Evaluating feasibility of using wireless sensor networks in a coffee crop through simulation of aodv, aomdv, dsdv and their variants with 802.15.4 mac protocol

International Journal of Computer Networks & Communications (IJCNC) Vol.6, No.6, November 2014
EVALUATING FEASIBILITY OF USING WIRELESS
SENSOR NETWORKS IN A COFFEE CROP THROUGH
SIMULATION OF AODV, AOMDV, DSDV AND THEIR
VARIANTS WITH 802.15.4 MAC PROTOCOL
Ederval Pablo Ferreira da Cruz1, Luis Eduardo Gottardo1, Franciele Pereira
Rossini1, Vinicius de Souza Oliveira1 and Lucas Cellim Pereira1
1Federal Institute of Espirito Santo (IFES) – Campus Itapina, Colatina-ES, Brazil
ABSTRACT
A Wireless Sensor Networks is a network formed with sensors that have characteristics to sensor an area to
extract a specific metric, depending of the application. We would like to analyse the feasibility to use
sensors in a coffee crop. In this work we are evaluating routing protocols using real dimensions and
characteristics of a coffee crop. We evaluate, through simulation, AODV, DSDV and AOMDV and two
variants known in this work as AODVMOD and AOMDVMOD with 802.15.4 MAC Protocol. For this
comparison, we defined three performance metrics: Packet Delivery Ratio (PDR), End-to-End Delay and
Average Energy Consumption. Simulation results show that AOMDVMOD overall, outperforms others
routing protocols evaluated, showing that is possible to use WSN in a real coffee crop environment.
KEYWORDS
DSDV, 802.15.4, AODV, AOMDV, Coffee Crop, WSN, Wireless Sensor Networks & Routing Protocols
1. INTRODUCTION
In the last years several technologies emerged with the objective to assist human being. One of
these emerging technologies is known as Wireless Sensor Networks (WSN). The use of new
"smart" wireless equipments to sensing and to communicate with each other open new
perspectives. In this kind of network, sensors can sensing, measure and gather information from
the environment, consequently sending such data to the user.
Wireless sensor networks is an area that several research groups around the world have
concentrated their efforts to solve problems in all communication layers, including physical-layer
communication up to the development of new applications. Wireless sensor networks consist of
many smart sensor nodes, where these sensors are equipped with one or more sensors, a
processor, memory, a power supply and a radio wireless channel to communicate with each other
[1].
Wireless sensor networks can be considered as a special type of Ad Hoc Networks. They can be
static, where the nodes do not have any movement, or mobile, known also in the literature as
Mobile Ad Hoc Networks (MANET). Ad Hoc Networks is different from infrastructure networks,
where such architecture has a base station coordinating the communication of the nodes. Usually,
wireless sensor networks has not centralized control and predefined communication link,
transferring signals to the exterior world. All nodes are capable to act as source or sink node at the
DOI : 10.5121/ijcnc.2014.6602 15

same time. One of the drawbacks of the wireless sensor networks is due to the fact of the nodes
have limited processing power because of their tiny physical size, which limits the capacity of
processor and size of battery. When collectively works together, they have an ability to collect
information of the physical environment. In the Figure 1 is showed an example of a MANET with
infrastructure and infrastructureless or pure ad-hoc manner [2].
One of the main challenges to be solved in Wireless sensor networks is routing data of the source
node up to destiny node. Several factors can influence the design of the routing protocols such as:
Node Deployment, Power Consumption, Data Delivery Models, Node/link Heterogeneity,
Fault Tolerance, Scalability, Network Dynamics, Transmission Media, Connectivity,
Operating Environment, Data Aggregation/Fusion, Quality of Service (QoS), Production
Costs, Data Latency and Overhead and Autonomy. Hence, is possible to see that routing
protocols are needed to cope with the nature of wireless sensor networks and that proper routing
in ad-hoc networks is the challenge to the designers [3, 4].
16
Figure 1. MANET with infrastructure (left side) and infrastructureless (right side) [2]
This work objective to evaluate the feasibility of using Wireless Sensor Networks in a coffee crop
through simulations using three classics routing protocols for ad hoc networks and two little
variants:
· Proactive routing protocol named DSDV (Destination-Sequenced Distance-Vector
Routing Algorithm) [5];
· Reactive routing protocol knows as AODV (Ad Hoc On-Demand Distance Vector
Routing) [6]
· Routing protocol based in multiple paths called as AOMDV (Ad hoc On-demand
Multipath Distance Vector Routing) [7];
· A modification of AOMDV protocol called in this work as AOMDVMOD. The
modification consists to increase HELLO messages dissemination interval to 5 seconds.
Default value used by the protocol is 1 second;
· AODV named AODVMOD. The modification consists to increase HELLO messages
dissemination interval to 5 seconds. Default value used by the protocol is 1 second.
Furthermore, these routing protocols are simulated using IEEE 802.15.4 as the underlying MAC
layer. So, the main contributions of this paper is: (1) evaluate routing protocols for ad hoc
networks using realistic dimensions used in a coffee crop and (2) sensors located in the scenarios
evaluated considering characteristics used in a real coffee crop such as spacing between coffee
seeds.
The remaining of the paper is organized as follows: In the Section 2 is described about the routing
protocols used in this work. Section 3 shows the related works. Section 4 describes about the

performance evaluation describing scenarios, communications patterns, metrics and more. In the
Section 5 the results are analysed and discussed and the paper in concluded in the Section 6.
2. ROUTING PROTOCOLS BACKGROUND
The ad hoc networks routing protocols have as main objective to find better route between a
source-destiny node by the information existing in the routing tables of the nodes. In the WSN,
the movement of the nodes is not a challenging considering the type of application to deploy, and,
commonly, when movement is used, the nodes have lower speed than other kind of ad hoc
networks (e.g. VANETs). One of the major restrictions to be considered in the WSN is the battery
of the nodes. Sensor nodes have limited available power. So, energy efficient routing protocols
are truly crucial for life of WSN. But energy consumption is not the only factor to be analysed.
Considering that in a real environment, such as coffee crop (our objective to deployment WSN),
user needs information more fast possible (low delay) and with reliability (high packet delivery
rate). So, is possible to see that other metrics are very important as well.
Routing protocols in WSN can be classified depending of the characteristics such as [3]:
17
· Route Establishment
· Network Structure
· Protocol Operation
· Initiator of Communicator
The Figure 2 gives and overview of the routing taxonomy.
WSN Routing Protocol
Network
Structure
Protocol
Operation
Initiator of
Communicator
Flat
Hierarchical
Location
Negotiation
Query
Multipath
QoS
Coherent
Figure 2. Taxonomy of Wireless Routing Protocol
Route
Establishment
Proactive
Reactive
Hybrid
Source
Initiator
Destination
Initiator
Considering our work, we will focus in the Route Establishment classification. More details about
the protocols evaluated inserted in such classification will be describe later.

2.1 ROUTE ESTABLISHMENT BASED ROUTING PROTOCOL CLASSIFICATION
Different strategies can be used to route packets among source-destiny node in the network.
Routing protocols must be developed aiming maximize lifetime network with low delay and high
packet delivery ratio. Basically, three different route establishment strategies can be used:
· Proactive or Table-Driven Routing: In this approach when the routing protocol begins
to work, nodes try to populate its routing tables with possible destination nodes. This kind
of network is not suitable for larger networks, as they need to maintain node entries for
each and every node in the routing table. This leads to more overhead in the routing table
leading to consumption of more bandwidth Classic examples of routing protocols
categorized as proactive or table-driven routing are: OLSR [8] and DSDV.
· Reactive or On-Demand Routing: This type of routing protocols construct routes only
when is necessary to send information. In a situation where a node wants to communicate
to another node this kind of protocol searches for the route in an on-demand manner and
establishes the connection in order to transmit and receive the packet. A technique usually
used by reactive routing protocols to route discovery is using flooding route request
packets throughout the network. We can cite as routing protocols in this category:
AODV, DSR [9].
· Hybrid Routing: In this case routing protocols use both reactive and proactive
mechanisms to fill routing tables (create or update new routes). Examples of hybrid
routing protocols are: ZRP [10]
18
2.1.1 DESTINATION SEQUENCE DISTANCE VECTOR (DSDV)
Each node in the network maintains a routing table for the transmission of the packets. Each node
has a list of possible destinations in the network and the number of hops necessary to reach each
destination in the routing table. With the objective to maintain the information in the routing
tables always updated each station transmits a HELLO message in a broadcast manner
periodically. Each new route will contain the following information as showed in Table 1.
Table 1: Fields of Routing Table using DSDV [11]
DESTINATION NEXT HOP HOPS/METRIC SEQ. NO. INSTALL
TIME
STABLE
DATA
The newest route is used (identified with the highest sequence number). With this information is
possible to identify the old routes from the new ones, thereby avoiding the formation of loops.
2.1.2 AD-HOC ON-DEMAND DISTANCE VECTOR (AODV)
AODV (Ad-hoc On-demand Distance Vector) is a loop-free routing protocol for ad-hoc networks
based on vector distance algorithm, as DSDV. It is designed to be self-starting in an environment
of mobile nodes, withstanding a variety of network behaviours such as node mobility, link
failures and packet losses.
The AODV protocol is based in topology information that works in a reactive mode. In other
words, when a source node wants to send data to a destination node, a route discovery process is

started. In this process, the source node broadcasts a ROUTE REQUEST (RREQ) packet to all
your neighbours. Neighbours nodes which do not know an active route to destination node,
forward the packet to their neighbors until an available route is found or the maximum number of
hops is reached. When an intermediate node knows an active route to the requested destination
node, it sends back a ROUTE REPLY (RREP) packet to the source node in unicast mode,
enabling to the node creates the route among the source and destination nodes. In case of a link
failure, the neighbourhood nodes are notified by route error messages (RERR) on both sides of
link.
2.1.3 AD-HOC ON-DEMANDMULTIPATH DISTANCE VECTOR (AOMDV)
The main characteristic in AOMDV is computing multiple loop-free paths per route discovery.
Due to fact to create multiple redundant paths, the protocol switches routes to a different path
when an earlier path fails. Thus a new route discovery is avoided. Route discovery process is
initiated only when all paths to a node destination fail. For efficiency, only link disjoint paths are
computed so that the paths fail independently of each other. Note that link disjoint paths are
sufficient for our purpose, as we use multipath routing for reducing routing overheads rather than
for load balancing. The multi-path routing protocol discovers multiple paths during the single
route discovery process. These multiple paths can be used for load spreading or as backup routes
when the primary route fails [12].
Different of AODV routing protocol, AOMDV do not discard duplicate RREQs. AOMDV look
for an opportunity of getting an alternate route with each duplicate RREQ. In AOMDV, RREQ
propagation from the source towards the destination establishes multiple reverse paths both at
intermediate nodes as well as the destination. Multiple RREPs traverse these reverse paths back,
to form multiple forward paths to the destination at the source and intermediate nodes. AOMDV
also provides intermediate nodes with alternate paths as they are found to be useful in reducing
route discovery frequency. The core of the AOMDV protocol lies in ensuring that multiple paths
discovered are loop free and disjoint; and in efficiently finding such paths using a flood-based
route discovery. AOMDV route update rules, applied locally at each node, play a key role in
maintaining loop-freedom and disjoint-ness properties [13].
3. RELATEDWORKS
This section presents a brief summary of related works. Chicka et al [14] evaluates AODV and
DSR routing protocols for IEEE 802.15.4/ZigBee. The authors aim to analyse, specially, the
energy consumption. But the scenario studied in the work does not consider any specific
application.
In [15] is realized an evaluation of the network performance of a WSN for Temperature
Monitoring in Vineyards. The authors deployed real equipments (called motes), in real city. But
in the work the authors do not describe what routing protocol was used in the experiments.
In [16] Santos et al., give an brief overview about feasibility of using WSN in agricultural
monitoring where they show that is possible to use WSN with low cost and increasing
productivity.
In the work [17] Verona realizes a simulation of a WSN with the objective to use WSN in
vineyards with hierarchical or flat approach.
Oliveira et al [18] present in their paper a Quality of Service (QoS) analysis of four Routing
Protocols in WSN based on the IEEE 802.15.4 standard in the Monitoring of Wind Farms. They
19

claim that the rising global demand of energy and the scarcity of fossil fuels can be factors that
justify to use renewable energies sources in the world, such as wind power.
4. PERFORMANCE EVALUATION
This section presents the evaluation of the AODV, AODVMOD, AOMDV, AOMDVMOD and
DSDV routing protocols under 802.15.4 MAC protocol in a scenario that aiming to represent a
coffee crop scenario. We adopted 802.15.4 because this MAC protocol has some characteristics
such as low transmission rate and consumed energy when compared with 802.11, and the devices
that use 802.15.4 as MAC protocol are cheaper. This shows that in our case, aiming to use sensors
in a coffee crop, 802.15.4 is more viable to adopt than 802.11. In the Figure 3 is showed (in the
selected area) the dimensions of the real area deployed in the simulator. In the Table 2 is showed
the coordinated points extracted from Google Earth of the scenarios used in our simulations.
20
Table 2: Coordinated points of the area used in the simulations
Latitude Longitude
A 19°29’48.16”S 40°45’32.54”W
B 19°29’46.86”S 40°45’31.95”W
C 19°29’48.34”S 40°45’25.16”W
D 19°29’49.62”S 40°45’25.75”W
To realize the simulations, NS-2 simulator [19] was adopted to evaluate behaviour of the wireless
sensor networks deployed in this work. NS-2 is a discrete event simulator developed by the VINT
project research group at the University of California at Berkeley. There are some interesting
characteristics such as: (a) node mobility, (b) a realistic physical layer with a radio propagation
model and more.
We consider 3 different scenarios, where the number of sensors varies as follows:
· Scenario 1: 40 nodes + 1 sink node
Figure 3. Selected area deployed in the NS2 simulator extracted from Google Earth.

It is important to mention that the sink node (represented in the Figures 4, 5 and 6 by the white
circle) is located in the center of the scenario evaluated. To give more details about the
arrangement of the nodes in the scenarios evaluated, are presented scenarios 1, 2 and 3 in the
Figures 4, 5 and 6, respectively.
21
Figure 4. Scenario 1 deployed in the NS2 simulator.

22
Table 3 summarizes the parameters used in the employed simulation.
Table 3: Parameters used in the simulation
MAC Protocol 802.15.4
Radio Propagation Model Two Ray Ground
Routing Protocols AODV, AOMDV, AODVMOD,
AOMDVMOD, DSDV
Simulation Time 180 seconds
Number of Nodes
Scenario 1: 40 + 1sink
Scenario 2: 55 + 1 sink
Scenario 3: 70 + 1 sink
Packet Size 512 bytes
Transmission Rate 4 packets/sec
Traffic Type CBR
Initial Energy
Sink Node – 50 kJ
Other nodes – 5 kJ
Transmission Range 60 meters
On Table 4 is showed the relation between the amount of source nodes and connections created
for each scenario. We adopted such characteristic considering that in a real communication is
possible that one source node can create several connections simultaneously (2 or more different
nodes). The number of connections in each scenario is equal to 20% of the total of nodes (except
sink node) of the scenario.
Table 4: Connections and source patterns used in the simulations for each scenario
Amount of connections for each scenario
40 nodes + 1 sink 6 (different sources) and 8 (connections)

It is important to mention that the results presented in this paper are averaged of 30 simulations
for each scenario and for each protocol. All simulations results presented were obtained
guaranteeing a 95% confidence interval.
4.1 PERFORMANCE METRICS
As already showed in the Tables 3 and 4, the performance of the routing protocols AODV,
AOMDV, DSDV, AODVMOD and AOMDVMOD using 802.15.4 MAC protocol was realized
by varying the network density and the amount of connections. The metrics to assess the
performance are given as follows:
23
a) End to End Delay
It can be defined as the average time between packets sent and received by the destiny nodes.
Such metric can be calculated by using the Equation 1:
=
1
( − )
=1
Where N is the number of successfully received packets, i is unique packet identifier, ri is time at
which a packet with unique id i is received, si is time at which a packet with unique id I is sent
and D is measured in ms. [20, 21].
b) Packet Delivery Ratio (PDR)
Such metric can be defined as the percentage of the data packets delivered to the destinations to
those generated by the sources. In Equation 2 is showed how such metric can be defined:
=
1
=1
Where P is the fraction of successfully delivered packets, c is the total number of flow or
connections, f is the unique flow id serving as index, Rf is the count of packet received from f and
Nf is the count of packets transmitted to f [20, 21].
c) Averaged energy consumption
Such metric is important to be evaluated due to the fact of the WSN nodes have limited lifetime
due to use batteries.
Considering E be the initial energy of a node and residual energy Eres of a node at time t, can be
calculated by using the Equation 3 [22]:
Eres = E - Econ(t)
Where Eres is the residual energy; Econ is the consumed energy. Total energy consumption of all
nodes is measured, as presented in Equation 4 as the summation of all node’s residual energy plus
the product of initial energy and number of nodes [22]:
TEcon= N * Initial Energy – Eres
(1)
(2)
(3)
(4)

24
Where TEcon is the total consumed energy; N is the total number of nodes used in the scenario.
5. RESULTS AND ANALYSIS
To discuss more about the results obtained in the simulations, they are showed in the Figures as
follows.
In the Figure 6 is presented the results about Packet Delivery Ratio (PDR). AOMDV and
AOMDVMOD protocols overcome other protocols due to fact to have multiple paths among
source node and destiny node. When a path is lost, another path already established can be used to
deliver packets. It is possible to see that the modification made in the HELLO messages interval
of the protocol AOMDV, resulting in the protocol AOMDVMOD, impacted directly in the results
in all scenarios evaluated, where in the scenario 1 is possible to see a performance about 25%
higher of AOMDVMOD when compared with AOMDV due to the fact of the reduction of the
HELLO messages, number of packet’s collision and drop packets are reduced as well.
DSDV proactive protocol, needs to maintain your routing tables always updated and periodically,
even if nodes do not have packets to send. Due to this reason, DSDV waits for a certain period to
update its routing tables. In this interval of time, if some node wants to send packets, such packets
are put in the queue and when the queue is full, packets will be dropped. That is why the packet
delivery ratio of the DSDV protocol is too low as can be seen in the Figure 6. AODV and
AODVMOD obtain better results than DSDV. The reason of this behaviour is that in case of link
failure, DSDV waits for update packets while AODV broadcasts immediately a route request.
Figure 6. Results of Packet Delivery Ratio (%)
Figure 7 shows a comparison between the routing protocols on the basis of average end-to-end
delay for different nodes number. Higher number of nodes is not necessary higher end-to-end
delay values. Considering that there is no mobility in the nodes in our scenarios evaluated, the
only problem that can increase delay will be battery. But in the simulations we saw that energy
during the simulation time never ends. It is important to mention that DSDV have lower end to
end delay, due to fact to have proactive behaviour and have fresh routes in its routing tables.
AOMDV and AOMDVMOD have the best results with a little win of the AOMDVMOD and
their results are near of the results obtained by DSDV. First, due to the fact to have multiple paths

(“backup paths”) to get destiny node in case of link failure and secondly, due to fact to send less
HELLO messages broadcasts, reducing messages generated in the network avoiding collision and
drop packets. AODV and AODVMOD routing protocols do not have satisfying results when
compared with other protocols evaluated, because when there is a link failure, messages notifying
such failure are necessary to inform the nodes in the network, generating more overhead in the
network, increasing delay.
25
Figure 7. Results of End-to-end delay (in ms.)
Figure 8 shows the results comparing the average energy consumption of the routing protocols
evaluated in this work. AOMDV and AOMDVMOD are the routing protocols that consume more
energy. These protocols try to find multiple paths, using more resources and obviously consuming
more energy. DSDV is the protocol that consumes less energy considering that it fills its routing
tables without use techniques such as broadcast used by AODV and AODVMOD routing
protocols, consuming more energy.
Figure 8. Results of Average Energy Consumption (in kJ.)

In the Table 4 we do a summary of the results, where the performance of the routing protocols are
shown considering a score where 1 is worst result and 5 is the better result, considering the
application aiming by us.
26
Table 4: Result’s summary
Metric/Protocol AOMDV AOMDVMOD AODV AODVMOD DSDV
Packet Delivery Ratio 4 5 3 3 1
Average End-to-end Delay 4 4 2 3 4
Average Energy Consumption 3 3 4 4 4
Total point 11 12 9 10 9
It is possible to see that considering Packet Delivery Ratio (PDR), AOMDVMOD is the best
solution and have good results in other metrics evaluated. DSDV routing protocol has the worst
result in PDR, but in the other metrics has good results. But considering the results obtained by
DSDV protocol in PDR metric, and the application to be deployed, it shows that cannot be viable
to be used. AODV and AODVMOD depending on the type of application, maybe they can be
good routing protocols to be used in the network.
6. CONCLUSIONS
This work presented a study evaluating the feasibility of using Wireless Sensor Networks in a
coffee crop through simulation using dimensions with a real area extracted from Google Earth
and using characteristics of a coffee crop (such as spacing between coffee seeds). The results
presented in this paper motivate the investigation of applicability of WSN in several areas. The
results presented shows that AOMDV, overall, can be a good solution to use in a real deployment
of a WSN.
As future works, the authors will deploy real sensors in the same area used in the simulations to
evaluate the behavior of the routing protocols and to develop an Android software to manage the
WSN deployed in a real environment to help farmers to have information in real-time.
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AUTHORS
Ederval Pablo Ferreira da Cruz received the graduation in Data Processing from the
University Center of Espirito Santo (UNESC), Brazil, in 2001 and the M.Sc degree from
the Federal University of State of Rio de Janeiro (UNIRIO), Brazil, in 2012. Actually, he
is a Ph.D special student at Federal University of Espirito Santo (UFES). He is currently
professor of the Federal Institute of Espirito Santo (IFES) - Campus Itapina. His research
interests include vehicular networks, wireless sensor networks, software-defined
networks, Data Center Networks and Cloud Computing.
Luis Eduardo Gottardo is an undergraduate student at Federal Institute of Espirito Santo
(IFES) - Campus Itapina. Currently, he has interests in precision agriculture using wireless
sensor networks.
Franciele Rossini Pereira is an undergraduate student at the Federal
Institute of Espirito Santo (IFES) – Campus Itapina. Currently she has interests in
Research Development and Extension towards precision agriculture to hang on family
farms.
Vinicius de Souza Oliveira is an undergraduate student at Federal Institute of Espirito
Santo (IFES) - Campus Itapina. Currently, he has interests in precision agriculture using
wireless sensor networks.
Lucas Cellim Pereira, in an undergraduate at Federal Institute of Espírito Santo (IFES) –
Campus Itapina in agronomy college course. Currently, he has interests in mineral
nutrition of plants, fertilization where is developing a software and in the precision
agriculture.

Evaluating feasibility of using wireless sensor networks in a coffee crop through simulation of aodv, aomdv, dsdv and their variants with 802.15.4 mac protocol

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Evaluating feasibility of using wireless sensor networks in a coffee crop through simulation of aodv, aomdv, dsdv and their variants with 802.15.4 mac protocol