Reliability Comparison of Routing Protocols for WSNs in Wide

Agriculture Scenarios by Means of η

Index

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, AODV, LEACH, PEGASIS, MPRR.

Abstract: A comparison between the most suitable routing protocols for WSNs applied in wide agriculture scenarios is

shown. The protocols, already present in literature, have been conceived to better manage the power budget

of the nodes and are particularly suitable to cover the energy issues that wide agriculture scenario can request.

This study aims to indicate which of the protocols eligible for this scenario is the most suitable. Comparative

simulation test will be shown.

1 INTRODUCTION

Although an ultimate definition has not provided yet

by the scientific community, the term Wireless

Sensor Network (WSN) is typically referred to a

network of spatially dispersed devices, even called

nodes, for the sensing of the around environment and

able to transfer the acquired data by means of wireless

communications (Shi & Perrig, 2004; Akyildiz et al.,

2002). Typically, the nodes should be characterized

by a low level of complexity, low dimensions and

their power consumption should be low (Leccese et

al., 2014; Leccese et al., 2017). Obviously, these

characteristics, so as the overall price of the nodes,

depend from the final use. Therefore, aims in which

high reliability and/or high power consumptions is

needed are generally more complex and expensive

than to nodes used in less challenging contexts (Iqbal

et al., 2017; Abruzzese et al., 2009; Ming et al. 2009;

D'Amato et al., 2012; Abruzzese et al., 2009; Pasquali

et al. 2016; Pasquali et al. 2017). From a

communication point of view, the nodes often respect

a hierarchical structure in which the lowest level is

composed by nodes that have not a direct access to

the outside. They can transmit data to neighbouring

nodes that route own data and received ones coming

from other nodes to an upper level node enabled to

transfer outside the data. This last node is called “sink

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

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

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

or gateway”. The ways to route the data and the way

to decide who will cover and how long depend by the

routing protocol implemented by the network.

Therefore, data locally acquired and gathered are

usually related to the sink by a routing based on

multiple hops that involve many nodes placed

between the farthest with respect to the sink. The sink,

making available the data to the outside, allows to

other clients to receive the information collected by

the local WSN. Fig. 1 shows an idea of a WSN

topology.

Figure 1: Typical architecture of a WSN.

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

Reliability Comparison of Routing Protocols for WSNs in Wide Agriculture Scenarios by Means of L Index.

DOI: 10.5220/0009365401690176

In Proceedings of the 9th International Conference on Sensor Networks (SENSORNETS 2020), pages 169-176

ISBN: 978-989-758-403-9; ISSN: 2184-4380

169

The parameters on which working to design a

WSN are many and are linked to the scenario in which

it will be apply. In fact, as example, a WSN for a

smart city could not have electrical energy problems

because placed closed to the mains while, for an

application in open field far from the mains, the

procurement of power might be critical pushing the

designers to adopt all the possible solutions and

strategies to limit the power consumption.

Whithin of the design parameters, there are some

more evident, as the capacity of the batteries, and

other more complicated for which a deeper analysis

is necessary, as the routing protocols. In fact, the

energetic autonomy offered by a battery to a node is

directly proportional to its energy capacity. Instead,

for routing protocols that have different strategies to

route the data, it is more complicated to foresee their

impact on the power consumption of the nodes of the

WSNs. This is even more correct as some of them can

automatically change their setting during the time

(Al-Karaki & Kamal, 2004; Leccese et al., 2017).

In this paper, we are going to focus our attention

on the routing protocols trying to compare the

performance of existent protocols to find the more

suitable ones for an agricultural scenario in terms of

efficiency of the WSN. After a description of the

scenario in which we imagine to work, a description

of the routing protocols eligibile for this scenario will

be provided. At the end, a comparison between them

will be obtained by means of a suitable simulator.

2 OPERATIVE SCENARIO

The parameters involved in the definition of a WSN

are many, therefore, its designing is strongly

dependent by the scenario in which it is going to work

(Lamonaca et al., 2017; Gallucci et al., 2017; Morello

et al., 2010; D’Alvia et al., 2017; Islam et al., 2012;

Shen et al., 2001; Vicentini et al., 2014; Pecora et al.,

2019; Polese et al., 2019). For this reason, before any

consideration on the WSN, it is necessary to descript

the operative scenario. In our case, we considered a

wide agricultural site (WAS). We define a WAS as a

land of at least one hectare, in which there some kind

of crop. In order to simplify the geometry, but taking

nothing away from the generality of possible cases,

we imagine the soil flat and squared. Within of the

land, we decide to place a cert number of sensors that

depends by the needs. Fig. 2 gives an idea of the

placing of the sensors. The nodes (red circles) are

placed in the centres of an ideal grid made of internal

squares with a side of 15 m, therefore we could have

36 nodes for hectare, but this number is absolutely

aleatory and is fixed only to define a possible

operative scenario necessary for the further analysis.

Imaging that the land is far from farm, the nodes have

not the possibility to receive electrical energy from

the mains and have to be supplied by local sources as

batteries.

Figure 2: Possible operative scenario in which 36 nodes are

placed in a hectare of an agricultural land.

The use of other local electrical energy sources as

renewable ones, e.g. photovoltaic panels, is not

considered since the idea is to make as efficient as

possible the WSN. This leads a deep analysis of the

routing protocols because in order to increase as

much as possible the efficiency, the power

consumption of the WSN must be as low as possible.

Between the nodes placed in the land, we decided to

put the gateway in the centre of the WSN.

3 ROUTING PROTOCOLS

After the definition of a possible operative scenario,

which revealed the problem of power consumption

and so the need to make the network as efficient as

possible, a description of the routing protocols that in

literature are pointed out as the most suitable for this

kind of scenario is necessary. Between the routing

protocols present in literature four of them seem

suitable for our scenario: Ad hoc On Demand

Distance Vector routing protocol or AODV (Maurya

et al., 2012), Low-Energy Adaptive Clustering

Hierarchy or LEACH (Shekar, 2012), Power-

Efficient GAthering in Sensor Information Systems

or PEGASIS (Lindsey, 2013) and Multipath Ring

Routing or MPRR (Pandya & Mehta, 2012).

WSN4PA 2020 - Special Session on Wireless Sensor Networks for Precise Agriculture

170

3.1 AODV

The Ad-hoc On-Demand Distance Vector (AODV) is

a reactive protocol principally conceived for ad hoc

mobile networks and is able to set both unicast and

multicast routing. It builds routes between nodes only

as desired by source nodes (in this sense, it is an on

demand algorithm) maintaining they active until is

requested by the source nodes. All the routing

information are uploaded in a routing table driven,

and so updated, by the demand reducing the typical

problem of the proactive routing protocols which try

to up to date all the time the routing tables engaging

many computational resources.

For destination, AODV uses sequence numbers

that avoid routing loops so preventing problems such

as the "counting to infinity" more typical for more

classical distance vector protocols.

Other advantages are the quick adaptation to

dynamic link evolutions, a low overhead of

processing and memory, it has the ability to find

unicast routes to destinations within the ad hoc

network, self-starting and scales to large numbers of

mobile nodes.

Unfortunately, this protocol presents problems in

case of managing of network congestion where an

overloading of nodes is typical. This makes slower

the transmission speed of the network but, even more

important from our point of view, the nodes should be

energetically weaker.

3.2 LEACH

Low Energy Adaptive Clustering Hierarchy

(LEACH) is conceived for hierarchical clustering

WSNs. A cluster is a set of nodes that, in order to

make similar the power consumption, randomly, after

a fixed time, elects a cluster-head (CH) rotating this

role between the nodes within of the cluster. The CHs

collects data coming from the nodes aggregate them

and compress the total amount of information that

will be send to the base station (BS). In MAC layer, a

TDMA/CDMA technique is implemented to reduce

the possible collisions inside the cluster or between

different clusters. The collection of data is centralized

and can be set both periodically or asynchronously

making it suitable to constant monitoring activities.

The set-up of the WSN is performed in two

successive steps called setup phase and steady state.

During the setup, there is the organization of the

clusters which elect the own CHs while, in the second

phase, the data transfer inside the cluster and to the

BS is done. The procedure foresees that during the

setup phase, a small number of nodes elect

themselves as CHs notifying their own role to the

other nodes using a broadcast message. The other

nodes, alerted by this message, on the base of the

signal strength, decide on which cluster they want to

belong informing the appropriate CHs that they are a

member of that cluster. Once established the cluster,

a TDMA schedule is established by the CH node,

which assigns a time slot to each node for the

transmission. This schedule is sent to the other nodes

of the cluster through a broadcast message. During

the steady state phase, the data are transmitted. After

an aforethought time, a new setup phase is launched.

The principal advantage of the LEACH protocol

is the high lifetime of the network. On the contrary, it

assumes that all nodes have enough power to transmit

to reach the BS and that each node has been designed

to work with different MAC protocols. Therefore, if

the network is not properly designed, its application

for networks deployed in large regions could be

critical. Another disadvantage is the fact that it is not

ensured that the CHs are uniformly distributed in the

network having the possibility that the CHs can be

concentrated only in a part of the network. This

implies that some nodes may not be close to CHs.

Another disadvantage is that the dynamic clustering

leads further overhead caused by head changes,

advertisements etc., which drains the available

energy. Moreover, the protocol supposes that, at the

beginning, all nodes have the same quantity of energy

in each round, wrongly assuming that each CH

consumes a similar quantity of energy.

3.3 PEGASIS

Power-Efficient GAthering in Sensor Information

Systems can be considered as an optimization of the

LEACH algorithm. It does not group nodes in clusters

but forms chains of sensor nodes. With this

architecture, each node talks only with the closest

neighbors receiving and transmitting data only from

the previous ring and with successive ring of the

chain. In this way, the nodes can adjust the power of

their transmissions. Even in this case, the single node

performs the aggregation of data coming from the

previous with own and forwarding the new set to the

next node of the chain up to the BS. Each round,

foresees that one node of the chain is elected to

communicate with the BS and the chain is built

according to a greedy algorithm. The final packet that

will be sent out of the WSN is made with the data

collected from all nodes so realizing a “data fusion.”

This texture has the great advantage to reduce the

overall amount of the data transmitted to the BS

because reduces the number of ancillary data that

Reliability Comparison of Routing Protocols for WSNs in Wide Agriculture Scenarios by Means of L Index

171

forms, together with the measured information, the

data packet coming from a single sensor.

With respect to the LEACH, the main

advantageous of the Pegasis is the lower transmission

distance between the nodes, moreover, since the

nodes are selected for only the time of the

transmission round, the power dissipation during the

time is balanced between the nodes. On the contrary,

PEGASIS presents many disadvantages:

 requests that the CHs have to be located near the

BS;

 since the energy of the CH at the beginning is

unknown, there is the risk that the nodes could

discharge during a transmission losing all the data

coming from the whole WSN;

 the presence of an only CH could be a bottleneck

for the network causing delays;

 the lack of redundancy increase the risk of lost;

 if the packets have a low number of bits, the

energy efficiency is low.

3.4 MPRR

In order to make data collection robust against

communication failures, multipath routing

architectures allow setting up multiple propagation

paths between each sensor node and the base station.

In this way, data collected by a node are successfully

sent to the base station as long as any one of its

propagation paths is failure-free (Huang et al., 2013).

In MPRR, nodes do not have a specific parent and

the construction phase organizes the network into

levels, even called rings, according to hop distance

from the sink node to a sensor node. This means that,

at the end of the build phase, each node will have a

number that indicates how many hops is far from the

sink node and this number corresponds to the level or

ring of belonging.

At the beginning of the construction phase, the BS

sends a broadcast setup packet indicating the ring

number 0. The nodes that receive this topology setup

packet will increment it 1 (nodes belonging to ring 1)

and rebroadcast it. This process continues until all

nodes will have a ring number. After topology setup

phase is completed, when a node needs to send data

to the gateway, the node sends a broadcasts message

endowed of its ring number. Any node having a

smaller ring number will receive that packet and

rebroadcasts it. The process continues until the packet

reaches to sink. In this sense, MPRR is a proactive

routing protocol in which the network initialization is

performed prior to the data dissemination, all nodes

are distributed randomly in the field under analysis,

the base station is responsible for gathering data from

the whole network, moreover, route discovery is also

not required before data transmission.

Because of its own architecture, MPRR is natively

reliable in the transmission data; in fact, the

possibility to set more paths to reach the sink ensures

that the data sent by the generic sensor node has more

possibility to reach the gateway respect to a less

complex topology. On the contrary, the major

disadvantage is the overall overhead of the WSN that

drains inefficiently energy from the nodes.

4 CASTALIA SIMULATOR

In order to study the most suitable routing protocol

for the described agricultural scenario, we used a

WSN simulator able to implement low-power

embedded devices: its name is Castalia. We chose this

simulator since it is “open source.” This allows

studying the algorithm following step by step what

happens during the simulations verifying the

compliance of the software with the theory and allows

introducing check points to avoid problems as infinite

loops, etc. At the same time, it allows modifying

already defined algorithms, and, even more

important, allows implementing, developing and

validating new algorithms (Boulis, 2019). Anyway,

in order to find the best protocols, we decided to not

change the already algorithms testing the original

version of the protocols implemented in the

simulator.

5 TEST AND RESULTS

A comparison between different routing protocols

can be scientifically insignificant because each

protocol has been conceived to exalt some

characteristics with respect to the others. For instance,

AODV has been conceived for mobile networks and

surely will better fit to the exigencies of those nets

instead of static architectures. This leads that the test

are typically focused on a single aspect (resilience,

energy consumption, transmission speed, etc.)

analysing how and how much a specific protocol is

better than the other for that specific aspect. Although

this approach is overall reasonable because there is

not a perfect WSN for all possible scenario, in order

to try a more suitable and objective index for our test,

we used a performance index that takes into account

both the energy aspects and the reliability of data

transmission.

WSN4PA 2020 - Special Session on Wireless Sensor Networks for Precise Agriculture

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5.1 Performance Index

The index, called η

, is defined as the number of

packets received by the sink after a fixed time divided

for the difference between the initial nodes and those

that during the activity are switched off.

(1)

where:

: performance index

p: number of packet received by the sink after a

fixed time.

S: number of initial nodes (they are initially active.)

D: number of dead nodes after a fixed time.

For dead nodes, we mean even those unable to

communicate with the gateway. The index gives an

indication of how much efficient the network is in the

delivery of the information considering both the

number of packets that are running in the network and

that arrive to the sink and the number of nodes that

fail over the time. This fail could be linked to the

energy lack caused by the stress that some nodes

could suffer due to the strategy adopted by the routing

protocols. The index is built to have values lower,

higher or equal the unit value that represents the ideal

performance of the network in which the number of

the received packets is equal to the number of alive

nodes. This condition is certainly achieved by

protocols that do not provide redundancy in the

transmission of data and at a time (necessarily initial)

in which all the nodes are "alive". Numbers different

by the unit mean inefficiency: higher values indicate

that there is plenty of packets; lower values indicate

fewer packets than the number of live nodes.

5.2 Test, Results and Discussion

To perform the test, it has been assumed that each

sensor node is powered by on board battery (Caciotta

et al., 2013; Leccese, 2007). Additionally the battery

cannot be replaced or recharged, therefore the battery

discharge leads the failure of the node and determines

the lifetime of the WSNs. Considering the supposed

scenario of Fig. 2, it is assumed that one of the node

will perform the role of gateway. Moreover, the

quantity of data transmitted toward the gateway from

each node is equal for each routing protocol. It is clear

that in each epoch, depending on the specific

protocol, a certain percentage of nodes fail. Fig. 3

shows the average of 100 simulations obtained by

Castalia for a network composed of 100 nodes.

Consequently, the dimension of the hypothetical area

analyzed with the simulation is bigger than one

hectare. The numbers on the abscissas of the graphs

(from 1 to 8) indicate the evolution of the time

expressed in epochs (in real cases an epoch could be

equal to 2 months).

As it is possible to see, in the first epoch, the first

three protocols are similar showing optimal results,

while the MPRR shows high inefficiency cause the

redundancy of the packets that are running in the

network. High inefficiency does not mean that the

packets do not arrive to the sink, but simply that the

number of packets is redundant and so a high-energy

consumption without a real necessity happens.

After the first epoch, the first three protocols lose

efficiency, while the MPRR recovers efficiency even

if the improvement is strongly limited for the second

and for the third epoch.

Figure 3: Service performance index with respect to the

protocol: number of packets arrived at the SINK divided by

the difference between the number of initial nodes and

those switched off. Simulation obtained with CASTALIA

for a network of 100 nodes. The values are the average of

100 simulations; each simulation needs about 40 minutes to

be performed for a total simulation time of about 100 hours.

Between the first three protocols, the networks

managed by LEACH is surely weaker if compared

with PEGASIS and AODV. This can be explained

with the distribution of the dead nodes that is linked

to the protocol: in fact, in the LEACH, the CHs are

more stressed with respect to the other nodes even if

they are normally a limited number. Moreover, the

probability to select the CHs is higher for the nodes

nearer to the sink. The better performance of the

PEGASIS with respect the LEACH is due to the fact

that it is an improved version of this last, while the

good behavior of the AODV could be due to the

particular scenario. The behavior of the MPRR needs

some explanations. Considering how its routing

protocol works, it is highly inefficient at the

Reliability Comparison of Routing Protocols for WSNs in Wide Agriculture Scenarios by Means of L Index

173

beginning even if, in the first epochs, it ensures the

highest reliability of the network because all the

packets find a route to arrive to the sink. Always

considering its way to work, the nodes in the lower

levels are energetically more stressed than those

belonging to the upper levels and far from the

gateway. This leads an early death of the nodes

belonging to lower levels with respect to the other

routing protocols and this prevents to the nodes of the

higher levels to communicate with the gateway.

Therefore, even if many nodes of the higher rings are

still alive, they cannot communicate with the gateway

and so are considered died. This justifies its behavior

highly reliable at the beginning but that early

becomes unsuitable. In fact, after the fourth epochs,

the number of dead nodes belonging to the lower

rings is such as to prevent an acceptable transfer of

information. The simulations were performed on an

ASUS Notebook, with an Intel Core Pentium i7-

3630QM CPU @ 2.40 GHz and memory RAM of 8

GB. Each simulation took 40 minutes.

In order to validate our test we repeated the it with

a bigger number of nodes. The second test used 200

nodes and each simulation needs about 100 minutes

to be performed and a total simulation time of about

6 days. 300 nodes composed the third network and the

simulation needs about 360 minutes. In this case, we

performed only 50 simulations for a time of about

12,5 days. The results are shown in figures 4 and 5.

Figure 4: Service performance index with respect to the

protocol. Simulation obtained with CASTALIA for a

network of 200 nodes. The values are the average of 100

simulations; each simulation needs about 100 minutes to be

performed for a total simulation time of about 6 days.

As it is possible to see, even in these cases, the

graphs show that we have similar answers for similar

protocols (LEACH and PEGASIS) with PEGASIS

better than LEACH, while different architectures

(MPRR) suggest high reliability of the transmission

only for a short time. Anyway, even if the differences

between PEGASIS and AODV are not high, the

simulations identify in the AODV routing protocol a

good competitor for PEGASIS resulting both the

more suitable routing protocols for this scenario. This

leads that, if you have the possibility to change the

batteries of the nodes of if you have the possibility to

provide a safe and continuous energy source for the

nodes as the photovoltaic one, the better routing

protocols is surely the MPRR. If these possibilities

are not sure, a PEGASIS or an AODV could be the

better strategies for the WSN in this kind of scenario.

Figure 5: Service performance index with respect to the

protocol. Simulation obtained with CASTALIA for a

network of 300 nodes. The values are the average of 50

simulations; each simulation needs about 360 minutes to be

performed for a total simulation time of about 12.5 days.

6 CONCLUSIONS

In order to find a routing algorithm that can better fit

the exigencies of a wide agricultural scenario, a

comparison between the most suitable protocols

present in literature has been done by the use of a

particular performance index that points out how

many the network is reliable during the time. The

simulations have been realized with a scenario that

foresees an equally space spaced nodes in a flat land

with the gateway placed in the centre of the WSN,

with the nodes that start with the same amount of

energy and that send the same quantity of

information. This last choice is linked to the idea of

realizing the objective of the document without

possible facilitations. The simulations find that the

MPRR, although highly inefficient under the

energetic profile, ensures the deliverable of the

WSN4PA 2020 - Special Session on Wireless Sensor Networks for Precise Agriculture

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information during the first epochs showing itself as

the most reliable but only for a limited time.

PEGASIS, being an improvement version of the

LEACH, shows a performance better of this last,

while, paradoxically, the simulations identify in the

AODV protocol, conceived for mobile networks, a

valid competitor of the PEGASIS. This result can be

due both to the particular scenario and to the energy

requests of the other routing protocols.

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