[IEEE 2012 National Conference on Communications (NCC) - Kharagpur, India (2012.02.3-2012.02.5)]...

Testbed Based Throughput Analysis in a Wireless

Sensor Network

Anand Kumar†, P. Gireesan Namboothiri†, Sarang Deshpande†, Sreejith Vidhyadharan†,

Krishna M. Sivalingam† and S.A.V. Satya Murty‡†Department of Computer Science and Engineering, IIT Madras, Chennai, India

‡IGCAR, Kalpakkam, India

Email: {anu22732, sahyagiri, uday.sarang, srevin}@gmail.com, [email protected], [email protected]

Abstract—This paper presents the throughput results obtainedfrom a Wireless Sensor Network testbed, with single and multiplesources in different network deployments and routing architec-tures. The experimental testbed deployed at IIT Madras consistedof commercially available Crossbow TelosB and MicaZ nodesand a custom-built sensor node based on the DigiNet Xbeechip, with all nodes implementing the Zigbee standard. Thenetworks were deployed in uniform grid topologies in threedifferent deployments with up to 228 nodes. The main aim ofthe experiments is to analyze the throughput and packet deliveryratio observed with single and multiple sources. The experimentalresults show that delivery ratio reduces with increase in datarate due to collisions and help characterise the network capacitylimits.

I. INTRODUCTION

Wireless Sensor Networks (WSNs) are quickly gaining pop-

ularity due to the ease with which they can be deployed at low

cost without depending on any of the existing infrastructure.

Traditional routing protocols for WSNs abstract the wireless

links as wired links and use modified wired network routing

protocols. However, these routing protocols do not fully con-

sider the network infrastructure and the unstable nature of the

wireless medium which leads to unreliable communication. To

address this problem, in this paper we have made an attempt to

study throughput performance in a WSN using commercially

available and custom-built sensor nodes.

Researchers have proposed several schemes to improve the

throughput parameters. However, there is a lack of adequate

experimental analysis on the maximum throughput achieved

in WSNs. We have conducted an empirical study to determine

the potential capacity of the architectures/channels in terms of

throughput. Different WSN testbeds were built using heteroge-

neous sensor nodes. Results achieved from our analysis model

show that, there is a limit to network architecture/channel

capacity, beyond which throughput falls drastically.

In this paper, two kinds of testbed experiments are presented

for conducting the throughput analysis. The first testbed con-

sisted of Crossbow TelosB and MicaZ nodes on a small scale

network. In the second testbed setup, a custom-built sensor

node was developed and a large scale testbed comprising of

228 nodes was deployed using both Crossbow TelosB and

custom built sensor nodes.

Fig. 1. Custom-built Xbee based sensor node.

II. TESTBED COMPONENTS

This section presents the details of the wireless sensor nodes

used in the testbed.

A. TelosB and MicaZ

The Crossbow TelosB node consists of an 8 MHz 16-bit

TI MSP430 micro-controller, with 10 KB RAM [1]. The

Crossbow MicaZ node consists of a 16 MHz 8-bit Atmel

ATMega 128L processor, with 128 KB RAM and 512 KB flash

memory. The nodes run the TinyOS operating system [2], with

the NesC language [3] used for application programming. The

sensor nodes use the CC2420, an IEEE 802.15.4 compliant

radio transceiver chip supporting the ZigBee protocol stack

[4]. The radio operates in the ISM band of 2.4 GHz frequency.

CC2420 provides 32 different power levels (0-31) at which

a packet can be transmitted [5], where the highest level 31

corresponds to 0 dB (1 mW).

B. Xbee based nodes

A custom-built sensor node was designed and implemented

as part of this testbed. The Digi International Xbee Series

II chip, which is IEEE 802.15.4 compliant, was chosen for

the micro-controller and radio transceiver functionality. The

Xbee node enables fast prototyping and has the following

components and functionalities: Embers EM250 Integrated

radio transceiver; 8051 micro-controller with GPIO pins and

antenna; Znet 2.5 Protocol as well as Digi’s Digi-Mesh pro-

tocol for routing. The Xbee node can be controlled using an

978-1-4673-0816-8/12/$31.00 ©2012 IEEE

AT-command based API. The custom-built Xbee based node’s

picture is shown in Fig. 1.

Digi provides a software named “X-CTU” which can be

used to change the firmware in Xbee chips. Two different

Zigbee protocol stacks are supported by the series II chips,

namely, ZNet protocol and DigiMesh protocol. The nodes

in these experiments were configured to use the DigiMesh

protocol. The configuration settings used are as listed below:

(i) Every node was configured as either a coordinator or a

router. (ii) Each node has a 16 bit ID apart from a unique

64 bit PAN ID. The 16 bit ID is assigned, when a node is

associated to a coordinator. The node changes its ID whenever

there is a change in the configuration. (iii) One coordinator and

Five nodes in a cluster were configured in a dedicated channel

using the scan channels option in “X-CTU” application such

that communication takes place between the nodes and the

coordinator of that cluster itself. Please note that there are

16 orthogonal channels available in the 2.4 Ghz bandwidth

as specified in the IEEE 802.15.4 protocol. (iv) The sensor

nodes were configured to send a 49-byte packet that includes

the sensed data to the coordinator in each sampling interval.

III. CROSSBOW NODES BASED TESTBED

The details of the Crossbow nodes based testbed setup and

the results obtained are presented in this section.

A. Description

The experimental testbed consists of sensor nodes placed in

a grid of different sizes which were deployed at the central

stadium in the IIT Madras campus. The distance between

adjacent nodes is set to ten meters. The node specifications

claim higher transmission distance of around 50 m. However,

we chose the distance to be 10 m such that 99% delivery ratio

was consistently achieved on a single link based on repeated

experiments [6]. When multi-hop paths are used, the effect

of interference from neighboring nodes is important. It has

been shown that the interference range is up to 1.78 times the

transmission range [7].

The experiments were conducted with two base stations.

When a source node has data to transmit, it generates two

data packets, one for each base station. The size of each data

packet is 128 bytes (i.e. 1 Kbit). Each source generates packets

at periodic intervals that was varied in the experiments. For

example, for an inter-packet interval of 200 ms, the source

generates five packets per second for a rate of 5.12 Kbps.

These experiments used only one of the 16 available channels

for communication.

A Manhattan routing based multi-hop protocol was used to

route the packets from the source to the base station. When

a node receives a packet, it calculates its next hop nodeID

based on the packet’s destination address and its own nodeID.

If the destination address is less than its own nodeID, the

sensor node forwards the data to its downstream nodes in a

Manhattan manner. If the destination nodeID is greater than its

nodeID it will forward the data packet to its upstream nodes.

(a) Photograph (b) Layout

Fig. 2. A 42-node grid deployment.

B. Performance results

Throughput (in Kbps) and delivery ratio (as a percentage)

were measured at the base station. Delivery ratio is defined

as the ratio of the total amount of data received at the base

station to data generated at the source. In general, the packet

delivery ratio depends on link quality, interference and number

of hops between the source-destination pair.

The throughput for a single source was analyzed in a larger

96-node grid network, not presented here. The delivery ratio

was close to 100% as expected. This was done to verify that

multi-hop routing of up to 10 hops was practically feasible

and that packet forwarding took place successfully. The delay

per hop was also measured. The average one hop packet delay

(including processing and propagation delay) was measured to

be 20 ms. There was no queuing possible at the intermediate

nodes due to hardware limitations. Thus, the end-to-end delay

of a session was directly proportional to the number of hops.

1) Multiple sources in centralized architecture: The first

set of experiments were conducted using the 7× 6 Crossbow

TelosB node based grid network shown in Figure 2, deployed

in the IIT Madras outdoor stadium. The two base stations were

implemented using Crossbow MicaZ nodes, each connected to

a laptop. The nodes were deployed at a height of 1 m above

the ground, for better radio reception. The node identifiers are

assigned based on their geographical position as shown in the

Figure 2(b).

Experiments were conducted with 1, 3 and 5 sources and by

varying the data rates from 3.14 to 12.8 Kbps, by varying the

inter-packet generation interval. For example, 200 ms interval

corresponds to 5.12 Kbps. Transmitter power levels of 16

and 24 were used to analyze the effect of power level on

throughput analysis. Table I presents the throughput results

with three sources transmitting at a power level value of 24.

The experiments were done for four different data rates. Total

number of active connections at any point in time in the

network is 33. It was mainly observed that, even using 3

sources, the delivery ratio is much less than 100%, ranging

between 12% and 63%. When the data rate increases, the rate

of delivery of packets decreases, as expected. It is also seen

that, the receiving rate at BS-1 from source-2 and source-3

dropped to zero (this occurred after forty seconds into the

experiment). The experimental results show that the increase

TABLE ITHROUGHPUT ANALYSIS WITH 3 SOURCES WITH DIFFERENT POWER

LEVELS

(a) At BS-1 (Source Power Level = 24)Rate/Source Traffic Received from Source Total N/W Traffic Delivery

(Kbps) S-47 S-31 S-16 Generated Received Ratio

(Kbps) (Kbps) (Kbps) (Kbps) (Kbps) (%)

5.12 1.41 3.69 3. 49 15.36 8.6 56

6.4 2.34 2.86 3.96 19.2 9.17 47.44

8.53 2.65 4.04 3.76 25.6 10.47 40.9

12.8 0 0 4.44 38.4 4.44 11.58

(b) At BS-2 (Source Power Level = 24)Rate/Source Traffic Received from Source Total N/W Traffic Delivery



5.12 2.56 3.63 3.58 15.36 9.78 63.69

6.4 3.01 2.28 3.057 19.2 8.35 43.5

8.53 3.05 3.2 1.49 25.6 7.76 30.32

12.8 4.07 0.58 0.32 38.4 4.98 12.96

(c) At BS-1 (Source Power Level = 16)Rate/Source Traffic Received from Source Total N/W Traffic Delivery



5.12 3.62 3.19 2.41 15.36 9.14 59.55

6.4 3.12 4.14 3.12 19.2 10.37 54.06

8.53 4.06 4.15 3.05 25.6 11.26 44

12.8 0 3.35 3.59 38.4 6.94 18.09

in data rate reduces the rate at which the packets are delivered.

Also, the rate of delivery of the packets will be higher if the

path used by the source is not shared by any other source to

reach the same destination.

Due to interference and high data rates, the nodes that lie on

the forwarding path for multiple sources (such as forwarding

nodes 29, 23, 17) freeze up due to the high data rate and

because of their low processing capability. In order to reduce

the interference effects, the experiments were repeated with a

power level of 16. The results presented in Table I(c) show

that the delivery ratio is still low with 3 sources.

TABLE IITHROUGHPUT ANALYSIS WITH 5 SOURCES AT BS-2 (POWER LEVEL= 16)

Rate Traffic Received from Source Total N/W Traffic Delivery

(Kbps) S-47 S-35 S-31 S-25 S-16 Generated Recd. Ratio

(Kbps) (Kbps) (Kbps) (Kbps) (Kbps) (Kbps) (Kbps) (%)

6.4 3.75 3.28 2.34 1.27 1.95 32 12.61 39.43

4.26 2.87 1.81 2.11 1.47 2.05 21.33 10.34 48.48

Table II presents the results with 5 sources in the 42-node

network. For a source packet generation rate of 6.4 Kbps, the

delivery ratio falls from 43.5% to 39.43% when the number

of sources is increased from 3 to 5. Overall, it is seen that

the interference and forwarding capabilities limit the network

throughput significantly.

Previously conducted research work [6], [8] shows that

throughput depends on several parameters including the num-

ber of active sources, wireless link quality, interference and

number of hops. It is well known that a hierarchical multi-

tiered architecture with multiple communication channels

(available in IEEE 802.15.4 standard) will provide better

throughput. Hence, a cluster-based architecture has been stud-

ied to analyze the system performance.

2) With single source in clustered Architecture: In this

architecture, the nodes are organized into clusters. A cluster

head receives packets from its cluster members and forwards

it to the base station through the next backbone node or

Fig. 3. 12×9 grid with backbone nodes (single source - 54)

Fig. 4. Deployment in IITM Old Gymkhana (Gym).

cluster head. A backbone node acts as a relay and acts as

a communication bridge between two adjacent cluster heads.

The experiments were conducted for a 12×8 grid as shown in

Figure 3. In this network, the cluster heads are 121, 123, 125,

131, 133, etc. (which are shown in blue color). The backbone

nodes are 122, 125, 126, 127, 128, etc. (which are shown

in green color); the source node is 54 (which is shown in

red color). For a data generation rate of 6.82 Kbps (which

is quite high), the observed throughput at the base station

was 6.1 Kbps for a delivery ratio of 89.4% in this cluster

architecture. Thus, this experimentally validates the need for

a cluster based architecture for large networks, as studied in

the next section.

Due to increased transmission power and channel inter-

ference, it was observed during the above experiments that

the orientation of the sensor node as well as the height of

the node from the ground level have a high impact on the

throughput performance. Obstacles such as a human or foliage

plant and atmospheric moisture also had a major effect on the

performance.

IV. XBEE NODES BASED TESTBED

This section presents the Xbee node based testbed and the

results obtained from the same.

A. Description

The testbed consisted of heterogeneous sensor nodes con-

sisting mostly of the custom-built sensor nodes based on Digi

Xbee chip and a small number of Crossbow TelosB motes. The

network had 228 nodes including 192 Xbee nodes, 32 TelosB

based cluster heads and four TelosB based base-stations. The

nodes were divided into four groups, named as Group-1,

Group-2, Group-3 and Group-4. Each group consisted of eight

clusters, where each cluster had five custom built sensor nodes,

a coordinator and a cluster head. Within a group, each cluster

was configured to use a unique radio channel for intra-cluster

communication and called as CH Channel𝑖, where 1 ≤ 𝑖 ≤ 8.

Each cluster head was configured with a unique radio channel

to communicate with the base station (BS Channel). For a

group, eight out of the 16 channels available in IEEE 802.15.4

standard were used. The same channels were reused in the

other groups for intra-cluster communications.

The Digi Xbee Series can run on either Znet or the Digi-

Mesh protocol (for which the copyrights are reserved). A

sniffer application was designed for achieving interoperability

between Xbee and Crossbow TelosB. That is, a cluster head

was programmed to sniff the packets from its cluster members.

To reduce CSMA delays and interference, each cluster was de-

signed to work in a dedicated channel. This was done by mod-

ifying the Receiver Module of TinyOS CC2420 Radio stack.

Xbee modules were configured to work in predefined channels

and Xbee-Java API (http://www.code.google.com/p/xbee-api/)

was used to send and receive commands and responses.

The packet dumps were analyzed for patterns and necessary

information was obtained. Using this information, a static

clustering procedure was adopted.

The experiments were conducted by placing sensor nodes in

a rectangular grid at an indoor location named Old Gymkhana

(Gym) in IIT Madras campus. The inter-node spacing was set

to two meters in each group; and the adjacent groups were

horizontally separated by 4 meters as shown in Figure 4.

Two different configurations were studied: one with a single

base station and one with multiple base stations. Different sam-

pling intervals were used to vary the amount of network traffic.

Each source transmitted a packet to its cluster head using

single-hop communication; the cluster head then forwarded the

packets to the base station using single-hop communication.

The metrics measured were received throughput and delivery

ratio at the base station.

B. Performance results

Each sensor node in a cluster was configured for generating

sensed data at fixed intervals. All the five nodes in a cluster

generate packets simultaneously as per the sampling rate. The

source node in a Cluster𝑖 generates a 49 bytes packet and sends

the same packet to the coordinator using CH Channel𝑖. This

packet is sent to the cluster head. The packet is sniffed by the

cluster head and buffered. Once the cluster head accumulates a

total of 125 bytes from all the node members, it performs data

aggregation and sends a 125 byte-packet to the base station

on its BS Channel.

(a) Single BS (With 225 Nodes)

(b) Multiple BS (With 228 Nodes)

Fig. 5. Testbed set up for Data collection.

TABLE IIITHROUGHPUT FROM 32 CLUSTER HEADS: SINGLE BASE STATION

Sampling Interval (ms) 500 300 200 100 50

Per Source (Kbps) 0.62 1.04 1.56 3.12 6.25

Total Generated (Kbps) 20 33.3 50 100 200

Total Received (Kbps) 16.9 26.13 34.54 36.45 29.95

Delivery Ratio (%) 84.5 78.42 69.09 36.45 14.98

After completing the transmission to the base station, the

cluster head returns to the original channel for sniffing the

packets from the member nodes. Each member node in a

cluster was enabled for transmission at fixed intervals. When

multiple nodes try to communicate, collisions occur and will

in turn affect throughput. The main aim of the experiment

is to analyze the throughput parameters in a WSN using

multiple channels and multiple sources using cluster head

based architecture. The experiments have been repeated with

different data rates to calculate the throughput parameters at

the single or multiple base stations deployed. Experimental

results show that the delivery ratio reduces with increase in

transmission rate. By increasing the data rate, the throughput

parameters increase up to a certain point beyond which the

throughput drops.

1) Single Base station in a Cluster architecture: We first

conducted experiments using a single base station, 32 clusters

with each cluster having 5 sensor (source) nodes, a coordinator

node and a cluster head, for a total of 225 nodes in the

network. The deployed network is shown in Figure 5(a).

The different source node packet generation intervals were:

500 ms, 300 ms, 200 ms, 100 ms and 50 ms at the source

nodes. One Crossbow TelosB node was configured as the

base station to receive packets from all the 32 cluster heads.

The results are presented in Table III. When the sampling

interval decreased from 500 ms to 50 ms, the throughput

received at the base station was increasing up to 100 ms

sampling interval and reached approximately 36 Kbps for a

source generation rate of 100 Kbps. Thereafter the throughput

value fell drastically. However, this was not the case with

the delivery ratio. The delivery ratio reduced as the sampling

interval was decreased from 500 ms to 50 ms. The decay

was faster for the sampling intervals of 100 and 50 ms. Post

analysis of the architecture design reveals two reasons for

decrease in throughput, discussed below.

In this setup, 32 cluster heads behaved as sources and

periodically sent the data to a single base station. This caused

more traffic at the base station, especially when the sampling

interval decreased from 500 ms to 50 ms. This is because the

source was sending more packets to the cluster head, followed

by aggregation at the cluster head which sends a 125 bytes

packets to the BS. This led to high traffic and congestion at

the base station. Hence several packets were dropped at the

base station leading to reduced throughput.

Whenever the cluster head has a packet to send to the

base station, the cluster head switches to the base station

channel and sends packet. After transmission, the cluster

head switches back to the members channel for sniffing the

packets. During this transmission interval, the sensor node’s

data packets were dropped at the cluster head level leading to

reduced throughput.

2) Multiple Base stations: Channel switching was unavoid-

able because of a single radio at the cluster-head and the

use of multiple channels. An alternative way to improve the

throughput parameters is to utilize multiple base stations, as

shown in Figure 5(b). The experiments were conducted by

varying the source node sampling rate as 500 ms, 300 ms,

200 ms, 100 ms and 50 ms. Four Crossbow TelosB nodes

were configured as the base stations to receive the packets from

the respective groups, i.e. Base station-𝑖 receives packets from

Group 𝑖. Static clustering was performed at each base station in

order to avoid unnecessary receptions from other groups. The

throughput results are presented in Table IV and in Figure 6.

When the sampling interval decreased from 500 ms to 50 ms,

the throughput received at the base stations increased up to

100 ms sampling interval and reached approximately 38 Kbps

for a total source generation rate of 100 Kbps. Beyond this,

the throughput decreased. A marginal difference was observed

in the throughput parameters between the single base station

and multiple base stations experiments.

We see that for the sampling intervals of 200ms, 100ms

and 50ms, the data generations rates were 12.5 Kbps, 25 Kbps

and 50 Kbps respectively. However, the received throughput

at all the base stations was between 9 and 9.5 Kbps. Constant

throughput at the base station irrespective of the source gener-

ation is due to the architecture design limitation with multiple

sources. In some cases, the architecture used in this experiment

places constraints on the achievable channel capacity.

V. CONCLUSIONS

This paper presents testbed based experimental analysis

of throughput in a Wireless Sensor Network. The network

consisted on off-the-shelf Crossbow sensor nodes and custom-

built Xbee based nodes. Flat and cluster-based architectures

Sampling Interval (ms) 500 300 200 100 50

Per Source (Kbps) 0.62 1.04 1.56 3.12 6.25

Per Group (Kbps) 5 8.33 12.5 25 50

HCH1 Received (Kbps) 4.85 7.46 9.43 9.43 9.21

HCH1 Delivery Ratio (%) 97.00 89.50 75.41 37.19 18.42







Total Generated (Kbps) 20 33.33 50 100 200

Total Received (Kbps) 9.54 30.96 36.63 38.12 35.01

Delivery Ratio (%) 97.70 92.90 73.26 38.20 17.50

TABLE IVTHROUGHPUT FROM 32 CLUSTER HEADS WITH FOUR BASE STATIONS

0

50

100

150

200

250

0 100 200 300 400 500 600

Th

rou

gh

pu

t (K

bp

s)

Sampling Interval (ms)

Received Throughput-SingleBSReceived Throughput-MultipleBS

Actual Throughput

Fig. 6. Throughput results for the 228 node based experiments.

with single and multiple communication channels were stud-

ied. The experiments helped us quantify the throughput limits

of the channel. In particular, it was interesting to observe that

the upper limits of throughput received at the base station is

around 35-40 Kbps when combined of all the groups. Data

monitoring applications might find these results useful when

deciding the maximum generated source traffic.

REFERENCES

[1] “Crossbow MicaZ mote specification. URL: http://www.xbow.com/.”[2] “TinyOS: An open-source OS for networked sensor regime. URL:

http://www.tinyos.net/.”[3] “nesC: A Programming Language for Deeply Networked Systems. URL:

http://nescc.sourceforge.net/.”[4] “ZigBee: Low-cost, low-power, wireless networking for device

monitoring and control. URL: http://www.digi.com/technology/rf-articles/wireless-zigbee.”

[5] M. Mallinson, P. Drane, and S. Hussain, “Discrete Radio Power LevelConsumption Model in Wireless Sensor Networks,” in IEEE MASS, Oct.2007, pp. 1–6.

[6] P. G. Namboothiri and K. M. Sivalingam, “Performance of a multi-chanelmac protocol based on IEEE 802.15.4 radio,” in IEEE LCN, Oct. 2009.

[7] K. Xu, M. Gerla, and S. Bae, “How effective is the IEEE 802.11RTS/CTS handshake in ad hoc networks?” in IEEE GLOBECOM, Nov.2002, pp. 72–76.

[8] P. G. Namboothiri and K. M. Sivalingam, “Capacity Analysis of Multi-Hop Wireless Sensor Networks using Multiple Transimission Channels:A case study using IEEE 802.15.4 based networks,” in IEEE LCN, Oct.2010.

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