SENSOR
DATA RATE ADDIN CSL_CITATION
{"citationItems":[{"id":"ITEM-1","item=
Data":{"DOI":"10.1155/2016/7170943","ISSN&quo=
t;:"16877268","abstract":"Recently,
increasing demand for remote healthcare monitoring systems poses a specif=
ic
set of Quality of Services (QoS) requirements to the MAC layer protocols =
and
standards (IEEE 802.15.6, IEEE 802.15.4, etc.) of Wireless Body Area Sens=
or
Networks (WBASNs). They mainly include time bounded services (latency),
reliable data transmission, fair channel distribution, and specified data
rates. The existing MAC protocols of WBASNs are lack of a specific set of
QoS. To address this, the paper proposes a QoS profile named delay,
reliability, and throughput (DRT). The QoS values computed through DRT
profile provide maximum reliability of data transmission within an accept=
able
latency and data rates. The DRT is based on the carrier sense multiple ac=
cess
with collision avoidance (CSMA/CA) channel access mechanism and considers
IEEE 802.15.4 (low-rate WPAN) and IEEE 802.15.6 (WBASN). Further, a detai=
led
performance analysis of different frequency bands is done which are
standardized for WBASNs, that is, 420 MHz, 868 MHz, 2.4 GHz, and so forth.
Finally, a series of experiments are conducted to produce statistical res=
ults
for DRT profile with respect to delay, reliability, and packet delivery r=
atio
(PDR). The calculated results are verified through extensive simulations =
in
the CASTALIA 3.2 framework using the OMNET++ network
simulator.","author":[{"dropping-particle":"=
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Based QoS Profile: A MAC Layer Performance Optimization Mechanism for
Biomedical Applications in Wireless Body Area Sensor
Networks","type":"article-journal","volume&=
quot;:"2016"},"uris":["http://www.mendeley.com/doc=
uments/?uuid=3D1173fed6-f528-357b-987f-e4aed94f27cf"]}],"mendeley=
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et al., 2016)","plainTextFormattedCitation":"(Akbar et
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csl-citation.json"} (Akbar
et al., 2016) (Kos
et al., 2019) (Külah & Alemdar, 2020) , se propuso la siguient=
e división
mostrada en la Figura 1
y Figura 2 (Wehbe et al., 2014) , por lo cual se asignaron diferentes colores=
a
estas áreas para poder identificarlos, ya que los nodos no pueden
cambiar de área, con el motivo de simplificar el escenario de movili=
dad
de los nodos. Cabe recalcar que existieron posiciones de relevos por lo que=
en
ciertos momentos los nodos o jugadores compartieron la misma área, es
por ello que se ha definido áreas conformadas con barras, es el caso=
de
los DFI y EI o DFI y MC.
&n=
bsp;
Otro aspecto importante tomado en cuenta fue la veloci=
dad de
los jugadores (nodos). Por lo cual se consideró velocidades promedio=
s y
velocidades máximas donde el entorno cambiaba cada 5 segundos (Antonio Durá Vaquera, n.d.) , siendo este el tiempo =
de
movilidad. Después de cumplir este tiempo se cambió la
dirección y la velocidad de los nodos utilizando una variable aleato=
ria
uniforme. En (Wehbe et al., 2014) se detallaron las velocidades promedio en Km=
/h y
en (Mendez-Villanueva, 2012) y las velocidades
máximas, para las distintas posiciones, es decir para defensas,
medio-campistas y delanteros. En la Tabla 2
se resumen estos valores.
Figura <=
/span> 1
Escenario 1 "Equipo
Defendiendo"
Figura <=
/span> 2
Escenario 2 "Equipo Atacando=
"
Tabla 2
Velocidades Promedio y Máx=
imas
para cada Posición
DFC
DFI/DFD
MC
DC
Vel. Promedio
6,279
6,279
6,965
6,711
Vel. Max.
28,1
26,7
27
29,1
La
metodología utilizada para comparar el desempeño de cada uno =
de
los protocolos de enrutamiento dentro de estos dos escenarios se muestra en=
la Figura =
3 1 (Beitelspacher et al., 2020; Besher et al., 2020; Lloret et al., 2016)=
. Por último, se
escogió UDP como protocolo de transporte debido a que comparado con =
TCP
éste es más rápido, simple y eficiente. Esta
caracterización permitió generar un tráfico realista e=
ntre
los nodos.
El cuarto bloque permitió definir las ár=
eas de
movilidad de los nodos, así como las velocidades de cada uno dependi=
endo
de la posición que ocupó dentro del campo de juego y el tipo =
de
escenario, para esto se utilizó el módulo Random Walk =
de
NS3 el cual es un modelo de movilidad aleatorio 2D. Hay que tener en cuenta=
que
una de las limitaciones de la simulación es la modelación de =
la
movilidad, modelar el movimiento humano es otro campo de investigació=
;n
específico (Conti & Giordano, 2014) .
A continuación, se especifican las condiciones =
de
cada escenario estudiado, es decir, el comportamiento de los nodos cuando
representan al equipo de fútbol atacando o defendiendo, para lo cual=
se
hizo uso de dos scripts, ya que se definen diferentes áreas en cada =
uno.
Una vez configurados los dos escenarios, se ejecutó la simulaci&oacu=
te;n
utilizando los protocolos de enrutamiento propuestos y los parámetro=
s de
las tarjetas inalámbricas o módulos Wi-fi que trasmiten la
información de los sensores biométricos según el tipo =
de
análisis (tres análisis). Algunos de los sensores más
comunes utilizaron el estándar IEEE 802.11n como lo hizo en (Hu et al., 2020) , por lo que la simulación emple&oacut=
e;
el mismo. Para generalizar los resultados se hizo uso de una semilla de
aleatoriedad y se repitió la simulación utilizando un script =
de
Linux, variando así las condiciones de la simulación.
Después, se realizó un análisis estadístico de =
los
resultados obtenidos para cada escenario con cada uno de los protocolos
empleados. Finalmente, se establecieron las conclusiones respectivas y se
definió el mejor protocolo dependiendo del tipo de métrica. A=
ntes
de continuar, se muestran en la Tabla 3
los parámetros utilizados en las simulaciones.
Basándose en la metodología mencionada, =
se han
propuesto tres análisis estadísticos utilizando intervalos de
confianza del 95%, el primero consistió en ejecutar la simulaci&oacu=
te;n
con un tiempo de 3 minutos o 180 segundos con la configuración de la Tabla 3 , usando una potencia fija de 3dBm y los
protocolos de enrutamiento con sus valores por defecto. Se realizaron
cinco simulaciones para cada escenario con cada uno de los protocolos de
enrutamiento. El segundo análisis consistió en aumentar el
número de simulaciones para cada protocolo a 20, así como el
tiempo de cada simulación a 5 minutos o 300 segundos, también=
se
aumentó el intervalo de transmisión a 5, 10, 20, 30 y 60 segu=
ndos
y se modificaron los archivos de configuración de cada protocolo, pa=
ra
mejorar el desempeño de la red. Por lo tanto, para el protocolo OLSR=
se
acortó el valor del parámetro Hello de 2 segundos a 0.5
segundos, y el parámetro TC se disminuyó de 3 a 1 segu=
ndo.
Para el protocolo DSDV se cambió el parámetro PeriodicUpda=
teInterval
de 15 a 2 segundos, con esto se redujo el periodo de intercambio de tab=
las
de enrutamiento completas entre nodos.
El siguiente parámetro modificado fue el Set=
tlingTime ,
reduciendo el tiempo mínimo de almacenamiento de una
actualización de 5 a 3 segundos. Ahora, para AODV el primer
parámetro que se modificó fue el intervalo Hello , el c=
ual
cambió de 1 a 0.5 segundos. También se estableció al
parámetro ActiveRouteTimeout en 2 segundos en lugar del valor
original de 3 segundos, este parámetro determinó el periodo de
tiempo durante el cual una ruta es considerada como válida, por lo
tanto, al tener un escenario con alta movilidad se disminuyó este
periodo.
En el tercer análisis se escogieron los dos pro=
tocolos
con mejor rendimiento que en el segundo análisis y con el intervalo =
de
tiempo más óptimo. Además, varió la potencia del
transmisor en el rango mostrado en la Tabla
3 3
Resumen de la Metodología Ap=
licada
Tabla 3
Parámetros de la Simulaci&=
oacute;n
PARÁMETROS
ANÁLISIS 1
ANÁLISIS 2
ANÁLISIS 3
Está=
ndar
WI-FI
IEEE 802.11=
n (2.4
GHz)
Capa
Física
ErpOfdmRate=
48Mbps
Protocolo de transporte
UDP
Tipo de tráfico
CBR
Tamaño del paquete
100 bytes
Data Rate
100 kbps
Tipo de Movilidad
Random Walk
Tiempo de Movilidad
5 seg
Tiempo de Simulación
180 seg
300 seg
300 seg
Intervalo de Transmisión
1 seg
5, 10, 20, =
30 y
60 seg
20 seg
Número de Simulaciones por Protocolo
5
20
20
Potencia del
Transmisor
3 dBm
3 dBm
0 - 10 dBm
Cabe señalar =
que
la
cantidad de nodos y el tipo de escenario demandó un tiempo considera=
ble
para realizar múltiples simulaciones, debido a la alta carga
computacional requerida. Con el objetivo de realizar el estudio con varias
pruebas, 230 en total, se utilizaron tiempos de 3 y 5 minutos, ya que
incrementar estos tiempos es una limitación debido a las demoras que
requieren cada uno de los estudios. Entonces, se prefirió realizar
múltiples simulaciones de corta duración para obtener resulta=
dos
que se puedan valorar estadísticamente, en lugar de una sola
simulación de larga duración.
&n=
bsp;
Resultados y Discusión
Primer an&aac=
ute;lisis
En la Figura 4 se presentan los resultados obtenidos =
para
el PDR en el escenario 1 y escenario 2. Es evidente que la mejor tasa de
recepción de paquete se logra con el protocolo de enrutamiento react=
ivo
AODV, llegando hasta un 49% de paquetes recibidos. Mientras que el peor
desempeño lo obtiene DSDV con tan solo un 27%. Sin embargo, los
intervalos de confianza son mayores en AODV, lo que implica que hay m&aacut=
e;s
variaciones entre simulaciones. En cuanto al delay promedio obtenido para c=
ada
protocolo, se pueden observar los resultados logrados en la Figura 5 , que el protocolo OLSR alcanza los mej=
ores
resultados ya que tienen el menor delay. En cambio, los otros dos protocolo=
s no
varían mucho, pero se tienen que tomar en cuenta que para el escenar=
io 2
el protocolo DSDV tiene intervalos de confianza muy amplios. Finalmente, se puede observar en l=
a Figura 6 , que AODV tiene el mejor throughput pr=
omedio
en los dos escenarios, le sigue el protocolo OLSR y el protocolo AODV en es=
te
caso es el peor.
<=
/o:p>
Figura 4
Comparativa
del PDR para cada Protocolo de Enrutamiento
<=
/o:p>
Al analizar l=
as
métricas s e observa=
que
el protocolo AODV
tiene una alta variación en los intervalos de confianza. Por lo que
depende mucho de las condiciones de movilidad, velocidad y del canal, para
tener un buen desempeño. En ciertos instantes el tráfico cae
prácticamente a cero, debido a la perdida de paquetes. Por este moti=
vo
se verifica las tablas de enrutamiento y las posiciones de los nodos en est=
os
instantes y se verifica que, debido al movimiento de los nodos, existen
instantes en los que un nodo sale del rango de cobertura con algún n=
odo
vecino pero las tablas de enrutamiento tardan un determinado tiempo en
converger nuevamente, en el caso de OLSR, se escoge un intervalo de 3 segun=
dos
para intercambiar mensajes TC. Además, se puede notar que debido a la
naturaleza del protocolo AODV, este resulta ser más eficiente debido=
a
que actualiza sus tablas de enrutamiento únicamente cuando va a
transmitir tráfico.
<=
/o:p>
Figura 5
Comparativa
del Delay para cada Protocolo de Enrutamiento
=
Figura 6
Comparativa
del Throughput Promedio para cada Protocolo de Enrutamiento
Segundo
análisis
Los resultad=
os
muestran que, al aumentar el número de simulaciones y ajustar los
parámetros de los protocolos, las métricas mejoraron notablem=
ente
con respecto a los resultados anteriores. Esto se debe a que los protocolos=
de
enrutamiento tienen más tiempo para converger y por lo tanto existe =
una
menor pérdida de paquetes, además debido a la movilidad de los
nodos y al canal inalámbrico existen interferencias, pérdidas=
de
paquetes y por lo tanto el PDR no supera el 70%. Además, los interva=
los
de confianza se redujeron considerablemente, lo cual indica que existe una
menor desviación entre los valores. En la Figura 7 , se observa que el PDR tiene una tende=
ncia
creciente conforme se incrementa el intervalo, sin embargo, este crecimient=
o no
es tan acelerado, por lo que no hay gran diferencia a partir de los 20
segundos. Con respecto a los protocolos se puede notar que AODV presenta
mejores resultados en el escenario 1 y DSDV para el escenario 2.
Figura 7
Comparativa
del PDR para cada Protocolo de Enrutamiento
Figura 8
Comparativa
del Delay para cada Protocolo de Enrutamiento
En cuanto al delay, la REF _Ref87022791 \h Figura 8
muestra que el delay aumenta rápidamente conforme se incrementa el
intervalo de transmisión, pero al comparar los protocolos de
enrutamiento no se evidencia una diferencia muy marcada entre cada uno. Se
puede observar que a partir de los 20 segundos los intervalos de confianza
crecen debido a que al separar las transmisiones disminuye la cantidad de
información recibida y por lo tanto un error tendrá un mayor =
impacto
en los resultados. Con respecto a la última métrica, el
throughput, en la Figura 9 indica que el mejor protocolo es AODV p=
ara el
escenario 1 y el protocolo DSDV para el escenario 2. Además, se puedo
observar que el throughput no alcanza los 100 kbps que es la tasa fijada en
cada uno de los trasmisores, por el contrario tienen un valor promedio de 6=
7.82
kbps y 58.96 kbps para el escenario 1 y 2 respectivamente, esto ocurre debi=
do a
las características propias de una red ad-hoc multi-salto, ya que el
throughput disminuye con cada salto según (González et al., 2016) .
Figura 9
Comparativa
del Throughput para cada Protocolo de Enrutamiento
=
;
Tercer
análisis
De acuerdo a los resultados anteriores,=
se
descarta el protocolo OLSR debido a que tiene el peor rendimiento comparado=
con
los otros dos protocolos en la mayoría de métricas y escenari=
os.
Además, se establece el intervalo de transmisión en 20 segund=
os
ya que se obtienen mejores resultados y permite la convergencia de los
protocolos de enrutamiento. También se incrementa la potencia del
transmisor, y se puede notar que las métricas mejoran su rendimiento=
con
respecto a los resultados de la sección anterior. Sin embargo, a par=
tir
de los 4 dBm la red Ad Hoc deja de ser multi-salto y pasa a conformar una r=
ed
MESH. En la Figura 10 , conforme aumenta la potencia,
también aumenta el PDR debido a que se disminuye la cantidad de salt=
os,
sin embargo, también aumentan las interferencias por lo que
todavía existen pérdidas de paquetes. Por otro lado, en el
escenario 1 el protocolo AODV es mejor que DSDV hasta los 4 dBm o, en otras
palabras, AODV tiene un mejor rendimiento que DSDV en la red multi-salto, p=
ero
DSDV es mejor cuando la red pasa a ser de tipo MESH. Al analizar el escenar=
io
2, se observa que DSDV es mejor que AODV sin importar el valor de la potenc=
ia
del transmisor.
Figura 10
Comparativa
del PDR para cada Protocolo de Enrutamiento
&nbs=
p;
En la Figura 11 , se puede notar que el protocolo AODV =
tiene
un mayor delay que DSDV en los dos escenarios, esto se debe a que AODV al s=
er
un protocolo reactivo le toma mayor tiempo obtener la información de
ruteo de los demás nodos. También se observa que el menor del=
ay
en una red MESH se obtiene con una potencia de 10 dBm, mientras que en una =
red
multi-salto el mejor resultado se logra con 3 dBm, de lo cual se puede notar
que en ambos tipos de red el mejor resultado se obtiene con el máxim=
o de
potencia. Con respecto al throughput, la Figura 12 indica
que el valor incrementa conforme aumenta el nivel de potencia de los
transmisores. También se nota que en el escenario 1, AODV es mejor q=
ue
DSDV hasta los 4 dBm, y además se observa que con 10 dBm no existe u=
na
diferencia notable, teniendo además un error menor al 1%. Ahora, en =
el
escenario 2 DSDV siempre es mejor que AODV a excepción de los 10 dBm,
donde nuevamente no hay una diferencia significativa. Finalmente, se puede
notar que con 10 dBm el throughput coincide con el data rate de
transmisión configurado inicialmente, siendo así el mejor
resultado posible para esta métrica.
Figura 11
Comparativa
del Delay para cada Protocolo de Enrutamiento
Figura 12
Comparativa
del Throughput para cada Protocolo de Enrutamiento
<=
span
style=3D'mso-bidi-font-size:12.0pt;mso-ansi-language:ES-EC;font-weight:norm=
al;
mso-bidi-font-weight:bold'>
Conclusiones
En el primer análisis, se puede concluir que el
protocolo de enrutamiento reactivo AODV tiene un mejor desempeño en =
las
tres métricas analizadas (PDR, delay y throughput), pero con unos
intervalos de confianza muy amplios. Se comprueba que el número
máximo de saltos generados fue de tres, cuando el nodo se encontraba=
muy
alejado del nodo receptor. Mientras que cuando el nodo transmisor se encont=
raba
más central o cerca del nodo receptor el número de saltos
generado era de uno. De acuerdo al perfil del tráfico obtenido y el =
PDR
para cada uno de los protocolos, se puede notar que existe una gran
pérdida de paquetes. Estas pérdidas ocurren debido al
comportamiento aleatorio de los nodos, lo cual genera cambios en la
topología de la red. Es decir, las tablas de enrutamiento se actuali=
zan
constantemente, pero los movimientos bruscos de los nodos (jugadores) no
permiten que converjan en ciertos instantes. Además, se comprueba qu=
e el
crecimiento del throughput afecta la efectividad del envío de paquet=
es
debido a las limitaciones del ancho de banda.
En el segundo análisis las tres métricas
mejoran y existe una reducción de los intervalos de confianza debido=
al
cambio en los parámetros de cada protocolo, el espaciamiento entre
transmisiones y por el incremento del número de simulaciones. Por
ejemplo, con un espaciamiento de 20 segundos el delay se reduce un 64.58% p=
ara
OLSR, 89.36% para AODV y 88.31% para DSDV, realizando un promedio entre los=
dos
escenarios. Por otra parte, al aumentar el intervalo de transmisión =
se incrementa
el delay de cada paquete, por lo que se escoge 20 segundos como un valor
óptimo. Con este valor el throughput aumenta un 27.33% para OLSR, un
105% para DSDV realizando el promedio entre los dos escenarios. Mientras que
para AODV el throughput aumenta un 44.33% en el escenario 1. Además,=
se
evidencia que en el escenario 1 (Defensa) el protocolo con mejor rendimient=
o es
AODV y para el escenario 2 (Ataque) es DSDV. Finalmente, en el análi=
sis
tres, mejoran los resultados en los dos escenarios. Sin embargo, al superar=
los
4 dBm en la potencia del transmisor, la red se convierte en una red MESH. Y=
, en
definitiva, se comprueba que los dos protocolos no tienen gran diferencia e=
n su
desempeño en las tres métricas con una potencia de 10 dBm, po=
r lo
que se puede escoger cualquiera de los dos para este tipo de escenarios.
Reconocimientos
Los autores de este trabajo agradecen al Departamento =
de
Eléctrica, Electrónica y Telecomunicaciones de la Universidad=
de
Cuenca por todo el apoyo brindado y herramientas proporcionadas para la
elaboración de este artículo.
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![3D"Interfaz](3D"829-FINAL-GALERADA_archivos/image003.gif")
![3D"Interfaz](3D"829-FINAL-GALERADA_archivos/image005.gif")
![](3D"829-FINAL-GALERADA_archivos/image007.gif")
![3D"Diagrama
Descripción](3D"829-FINAL-GALERADA_archivos/image009.jpg")
![3D"Gráfico,](3D"829-FINAL-GALERADA_archivos/image011.jpg")
![3D"Gráfico,](3D"829-FINAL-GALERADA_archivos/image013.jpg")
![3D"Gráfico,](3D"829-FINAL-GALERADA_archivos/image015.jpg")
![3D"Gráfico,](3D"829-FINAL-GALERADA_archivos/image017.jpg")
![3D"Gráfico,](3D"829-FINAL-GALERADA_archivos/image019.jpg")
![3D"Imagen](3D"829-FINAL-GALERADA_archivos/image021.jpg")
![3D"Imagen](3D"829-FINAL-GALERADA_archivos/image023.jpg")
![3D"Tabla
Descripción](3D"829-FINAL-GALERADA_archivos/image025.jpg")
![3D"Gráfico,](3D"829-FINAL-GALERADA_archivos/image027.jpg")