshold. Now with
increasing simultaneous flows we investigate that which
parameter and when violates the threshold. In previous figures Figure 3. Average service time for 1 flow
we conceive that maximum amount of average delay for a
flow is 64 milliseconds and maximum queue length for the
same number of flows is 6 and maximum average service time
is 16 milliseconds. We consider these values as our network
threshold.
TABLE V. SIMULATION PARAMETERS
Simulation parameters
Area 200mX200m
Channel WirelessChannel
Propagation Model TwoRayGround
Energy Consumption Modelu EnergyModel
Antenna OmniAntenna
Bandwidth 5Mbps Figure 4. Queue length for 1 flow
We start the simulation from scratch. This time both node
1 and 2 are sending simultaneously and because they use the
same coding format they go burst together. Average delay of
node 5, average service time and queue length for node 4 is
depicted in figures 5, 6 and 7. In these figures we see the
change in value of parameters with the increase of a
simultaneous flows and occurrence of congestion.
We observe that average delay only in a single congestion
case does not violate its threshold. But queue length passes its
threshold only 3 times and this threshold passing for service
time is only 5 times. Both service time and queue length have
similar change. But delay in occurrence of congestion have
Figure 1. Network architecture further change and so better detects congestion in terms of
both speed and accuracy.
Figure 2. Average delay for 1 flow Figure 5. Average delay for 2 flows
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When quick congestion detection is aimed we may use
intermediate nodes to detect and control congestion and if
reducing intermediate nodes overhead is favorable we can set
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One of the disadvantages of delay parameter is the
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Delay can be simulated with some heuristics and it can
become independent of synchronization. So this is left for
future work on the problem.
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