A Modified MPRR Protocol for WSN in Agricultural Scenario

Marco Cagnetti

, Mariagrazia Leccisi

and Fabio Leccese

Dipartimento di Scienze, Università degli Studi “Roma Tre”, via della Vasca Navale n.84, Rome, Italy

Keywords: WSN, Routing Protocols, Precision Agriculture, Castalia, Simulations, Energy Management.

Abstract: This paper analyses the use of a WSN for agricultural scenario, referencing to the modality of communication

between the network nodes, and proposes a modified version of Multipath Ring Routing (MPRR) to improve

performances and robustness of the network on the long period. Through simulations with Castalia, some

limits of the standard MPRR have been highlighted, and through the possibility to modify the algorithm itself,

improvements have been made that make the modified MPRR suitable for our scenario.

1 INTRODUCTION

Precision Agriculture is a Management System

integrated with the aim of optimizing the efficiency

of the agricultural production, product quality and

profitability, increase climate and environmental

sustainability, using tools and innovative

technologies.

Italy has provided for Rural Development

Programs in various Italian regions, through

intervention strategies related to the spread of

agronomic management methods and approaches.

The Ministry of Agricultural Policies and Europe

itself invested many funds on precision agriculture

and agricultural engineering (Ministero delle

Politiche Agricole Alimentari e Forestali, 2017).

The development of applications more and more

suitable for national productions is important for

many reasons: from production and quality

optimization to the reduction of business costs, from

minimizing environmental impacts with seeds,

fertilizers, agro pharmaceuticals up to cutting water

use and fuel consumption. In fact, the monitoring of

the environmental parameters permits to manage

many interesting areas as:

 the use of pesticides and harmful substances,

 the quality of air and water

 monitoring of fires and atmospheric events or

natural and non-natural disasters etc.

https://orcid.org/0000-0003-0198-5043

https://orcid.org/0000-0003-2775-637X

https://orcid.org/0000-0002-8152-2112

The research field of precision agriculture is

having an increasing interest from the scientific

community due to its importance and the possibility

of using technology and IoT to improve processes.

For example, the use of an optoelectronic sensors

to evaluate the radial growth of a fruit, monitoring

fruit production, has been evaluated (Thalheimer

2016), while in (Pahuja et al., 2013) has been

monitored the climatic trend in commercial

greenhouses, in order to evaluate the production trend

and the health of the plants, through Wireless Sensor

Networks (WSN). In (Leccese et al., 2019) has been

studied the development of a WSN for smart

monitoring of pesticides on agricultural land,

designing an electronic nose starting from an array of

commercial gas sensors developed for other

environmental applications. In (Kim et al., 2008) a

distributed Wireless Sensor Network has been used to

remotely control an irrigation system. In (Nisio et al.,

2020) fast detection of olive trees affected by xylella

fastidiosa from uavs using multispectral imaging has

been implemented. In (Giaquinto et al., 2019) a

sensor for leak detection in underground water

pipelines has been developed. In (Cagnetti et al.,

2020) a comparison between the most suitable routing

protocols for WSNs applied in wide agriculture

scenarios is shown and it evidences the most suitable

protocol for a particular scenario.

In our paper, we are going to analyze the use of a

WSN for the agriculture, referencing to the modality

Cagnetti, M., Leccisi, M. and Leccese, F.

A Modiﬁed MPRR Protocol for WSN in Agricultural Scenario.

DOI: 10.5220/0010374701430150

In Proceedings of the 10th International Conference on Sensor Networks (SENSORNETS 2021), pages 143-150

ISBN: 978-989-758-489-3

143

of communication between the network nodes, and

proposing a modified version of Multipath Ring

Routing (MPRR) to better performances and

robustness of the network on the long period.

Through Castalia, a free simulation tool, the limits

of a standard MPRR have been evidenced, giving us

the possibility of modify the implementation of the

algorithm, improving it significantly.

2 WIRLESS SENSOR NETWORK

WSNs are widely studied and applied to many

various contexts (Gallucci et al., 2017; Spagnolo, et

al., 2020). They are composed by many sensors

(called nodes) and all is necessary to their functioning

and communications; each node communicates with

each other and with a sink that collects, analyzes,

tracks and eventually sends data to other platforms,

and typically is connected to Internet and mains

(Leccese et al., 2014; Leccese et al., 2017).

The node is a device formed by sensors, a

microcontroller to manage the communication

between nodes, transmitter to connect with the other

nodes and sink through an antenna and an adaptive

circuit, a power supply circuit, and some I/O

interfaces to manage signal from sensors.

The topology of a WSN (Figure 1) describes the

physical position of each node: it strictly depends on

scenario and on sensors. Nodes are spatially disposed

according to the area to monitor, and they

communicate, auto organize themselves and

coordinate with each other through a routing protocol.

Figure 1: A generic WSN architecture.

The environmental monitoring is a typical

application of WSNs, for example to monitor

archeological sites or museums (Leccese et al., 2017;

D’alvia et al., 2017; Leccese et al., 2018), for

surveillance (Morello et al., 2010; Islam et al.2012;

Caciotta et al., 2014), in aerospace scenarios

(Pasquali et al., 2016; Cagnetti et al., 2020) or street

light control (Leccese, 2013). They are very flexible

and robust structures that can be configured in the

correct way according to the scenario; in fact, an ideal

network cannot exist since each scenario has some

characteristics that should be evaluated (Pasquali et

al., 2016; Pasquali et al., 2016).

3 AGRICULTURAL SCENARIO

The definition of the operative scenario is

fundamental to design a WSN correctly; in fact, each

scenario has some characteristics we need to know

and analyze, and a wide number of parameters should

be considerate and studied.

It is important to guarantee the transmission, that

must be reliable and safe (a node sensor can stop

working compromising the stability of the network or

requiring a new configuration), and the number of

nodes must be compatible with the area to be

monitored (too few sensors could decrease accuracy

and too many sensors could increase energy

consumption). The scenario is an agricultural field

where the sink is positioned at the center of the

structure, and is connected to the national electrical

grid and to internet.

Sensors are arranged in a radial pattern around the

sink, their number is between 9 and 15 each hectare,

spaced about 25/50 m; the sink provides to send them

to specific system for data analysis through internet

connection.

Various specific constraints should be evaluated:

 Open field position of devices: sensors are

often on open field, so they are exposed to

meteorological events. They needs to be made

in a very simple and a light way, using robust

and reliable components as Commercial-off-

the-Shelf (COTS).

 Energy saving: the evaluation of the supply

type of network is an important part of

agricultural scenario; in fact, the connection to

the National electric grid could be not

provided. A cabled power supply is not

recommended due to the possible damages of

cables caused by water, or animals, but

batteries have limits to their life and

dimensions. To improve energy saving, the

choice of electronic components and of

communication modality, as routing protocol

and strategies for a limited use of resources, is

fundamental. E.g., a sensor can be activated

for a limited time, to avoid a continuous use of

Internet

Local

Remote

Sink

Nodes

WSN

WSN4PA 2021 - Special Session on Wireless Sensor Networks for Precise Agriculture

144

batteries, or network can be configured using

low-energy routing protocols.

 Sensor maintenance: a structure that does not

require great maintenance should be used;

sensors arranged in open spaces are subjected

to problems that would require heavy and/or

expensive maintenance.

 Economy: the structure must have affordable

costs for maintenance and commercial

development.

 The network is static or dynamic: the sensors

are placed in the field and remain in place until

they are naturally switch off.

4 ROUTING ALGORITHMS

The hardware of sensors and sink can be technically

composed by specific low energy components, and

the adaptive structures can be designed to minimize

energy consumption, but the network management

can be optimized searching for the best

communication modality between nodes and sink.

The consumption of a sensor is due to the

transmission phase, so an energy saving can be

obtained using specific protocols that guarantee

reliability of transmission, accuracy of information,

low consumption and maximize the life of the nodes.

A high consumption can be due to the overlapping

of information that are lost and should be transmitted

again, to the listening time of a node or the reception

of wrong packet.

Routing algorithms are a central point to work on

to save energy. Routing works managing the hops

between nodes and sink, creating the shorter path as

possible. Some protocols are designed to use

clustering, aggregating data before the dispatch. The

data aggregation is very useful to decrease energy

consumption, limiting the transmission time of a

sensor.

Analyzing literature and according to our

experience, the most suitable protocols to limit

consumptions are the LEACH or Low-Energy

Adaptive Clustering Hierarchy (Leccese et al., 2019),

the PEGASIS Power Efficient Gathering in Sensor

Information Systems (Shekar, 2012), the AODV or

Ad hoc On Demand Distance Vector (Maurya et al.,

2012) and the Multipath Ring Routing or MPRR

(Pandya & Mehta, 2012).

LEACH is a cluster based protocol, in which

sensors are divided into clusters and each one

contains a cluster head that collects data and sent

them to sink, limiting the time of transmission and

consequently the consumption. The node disposition

is a limitation because some nodes could be very far

from sink.

The AODV protocol is specifically used for

mobile networks and creates a table of shorter path

between nodes when requested by them. If the

network topology changes, paths are rebuilt. It’s

limitation is due to a bad managing of network

congestion.

Multipath ring routing uses multiple propagation

path between each sensors, to maximize network

reliability and avoid the loss of packets. The sink

provides a configuration signal to the nearest nodes,

assigning them a hierarchy. They are set with a level

of ring 1, so they send the signal configuration to the

nearest nodes that configure them as level 2 and so

on, until a level number, called ring number,

characterizes each sensor. At the end, network

provides almost the best paths between nodes. During

the transmission phase, a signal from node N is sent

towards all the N-1 nodes that send it toward the N-2

nodes and so on until it arrives to the sink. A sensor

could break or switch off; in this case the multiple

paths ensure that the signal reaches the sink through

another node of the same level, but its limitation is

due to initial configuration that could spent some

energy and time.

5 MPRR AND CASTALIA

We focused our attention on MPRR, providing more

simulations through Castalia, a very useful tool for

studying WSNs.

It is a free application that includes the

implementation of some routing protocols that are

applied to the specific topology of the scenario

defined by user. For this reason, we could compare

the routing protocols, according to the specific

scenario: each scenario has some characteristics that

can be evaluated through a simulation.

We also worked for a visual tool to show the

network physical topology and package trend during

a transmission time.

We focused our attention on MPRR for its

characteristics of being very robust and efficient,

reducing possibility of losing information. In fact,

although it provides multiple propagation paths, if the

nodes of a certain level shut down, the nodes of the

previous level could not receive messages to send

toward the sink. A multi-hop structure can be used; in

this case, the dead node is bypassed, permitting to the

message to arrive; obviously, it is very expensive for

consumption because of the more distances between

nodes and can create problem of overlapping.

A Modiﬁed MPRR Protocol for WSN in Agricultural Scenario

145

For our scenario, MPRR is not the first choice

because of the consumption during the initial

configuration phase, and the transmission can bring

to an early shut down of the network (Leccese et al.,

2014). However, the arrangement of the nodes is

compatible with MPRR, so we ask if it was possible

to improve this algorithm to make it more efficient.

Our simulations highlighted these problems and

allowed us to evaluate the configuration of the nodes

in MPRR.

In fact, the network configuration occurs only one

time and it sets the best routes for each sensor. In this

case, a little percentage of node could be wrong or no

configured: these nodes could not ever communicate

between the other nodes and the sink. This problem is

caused by the contemporary node’s transmission, so

during the configuration phase, an overlapping of

signal, and a reduction of signal/noise ratio, could

occur, causing a bad configuration of some sensors.

Castalia tool showed clearly and visually this

configuration problem, in which some nodes

appeared to be inactive.

The wrong configuration can be characterized by:

 one or more nodes that are not configured,

making them invisible to the network;

 one or more nodes that can acquire a wrong

ring number, incrementing the route to the

sink.

Our scenario provides a central sink and many

nodes disposed around it, equally spaced and with the

same initial energy.

Figure 2 shows the configuration: a central sink

sends the configuration message to the nearest nodes.

Figure 2: The topology of our scenario.

During the configuration, the sink sends a

message to the nodes that configure themselves as

level 1, then the nodes of level 1 (A1,B1 …) send

messages to the nearest nodes that configure

themselves as level 2 (A2, B2…) and so on until each

node is configured.

Only one configuration message could be

necessary to configure all nodes correctly, but in the

reality, the distance between nodes is not the same, so

these situations can happen:

 more packets collide between each other

(Figure 3). In this situation, the configured

node A1 and B1 transmit the message at the

same time towards the node N2 that does not

configure itself as level 2 because it cannot

decode the message. When node A3 will send

the configuration packet, N2, which has not

been configured yet, will configure itself as

level 4 instead of level 2, incrementing the hop

number from the sink.

Figure 3: The collision between two packets makes N2 not

configured.

 Nodes transmit in every direction (Figure 4).

The configuration packet from A1 is

intercepted by A2 but it can be intercepted also

by A3 that configure itself as level 2 instead of

level 3. Therefore, nodes already configured

are not newly modified, but nodes of higher

level could configure themselves wrongly.

Figure 4: The signal from A1 is intercepted by A3, which is

incorrectly configured.

WSN4PA 2021 - Special Session on Wireless Sensor Networks for Precise Agriculture

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Our simulations have confirmed the inefficiency,

due to the bad configuration; through a visual tool, we

monitored the configuration of all nodes, evidencing

the overlapping of signal and the loss of configuration

packet.

To avoid a bad configuration, we have modified

Castalia’s core to manage:

 a little delay to avoid the contemporary

transmission of packet by nodes, reducing

the probability of interferences;

 a double configuration signal. The first

configuration packet starts from the sink

toward the nearest sensors to configure the

whole network according to the standard

MPRR, while a second signal checks the

network and re-configure it when the first

signal failed, warranting a correct

configuration of all nodes.

According with these modifications, in case of

Figure 3, the node N2 that was not configured by the

first configuration signal will be configured as level 2

by the second signal. In case of Figure 4, node A3 is

configured wrongly as level 2 by the first signal from

A1, but the second configuration signal rechecks the

ring number and re configures node A3 as level 3. The

reconfigured nodes will reconfigure also all nodes of

higher levels. Therefore, compared to an initial

increase of energy consumption due to the

reconfiguration, at the end, the network is correctly

configured and it does not need configuration

anymore.

Figure 5 shows the initial topology for a

simulation of 108 sensors. No sensor is configured,

because it is waiting inactive for a configuration

packet from sink.

Figure 5: Initial topology for a network of 108 nodes. The

sink is at the centre of the network.

When the sink starts to transmit, the nearest node

configure themselves as level 1. Figure 6 shows in

green the nodes of level 1 just configured and, in red,

the nodes of level 2. The black circles represent the

configuration packet expanding for the entire

network, while Figure 7 shows a completely

configured network.

Figure 6: The configuration signal starts from the sink to

the sensors, which self-configure to create the best paths.

Figure 7: The whole network is configured.

Figure 8 shows a detail of the first configuration

phase: green nodes are configured as level 1, while

red nodes are configured as level 2.

Figure 9 shows the reconfiguration of nodes 2, 3,

7 and 8: in Figure 8 they were configured as level two

(red), while after the second configuration signal are

reconfigured as level one (green).

A Modiﬁed MPRR Protocol for WSN in Agricultural Scenario

147

Figure 8: The configuration of levels 1 and 2 by the first

configuration signal.

Figure 9: The re-configuration of nodes after the second

configuration signal.

6 SIMULATION AND RESULTS

Through Castalia we evaluated:

 the number of transmitted and sent packets

between nodes and sink;

 the life span of nodes, caused by excessive

consumption of batteries or physical

damage;

 the energy consumption of the network.

Performances information can be extracted from

simulations, studying the trend of the number of

packets received by the sink, and dividing it by the

number of nodes remaining active during the

network’s life.

The performance index η

is defined as:

= N

/ S – D

where N

is the number of packets received by the

sink, S is the number of initial node and D is the

number of dead nodes after a fixed time.

Higher values show energy inefficiency (due to

more transmission toward sink) and more reliability,

while lower value show a greater number of death

nodes but less energy consumption.

The abscissa represents the temporal evolution; it

is expressed in epochs and each epoch corresponds at

2 months of network working.

The ordinate axis represents the performance η

value. Figure 10 shows the average of about 50

simulation cycles, considering about 108 nodes.

Figure 10: Comparison between standard and modified

MPRR for a network of 100 nodes.

The comparison between the standard MPRR and

the modified MPRR is well highlighted; in the first

epoch, standard and Modified MPRR are both

inefficient, with a very large packet redundancy and

a very high consumption. In fact, each node transmits

its package toward sink through more than one path

(one level has more nodes), so the sink receives

duplicated information that will be managed by the

sink itself.

From the second Epoch, nodes start to switch off

for damages or low batteries, and in the MPRR, the

nodes nearest to the sink switch off before than the

nodes that are more distant because of the great

number of packets.

They do not switch off at the same time, thanks to

the network configuration, so at least one node

remains alive to send message to sink: on the long

time, the number of packets received by the sink

decreases. The standard MPRR, for this scenario,

provides a not completely correct configuration, so

the nodes nearest the sink shutdown faster than the

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PRESTACTIONALINDEX

EPOCHNUMBER

MPRRcomparison‐

100nodes

MPRR mMPRR

WSN4PA 2021 - Special Session on Wireless Sensor Networks for Precise Agriculture

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modified MPRR. After 8 epochs, the network based

on standard MPRR is dead, while the network based

on the Modified MPRR is still alive. On the long

period, the modified MPRR seems to be the first

choice to guarantee the best compromise between

energy saving and robustness of network. This

situation is confirmed incrementing the number of

node. Figure 11 shows the average of about 50

simulation cycles for about 200 nodes; it confirms the

modified MPRR robustness on the long time for a

wide network, while a WSN using standard MPRR

shut down earlier.

Figure 11: Comparison between standard and modified

MPRR for a network of 200 nodes.

7 CONCLUSIONS

In order to correctly design a WSN, it is important to

study various parameters, including how the nodes

communicate with each other and with the sink.

During the evaluation of the best routing algorithm

for our agricultural scenario, we identified some

critical issues in the use of the MPRR standard.

Therefore, we tried to understand if it was

possible to modify the MPRR so that it could be used

effectively in an agricultural scenario. Some changes

have been made to the routing algorithm, bringing a

clear improvement in its performance.

Through Castalia, a free tool for studying WSN

routing protocols, we evaluated the comparison

between the standard MPRR and its modified version

to exceed the MPRR limits due to the characteristics

of agricultural scenario.

Compared with the standard MPRR, the modified

MPRR provides two signal for configuring the

network, a first signal makes the network configured

in the standard way, while the second signal

reconfigures the wrong nodes to improve the routing

paths between nodes and sink.

In order to reduce the possibility of interferences

and loss of information, even a little delay during

transmission has been adopted.

Performances of the modified MPPR have been

evaluated, evidencing the better life span, despite a

bad initial performance.

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