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QoS Taxonomy towards Wireless Body Area
Network Solutions
Shah Murtaza Rashid Al Masud
Najran University, P.O. Box 1988
Najran, Saudi Arabia
ABSTRACT
To improve the health care facilities for the people a tiny, automated, and intelligent medical device and technology namely
wireless body area network (WBAN) evolved. The derivation of this technology is wireless sensor network (WSN) consists of
sensors, actuators, radio systems, and transmission systems which should be situated in, on, and around the human body to
measure, store, and transmitted patients’ vital signs and syndromes for further investigation, treatment, decisions, and
awareness. Researchers in all around the world now have very enthusiastic interest to advance this technology especially on
certain standardizations like its architecture, cost effectiveness, energy consumption or power efficiency, security and privacy
topics. Academicians are trying to improve the QoS factors in sensor networks by suggesting new protocols. But quality of
services (QoS) factors concerning WBAN technology still remains insignificant whereas QoS issues are also a major concern.
WBAN needs diverse functioning requirements vary from application to application which are very perceptive hence entail
more attention. Research personnel concerning QoS issues in WBAN should handle real time data transmission system, data
rate, end-to-end data transmission, data transmission accuracy rate, latency, delay time, jitter, low power data transmission,
data availability, minimum data loss, data security, network coverage, frequency, bandwidth, throughput, and reliability
matters very seriously and an effective way. In this paper we tried to focus on the overall limitation, scopes, and challenges
issues concerning QoS factors in WBAN. We have also given our effort to identify, analyze and present some of the recent
protocols and technologies developed towards updating QoS issues in WBAN. This research article will help the researchers,
academicians and practitioners to further study, modification, and develop more efficient QoS-based-WBAN. At the end of this
research paper a number of open research issues are also discussed.
Keywords: Quality of Service (QoS), WBAN, WSN, QoS Requirements
1. INTRODUCTION
Quality of service (or QoS) is one of the important features of any application like internet, wireless networks, ad hoc
networks, wireless sensor networks (WSNs), and wireless body area networks (WBANs). But the reality is that QoS
matters didn’t get more attention in WSNs and WBANs like other features such as design, architecture, energy efficient
protocol design, nodes’ positioning and location [1]. Other than health monitoring the major applications of WSNs
include environmental monitoring, military surveillance digitally equipped homes, manufacturing process monitoring,
conferences, vehicle tracking and detection (telemetry), and monitoring inventory control. Whereas, WBAN is location
independent portable patients’ monitoring system, sporting activities, and emergency system including military services
developed by using tiny and intelligent low powered and cost effective sensor devices [2][3].
The main provisions for WBANs are low power consumption that is energy efficient WBAN protocols, low latency,
scalability, quality of service (QoS), reliability, efficient bandwidth utilization, and throughput, co-existence with other
WBANs technologies, and high security and privacy [4].
WBAN is classified into three main classes, they are: off-body, on-body, and in-body communication. BAN nodes
(BN) and BAN network coordinators (BNC) are used to communicate bidirectional from BNC to BN and vice versa.
BNC is the gateway to external networks like internet, wireless local area networks (WLAN), wireless personal area
networks (WPAN), and cellular networks. Shorter or limited range WLAN can be used for indoor connectivity like
inside room, house, clinic, hospital, or health care center, in the other hand cellular networks can be used for longer
distance that is outdoor connectivity. This will help seamless roaming and end-to-end QoS factor. For real time
application it doesn’t need to store data, but for non-real time applications the gateway can store data locally and use
when necessary [5]. A typical BAN structures along with the comparison other types of wireless networks are shown in
Figure 1 [6].
Person’s vital signs which are usually created by sensors on, in, and around the individual body accountable for
sensing organic or biological signals such as movement, temperature, pulse, diabetes, blood pressure,
electromyography, electrocardiogram, oxygen saturation, etc. WBAN technology is used to continuously monitoring
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these vital signs for patients’ health status analysis. Low frequency, small information bandwidth based physiological
signals which are commonly detected by sensors in WBAN is listed in the following Table 1.
Figure 1: A typical wireless body area network (WBAN) application [6]
Table 1: Commonly detected Physiological signals by sensors in WBAN
Physiological Signal
Signal frequency range/
Range of parameter
Bandwidth (Hz)
ECG signal
0.01-250
0.5-4 mV
Respiratory rate
0.1-10
2-50 breaths/min
Blood pressure (BP)
0-50
10-400 mg/Hg
Blood flow
0-20
1-300 ml/s
Blood pH
0-2
6.8-7.8 pH
EEG
0.5-60
3µV-300µV
Body temperature
0-0.1
32-40 0 C
EMG (Electromyogram)
10-5000
10µV-15mV
GSR (Galvanic Skin Reflex)
0.03-20
30µV-3mV
Cardiac rate
0.4-5
Oximetry
0-30
Arterial pressure
0-60
Nerve potentials
Max 10,000
0.01-3 mV
Patients’ real time data and vital signs are the key elements for the WBAN technology that is why these data sets
should be handled with special care ensuring reliability, security, and accuracy since a wrong signal could make
vulnerable the person’s life. Towards bridging the physical world and electronic systems in WBAN sensors are playing
a vital role, and a wide range of commercially available sensors can be deployed, such as accelerometer and gyroscope,
ECG, electromyography (EMG), and electroencephalography (EEG) electrodes, pulse oximetry, respiration, carbon
dioxide (CO2), blood pressure, blood sugar, humidity, and temperature sensors etc.
The following Table 2 has shown the commonly used sensors along with their work range. It also notices the wide
variation in data rate, bit error rate (BER), delay tolerance, duty cycle, and lifetime, which requires scalable solutions
with quality of service (QoS) provisions [7].
Table 2: Sensors commonly employed in WBAN systems and their typical data rates.
Sensor
How it works
Data rate (kbps),
Bit error rate (BER), Setup
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Accelerometer
Gyroscope
ECG
EMG
EEG
Pulse Oximetry
Respiration
Carbon dioxide
Blood pressure
Blood sugar
Humidity
Temperature
time, Duty cycle, Desired
battery lifetime, P2P latency
Measures the acceleration relative to free fall High, <10 kbps up to 12 nodes,
in three axes
<10-10, <3s, <1%, >1 week, <
250 ms
Measures the orientation
based on the High, <10 kbps up to 12 nodes,
principles of angular momentum
<10-10, <3s, <1%, >1 week, <
250 ms
Measures potential difference across electrodes High, 6.0, <10-10, <3s, <10%,
put on corresponding parts of the body
>1 week, < 250 ms
Measures potential difference across electrodes High, 1.536 Mbps for up to 6
put on corresponding parts of the body
nodes, <10-10, <3s, <10%, >1
week, < 250 ms
Measures potential difference across electrodes High, 3.6, <10-10, <3s, <10%,
put on corresponding parts of the body
>1 week, < 250 ms
Measures ratio of changing absorbance of the Low, <10-10, <3s, <1%, >1
red and infrared light passing from one side to week, < 250 ms
the other of a thin part of the body's anatomy
Uses two electrodes, cathode and anode Low, 0.24; <10-10 , <3s, <1%, >1
covered by a thin membrane to measure the week, < 250 ms
oxygen dissolved in a liquid
Uses the infrared light and measures the Low, <10-10, <3s, <1%, >1
absorption of the gas presented
week, < 250 ms
Measures the systolic pressure (peak pressure) Low, 0.05, <10 kbps up to 12
and diastolic pressure (minimum pressure)
nodes, <10-10, <3s, <1%, >1
week, < 250 ms
Traditionally analyzes drops of blood from a Low, <10-10, <3s, <1%, >1
fingertip recently, uses non-invasive method week, < 250 ms
including a near infrared spectroscopy,
ultrasound, optical measurement at the eye,
and the use of breath analysis
Measures the conductivity changes of the level
of humidity
Uses a silicon integrated circuit to detect the
temperature changes by measuring the
resistance
Drug delivery
Deep
brain
simulations
Hearing Aid
Capsule
Endoscope
Drug Dosage
Audio
Video/ Medical
Imaging
Very low
Very low, 0.0024-0,05; <10-10,
<3s, <1%, >1 week, < 250 ms
<16
<320, <10-3, <3s, <50%, >3
years, < 250 ms
70, <10-10, <3s, <10%, >40
hours, < 250 ms
500, <10-10 , <3s, <50%, >24
hours, < 250 ms
<0.5, <10-10, <3s, <1%, >24
hours, < 250 ms
1 Mbps for 3 nodes, <10-5, <3s,
<50%, >24 hours, < 100 ms
<10 Mb/s for 2 node, <10-3, <3s,
<50%, >12 hours, < 100 ms
Despite the fact that WBAN technology is still new, the industry is expected to grow rapidly in the coming years.
Our research paper has been provoked by the recent studies with admiration to WBAN usages and increase of human
centric computing using wearable sensing devices. The different aspects of QoS factors of WBAN are presented in our
research paper.
This paper has been organized as follows. In section 1, we presented a brief introduction of the subject matter. In
section 2, we presented the IEEE requirements necessary for WBAN development. In section 3, we focused a general
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Volume 2, Issue 4, April 2013
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observations on QoS and its main objectives. In section 4, we discussed service issues of WSN towards developing
quality enable WBAN. In section 5, we analyzed the challengeable circumstances of QoS in WBAN. In section 6, we
discussed various QoS techniques, mechanisms, and metrics necessary to build efficient WBAN. In section 7, we briefly
studied, analyzed, and discussed the existing QoS based techniques, protocols and models for WBAN. In section 8, we
discussed some open research issues of QoS and then finally in section 9 the conclusion.
2. IEEE AND WBAN
A highly reliable communication for medical devices especially for those which are implanted in the human body a
radio frequency (RF) based wireless technology is needed, it was formally defined by the IEEE 802.15 working groups
[8] [9]. The transmissions of WBAN nodes cover a short range of about 2 m [10], and other specifications of WBAN
[11] are shown in Table 3.
Table 3: Technical requirements along with IEEE specification for WBAN technology
Requirements
Specifications
Distance/ operating space
2 m standard and 5 m special use; in, on, and around the body
Network Density
2-4 nets/m2
Network Size
Max : 100 devices/network, modest < 64 devices per BAN
Up to 5 year for implants
Up to 1 week for wearable
Target lifetime
Ultra-long for implants
Long for wearable
MedRadio, ISM, WMTS, UWB
Target frequency bands
Global Unlicensed and Medical bands
~1mW/ Mbps, support for several power management and consumption
Power Consumption
scheme
Between 0.001–0.1mW in stand-by mode up to
Peak power consumption
30mW in fully active mode
Scalable
Network Throughput
100 Mbps Max
From sub kb/s up to 10 Mb/s
Data rate
Scalable
Low power listening, wake up, turn-around and
MAC
synchronization
Scalable, reliable, versatile, self-forming
Self-forming, distributed with multi-hop support
Topology
Star, Mesh or Tree
Device Duty cycle,
From 0.001% up to 100%
Very Low, Low, and High Adaptive, Scalable
duty cycle modes
Allows device driven degradation of services
Startup Time
Latency
10 ms
Network setup time
< 1 sec ( Per device setup time excludes network initialization)
Coexistence
Simultaneous co-located operation of up to 10
independent BANs
• BER: from 10–10 to 10–3
• P2P latency: from 10ms – 250ms
QoS
support
and
• Reservation and prioritization
differentiation
Real-time waveform data, periodic parametric
data, episodic data and emergency alarms
Future proof
Fault tolerance
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Upgradeable, scalable, backwards compatible, effective sleep mode, peer to
peer, point to multi point communication , QoS and guaranteed
bandwidth, high privacy and security
Ability to isolate and recover from failures. Self-healing capability; No
single point of failure
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Dynamic Environment
Security
Seamless operation of multiple nodes moving in and out of range of each
other; Body shadowing (twisting, turning, running),
Attenuation
Authentication, Authorization, Privacy, Confidentiality, Encryption,
Message integrity; Many levels, long term, short term, light weight
Safety/Biocompatibility
Meet regulatory requirements. e.g., FDA, SAR and HIPPA; No harmful
effects of long term continuous use
Ergonomic consideration
Non-invasive, unobtrusive, small size, weight and form-factor Size, shape,
weight and form factor restricted by location and organ
Ability to reprogram, recalibrate, tune and configure devices wirelessly;
Personalized, integrated, configurable and context aware services
Reprogramming,
Calibration,
Customization
Antenna Pattern
Omni Directional, small, and flexible
3. QOS OBSERVATIONS AND MAIN OBJECTIVES
It is very difficult to find and give definition of QoS related to wireless sensor networks. Among many of definitions we
can select the following as examples. The number of useful sensors used to send data at any given period of time [12].
QoS can also determine by network characteristics like data transmission, and error rates [13]. QoS also depends on the
network quality types such as bandwidth, latency, and jitter [14]. In most of the cases the performance or quality service
vary from application to application and these applications can be classified as reliability, timeliness, robustness,
trustworthiness, and adaptability [15]. QoS issues towards developing high-quality and well-organized WSN and
WBAN is a great research area. But it needs more attention due to the critical level of operations for example critical
information with zero delay, real time data transmission with no error or drop, deployment, reliability, security,
privacy, and some features related to power or energy. There are two perspectives in traditional QoS point of view, they
are applications and network. In the first case, QoS usually refers to the quality as apparent by the user/application, but
in networking perspective, QoS is accepted as a measure of the service quality that the network offers to the
applications/users. The two QoS perspectives can be demonstrated using a simple form as shown in Figure 2 [16].
Figure 2: QoS perspectives: a general view
The efforts of QoS are categorized as best effort (no QoS), guaranteed services (hard QoS) or differentiated services
(soft QoS). Any application must satisfy any one of the above three categories to achieve its QoS goal [17]. QoS goals
for any application should include the maximization of services by the network by minimal usage of energy (energy
consumption) and efficient bandwidth utilization [18]. So the technologies like WBAN, WSN we should be very careful
that in both cases we have inadequate computational resources, restricted memory and limited time (deadlines) for an
event. Major QoS of wireless WBANs are latency & reliability [18].
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4. CONCERNING SERVICE ISSUES OF WSN TOWARDS DEVELOPING QUALITY ENABLE WBAN
Wireless sensor network is an intelligent, agile, low-cost, and ultra-low power technology developed by using sensors
that can collect data and help to transmit when necessary. The fundamental differences between sensor networks and ad
hoc networks are illustrated in the following Table 4.
Table 4: Difference between sensor networks and ad-hoc networks
Wireless Sensor Network
Ad-hoc Network
High
Low
Frequently changes
Almost fixed for a long time
Sensors nodes are densely developed
Flexible
High due to sensor nodes
Low
Used for broadcast communication
Used for point-to-point
communications
Computing capacity
Limited in power, computational capacities and
High
memory
Cost
High due to large number of sensors and overhead
Reasonable
Parameter
Sensor nodes number
Topology
Efficiency
Failure rate
Communication
For healthcare monitoring system, WSN, wearable and implantable wireless body area network emphasis on some
significant components such as Tele-monitoring, tracing and monitoring doctors and patients, and drug administration
[19]. Almost similar technologies used and applications of WSN are gradually moving into BBAN. The key goal of
WSN system is patients' physiological signals monitoring, where the main goal of WBAN is providing real time
feedback of patients biological data, and uninterruptedly observing health parameters like heartbeat rate, blood pressure
level in an efficient way and also some other parameters of patients' on-body, around body and in-body [20]. Depending
on the level of usages of WSN and WBAN technologies information or facts acquirement through sensor devices can be
point-to-point or multipoint-to-point. A WSN system that detects and transmits patients' vital signs through electric
signals is illustrated in Figure 3 [19].
Figure 3: A typical WSN system for detecting and transmitting signals from a human body: (a) current application and
(b) future application [19].
WBANs have some own characteristics which are different from conventional wireless sensor networks (WSNs) and
also characterized into some categories such as architecture, network density, data rate, latency, mobility, and many
more. It may include many devices and applications and has the characteristics of general wireless sensor networks. In
Table 5 in our research paper a schematic overview of differences between WSN and WBAN are given [21] [22] [23].
A WBAN can use the outmoded approaches existing for general sensor networks and must also have support to handle
life-threatening emergency situations.
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Table 5: Differences between WSN and WBAN
WSN
Challenges
WBAN
Scale
Monitored environment (m/km)
Human body (cm/m)
Node number
Fewer, limited in space
Result accuracy
Many redundant nodes for wide
area coverage
Through node redundancy
Node tasks
Node performs a dedicated task
Node performs multiple task
Node size
Small is essential
Network topology
Small is preferred, but not
important
Very likely to be fixed and static
Data rates
Homogeneous
Latency
Nodes
can
be
physically
unreachable after deployment. It
may be necessary to maximize
battery life-time in WSN at the
expense of higher latency.
Performed easily, nodes even
disposable
Several years/months
Heterogeneous WBAN may occur in a more
periodic manner and stable data rate. The data
rate may vary from few kb/s to few Mb/s.
Replacement of batteries in WBAN nodes is
much easier done when energy conservation is
definitely beneficial.
Node replacement
Node lifetime
Power supply
Accessible and likely to be replaced
more easily and frequently
Likely to be large, energy supply
easier
Most likely solar and wind power
Power demand
Energy scavenging
source
Biocompatibility
Not a consideration
applications
Lower
Security level
in
most
Through node accuracy and robustness
More variable due to body movement
Replacement of implanted nodes difficult
Several years/months, smaller battery capacity
Inaccessible and difficult to replace in an
implantable setting
Likely to be lower, energy supply more difficult
Most likely motion (vibration) and thermal (body
heat)
A must for implants and some external sensors
Higher, to protect patient information
Impact of data loss
Likely to be compensated
redundant nodes
by
Wireless
technology
Mobility
Bluetooth, Zigbee, GPRS, WLAN
More significant, may require additional
measures to ensure QoS and real-time data
delivery
Low power technology required
WSN nodes are usually considered
stationary.
WBAN users may move around. WBAN nodes
share the same mobility pattern.
5. THE CHALLENGES CIRCUMSTANCES OF QOS IN WBAN
In our research paper we have studied and analyzed the major challenges while developing a QoS based WBAN. The
most important QoS challenges in WBANs are illustrated in following Table 6.
Parameters
Table 6: Major challenges in order to develop QoS based WBAN
Related challengeable Circumstances to ensure QoS
Limited
resources
capabilities
Scalability
Multi-source
systems
and
multi-sink
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Limited energy, bandwidth, memory, and processing and communication
capabilities.
Number of WBAN nodes may be increased or decreased, but QoS should
not be affected for this reason.
Platform heterogeneity, service-oriented architecture, resource selfmanagement and security requirements [24]. And also critical
infrastructure protection [25]
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Node deployment
Dynamic network topology
Various types of applications
Various traffic types
Wireless link unreliability
Real-time system
Multimedia data in WSNs
and WBANS in some cases
Data redundancy
QoS methods must have available geographical information of the BAN
nodes.
QoS is constant and should not be affected with network topology changes
due to link failures, node power failures, or different power management
mechanisms.
Large number applications with various QoS requirements.
QoS method should be equal effective during peak and low traffic periods.
The wireless links among the sensor nodes can be easily affected by
various environmental factors, shorter links appears to be more reliable
than longer links.
Medical care are mostly used in real-time WBANs system. They have high
requirements on bandwidth, delay guarantees and delivery time, packet
delivery, guaranteed medium access and also end-to-end delay guarantee.
High throughput, low delay and data redundancy, successful deliver
multimedia content.
Is very important in multimedia and real-time WSNs and WBANs. It is
usually reduced with different data aggregation technologies [26].
Otherwise, it should be taken into account in QoS methods.
6. QOS TECHNIQUES, MECHANISMS, AND M ETRICS NECESSARY TO BUILD EFFICIENT WBAN
For managing risks in medical applications it is important to properly handling QoS issues [27] [28] [29]. Reliability is
the key factor towards guaranteed delivery of data in reasonable time. It directly affects the quality of patient
monitoring; in other hand it can be disastrous when a life-threatening result has gone unobserved and undetected.
WBAN layers along with QoS metrics, techniques, and mechanisms which must be fulfilled at these layers [30] [31]
[32] [33] [34] [35] are described in Table 7 bellow.
Layers
Application
Layer
Transport
Layer
Table 7: WBAN layers along with QoS issues
QoS issues
QoS metrics, techniques, and mechanisms
It includes system lifetime,
response time, data novelty,
detection
probability,
data
reliability and data resolution.
It
includes
reliability,
bandwidth, latency, and cost.
Network Layer
It includes path latency, routing
maintenance,
congestion
probability, routing robustness
and energy efficiency.
Connectivity
Maintenance
Layer
it includes network diameter,
network capacity, average path
cost, connectivity, robustness
and connectivity maintenance
It includes coverage percentage,
coverage reliability, coverage
robustness,
coverage
maintenance.
Coverage
Maintenance
Layer
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Coverage, Exposure, Measurement errors, Optimum
number of active sensors.
Maximizing end-to-end reliability.
Bandwidth/throughput fairness.
Minimizing congestion probability.
Minimizing energy consumption.
QoS mechanisms are: Loss recovery, Congestion
control, Flow control, Source prioritization.
QoS metrics:
Minimizing path latency/delay,
Maximizing routing reliability, Minimizing energy
consumption, Minimizing congestion probability,
Providing effective sample rate.
Routing QoS techniques are: Minimum cost forwarding,
Energy aware routing, Maintaining low routing control
overhead,
In-network
data
aggregation
and
Differentiation routing:
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MAC Layer
It
includes communication
range, throughput, transmission
reliability, and energy efficiency
Physical Layer
It includes physical capabilities
impose resource
QoS metrics: Minimizing medium access delay,
Minimizing
collisions,
Maximizing
reliability.
Minimizing
energy
consumption,
Minimizing
interference and maximizing concurrency, Maximizing
adaptively to changes.
QoS mechanisms: Adaptation and learning, Error
control, Data suppression and aggregation, Power
control, Clustering, and Service differentiation
7. STUDY AND ANALYSIS OF EXISTING QOS BASED PROTOCOLS, TECHNIQUES AND MODELS
FOR WBAN
A superior number of QoS solutions specific for WSNs have been proposed by many researchers previously but these
solutions mainly focus on one or a few QoS features such as reliability, delay, bandwidth specification or reservation
[36]. For WBANs, researchers have shown little effort to provide QoS solutions. In this research paper we have studied
and analyzed existing QoS based WBAN techniques and models which are illustrated in the Table 8.
Existing QoS based
WBAN Model, and
Techniques
Improvements
to
CICADA
BodyQos
NGL03-6
Ad-hoc
wireless
network
e-emergency
QoS provisioning in
emergency
telemedicine
Mission-critical mhealth services with
some QoS constrain
A prototype system
for continual health
monitoring at home.
Ambulatory
monitoring
and
health care
AFTCS
Table 8: Existing QoS based WBAN techniques, and models
Main Features
Studied and analyzed the reliability issues and proposed some additional mechanisms to
improve the reliability [37]. These improvements will positively affect the throughput of
the network and lead to fewer retransmissions.
BodyQos [38] focused on three unique challenges: To use an asymmetric architecture
where most of the processing is done at the central device. To support a wide variety of
different MACs. An adaptive resource scheduling strategy is used in order to provide
statistical bandwidth guarantees as well as reliable data communication in WBANs.
Vergados et al. show different QoS requirements for medical data over the broadband
networks using the wireless DiffServ technology. Different biomedical measurements need
different sampling rate as well as service time and it introduces the need of QoS
provisioning in WBAN [39].
High reliability of message delivery technology is proposed [40].
Gama et al. present a low power real time (LPRT) protocol to fulfill the QoS requirements
of an e-Health care system. Authors discussed the need for QoS in wireless e-health and eemergency services [41].
An overview of the e-Health technology with QoS provisioning is presented in [42].
Mei et al. work on a mission-critical m-health services with some QoS constrain. End-toend delay, system availability and battery lifetime are considered as the key performance
matrices for the critical health care application [43].
Otto et al [44] present some of the key factors that could affect the performance of such a
network, thereby reducing the reliability of the WBAN.
Peiravi et al discuss a scheme where a set of sensors are connected to a central controller
node in a star topology, and the central controller node forwarding data to the personal
server. The researchers have shown that neither the controller nor the sensors would know
a failure in each other. Also the reliability of a sample WBAN is computed [45].
G. Wu et al explained that a high degree of reliability for critical data transmission is
required in body sensor networks (BSNs). An adaptive and flexible fault-tolerant
communication scheme for BSNs, namely AFTCS, is proposed. AFTCS adopts a channel
bandwidth reservation strategy to provide reliable data transmission when channel
impairments occur [46].
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WASP
Braem et al [47] present an autonomous spanning tree protocol called WASP (Wireless
Autonomous Spanning tree Protocol), to improve the reliability of multi-hop WBANs.
They identify the energy efficiency provided by employing multi-hop communication, and
present a slotted multi-hop approach to improve the medium access control and routing,
thereby improving the reliability of WBAN communication.
Low delay protocol
Latre et al [48] present a low delay protocol to improve communication among the sensors
and the sink node, thereby improving the reliability of data communication.
A. Willig et al give an introduction to the reliable data transport problem and surveys
protocols and approaches for this protocol [49].
Urgency based MAC protocol for WBAN, U-MAC, is a priority access mechanism to
allow sensor nodes with urgent health information contend for the channel more than the
nodes with non-urgent information [50]. The main consideration of the protocol is on the
system design. Based on the performance results, this protocol can help on adjusting the
critical node's packet retransmission times for supporting a certain number of critical
nodes with desired traffic arrival rate, or achieve certain arrival rate for a given number of
critical nodes.
Employing IEEE 8025.15.4 for QoS in WBAN [51] proposes a QoS provisioning
framework by employing IEEE 802.15.4 super frame structure in beacon enabled mode. It
defines four QoS parameters to specify the QoS requirements. Priority of the applications,
delay constraint, arrival rate, and the available burst size are considered. QoS for IEEE
802.15.4 based WBAN [52] also defines QoS provisioning scheme in IEEE 802.15.4 with
service differentiation and prioritization. It differentiates the traffic into different service
classes and prioritizes them.
For secure and authenticated data transfer, secure and QoS assurance scheduling scheme
is provided which further classify the traffic broadly into real time and non-real time in
terms of QoS parameters [53].
The scalable and robust MAC protocol is proposed for appropriate and accurate channel
sensing and another contention based method in CAP without carrier sense is discussed
[54].
DQBAN [60] uses fuzzy-logic decision technique based scheduling algorithm to improve
the overall performance and scalability [55].
PNP-MAC presents QoS in accordance with the priority of traffic. It also handles the QoS
requirements through preemptive slot allocation and non-preemptive transmission [56].
QoS based MAC protocol design for WBAN proposed in MedWin [57]. It also proposed
three types of access mechanism: scheduled access (1-periodic, m-periodic), improvised
access (polls and posts), and random access (CSMA/CA).
QoS based MAC protocol proposed in Inha for WBAN where traffic is first categorized
into three classes: emergency, normal, and on-demand [58].
IMEC-NL and Holst Centre proposed IMEC. IMEC proposed priority guaranteed MAC in
beacon enabled mode [59].
National Institute of Information and Communication of Japan proposed NICT [60],
IMEC-NL and Holst Centre proposed IMEC [59], Samsung Electronics proposed
Samsung [61], Fujitsu Laboratories of Europe Limited proposed Fujitsu [62], etc. All of
these protocols have claimed to be compatible with IEEE 802.15.6 QoS requirements.
Reliable
data
transport model
Urgency based MAC
protocol for WBAN,
U-MAC
Employing
IEEE
8025.15.4 for QoS in
WBAN
QoS
assurance
scheduling scheme
Scalable and robust
MAC protocol
DQBAN
PNP-MAC
MedWin [
Inha
IMEC
NICT [60], IMEC
[59], Samsung [61],
Fujitsu [62],
Some
Routing
protocols with focus
on
QoS:
SAR,
SPEED,
Energy
aware
Some Routing protocols such as Sequential Assignment Routing, Multi-path and multispeed routing protocol, an Energy-Aware QoS Routing Protocol with focus on QoS are
discussed [63].
8. OPEN RESEARCH ISSUES
After a long discussion and analysis we found that the fundamental QoS metrics for WBAN technology are:
Decreasing overall energy consumption.
Maximizing network lifetime.
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Maximizing network throughput.
Minimizing end-to-end delay.
Maximizing overall reliability.
Minimizing collisions
Minimizing congestion
Providing effective sample rate.
Finally, we generalize assembled a list of current sensor networks research problems, which provide more
opportunities and advantages of the WBANs systems. Along with the current problems of research, we encourage a
deeper understanding of the problems and a lot of more development in solutions to the open research problems, as we
have described in this paper.
Transport, network, data link, physical layer, application layer and MAC layer
Power control, mobility and task management planes
Distributed network and Internet access to sensors, controls, and processors
Data dissemination protocols
Security protocol
Information networking architecture
Framework for implementing adaptive energy-aware distributed microsensors
Cluster formation protocol
Laser communication from a cubic millimeter
Scalable coordination architectures for deeply distributed and dynamic systems
Routing and power aware sensor management
Distributed query processing
Mathematical framework that incorporates key features of computing nodes and networking elements
Computation is directly limited due to the limited amount of power. Typically, biosensors are not expected to have
the same computational power as conventional WSN nodes.
Material constraints are another issue for wireless sensor networks application to WBANs and healthcare
applications. A biosensor must be in contact with human body, or even on it. If the biosensor is inside a pill, the
choice of construction materials must be careful, especially on batteries. Also chemical reactions with body tissue
and the disposal of the sensor are of utmost importance.
The authors believe that the role of WBANs in medicine can be further enlarged. In the near future, the use of
WBANs will increase because smart spaces will be enabled with wireless sensor networks which can sense
environmental conditions and take preventive actions based on the presence of humans is those spaces. The system can
therefore reach ubiquity, where each individual would have a computational module able to seamlessly interact with the
smart space’s system and prevent health problems.
9. CONCLUSION
QoS has come forward as a foremost apprehension and research vicinity in the field of ad-hoc, sensor network, and
body sensor network applications such as WBAN. But at a standstill much work has to be done. We believe that there
should be further and more QoS definite WBAN research. To handle QoS challenges and issues in WBAN
predominantly to advance the general functionality there is also need more research on energy efficient MAC and
routing protocols. It’s also very important to monitor the QoS in body area sensor networks itself and we desire to take
account of it in our upcoming research work. It’s a huge research domain for us especially for academicians and
researchers to work for improving the performance level as well as QoS level in sense of in-body and out body WBAN.
REFERENCES
[1] Munir, S.A.; Yu Wen Bin; Ren Biao; Ma Man, "Fuzzy Logic Based Congestion Estimation for QoS in Wireless
Sensor Network," Wireless Communications and Networking Conference, 2007.WCNC 2007. IEEE, vol., no.,
pp.4336- 4341, 11-15 March 2007.
[2] http://cdn.intechopen.com/pdfs/9103/InTech-Wireless_body_area_network_wban_for_medical_applications.pdf
[3] http://www.ukessays.co.uk/essays/communications/the-emerging-wireless-body-area-network.php
[4] IEEE 802.15.6, Technical requirement documents (TRD), 15-08-0644-09-0006-tg6-technical-requirementsdocument
Volume 2, Issue 4, April 2013
Page 231
Web Site: www.ijaiem.org Email: editor@ijaiem.org, editorijaiem@gmail.com
Volume 2, Issue 4, April 2013
ISSN 2319 - 4847
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25]
[26]
[27]
[28]
[29]
[30]
[31]
[32]
[33]
[34]
[35]
eksandar, Sanders Corey, Jovanov Emil, “System Architecture Of A Wireless Body
Area Sensor Network For Ubiquitous Health Monitoring”, Journal Of Mobile Multimedia, Vol.1, No.4 (2006)
307-326© Rinton Press
http://zeitgeistlab.ca/doc/Advanced_WBANs_for_an_Ageing_e-Health_Society.html
Huasong Cao and Victor Leung, Cupid Chow and Henry Chan “Enabling Technologies for Wireless BodyArea
Networks: A Survey and Outlook”, IEEE Communications Magazine , December 2009
http://www.ieee802.org/15/pub/TG6.html
http://www.cse.wustl.edu/~jain/cse574-08/ftp/ban/index.html
B. Zhen, H.-bang Li, and R. Kohno, “Networking issues in medical implant communications,” International
Journal of Multimedia and Ubiquitous Engineering, vol. 4, no. 1, 2009.
M.Arif Siddiqui, Shah Murtaza Rashid Al Masud, “Towards Design of Novel Low Power MAC Protocol for
Wireless Body Area Networks”, http://www.svpublishers.co.uk/#/ijcis-apr-2012/4564734051, issue 4, volume 4,
2012
http://pdf.aminer.org/000/369/962/qos_support_in_wireless_sensor_networks_a_survey.pdf
http://www.pcmag.co.uk/networkitweek/features /2059634/jargon-buster
http://newsroom.cisco.com/dlls/2004/hd_051904c.html
Feng Xia, Wenhong Zhao, Youxian Sun and Yu- Chu Tian. Fuzzy Logic Control Based QoS Management in
Wireless Sensor/Actuator Networks, Sensors, vol.7, no.12, pp. 3179-3191, 2007.
Aura Ganz, Zvi Ganz, Kitti Wongthavarawat, “Multimedia Wireless Networks: Technologies, Standards, and
QoS”, Prentice Hall PTR, September 2003, pp.37-38.
Gang Zhou, Jian Lu, Chieh-Yih Wan, Mark D. Yarvis, and John A. Stankovic, "BodyQoS: Adaptive and RadioAgnostic QoS for Body
Okundu Omeni, Alan Chi Wai Wong, Alison J. Burdett, and Christofer Toumazou, “Energy Efficient Medium
Access Protocol for Wireless Medical Body Area Sensor Networks”, IEEE Transactions on Biomedical Circuits
and Systems, Vol. 2, No. 4, December 2008.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231450/
Joel JPCR, Pereira OE, Neves PCS. Biofeedback data visualization for body sensor networks. J. Netw. Comput.
Appl. 2011;34:151–158.
Chen, M., Gonzalez, S., Vasilakos, A., Cao, H., & Leung, V. C. M. “Body Area Networks: A survey,” Mobile
Networks and Applications, vol. 16, 2011, pp. 171-193, doi:10.1007/s11036-010-0260-8.
Jang, C. S., Lee, D. G., Han, J.-W., & Park, J. H.. “Hybrid security protocol for wireless body area networks,”
Wireless Communications and Mobile Computing, vol. 11, 2011, pp. 277-288, doi: 10.1002/wcm.884.
Latré, Benoît, Bart Braem, Ingrid Moerman, Chris Blondia, and Piet Demeester. “A survey on wireless body area
networks,” Wireless Networks, vol. 17, 2010, pp. 1-18, doi: 10.1007/s11276-010-0252-4
Xia F. QoS Challenges and Opportunities in Wireless Sensor/Actuator Networks. Sensors 2008; 8: 1099-12.
Chen J, Díaz M, Llopis L, Rubio B, Troya JM. A Survey on Quality Of Service Support in Wireless Sensor and
Actor Networks: Requirements and Challenges in the Context of Critical Infrastructure Protection. Journal of
Network and Computer Applications 2011; 34: 1225-15.
Cheng C, Tian B, Li Y, Yao O. Data Aggregation Technologies of Wireless Multimedia Sensor Networks: A
Survey. Proceedings of the 2010 IEEE International Conference on Vehicular Electronics and Safety. QingDao,
China, July 15-17, 2010.
B. Zhen, H.-bang Li, and R. Kohno, “Networking issues in medical implant communications,” International
Journal of Multimedia and Ubiquitous Engineering, vol. 4, no. 1, 2009.
M. Ameen, A. Nessa, and K. S. Kwak, “QoS Issues with Focus on Wireless Body Area Networks,” in 2008 Third
International Conference on Convergence and Hybrid Information Technology, 2008, pp. 801-807.
C. Li, H.-B. Li, and R. Kohno, “Performance Evaluation of IEEE 802.15.4 for Wireless Body Area Network
(WBAN),” in 2009 IEEE International Conference
Chen D, Varshney PK. QoS Support in Wireless Sensor Networks: A survey. Proceedings of the 2004
International Conference on Wireless Networks. Las Vegas, USA, June 21-24, 2004.
Yigitel MA, Incel OD, Ersoy C. QoS-aware MAC Protocols for Wireless Sensor Networks: A survey. Computer
Networks (Elsevier) 2011; 55: 1982-23.
Ehsan S, Hamdaoui B. A Survey on Energy-Efficient Routing Techniques with QoS Assurances for Wireless
Multimedia Sensor Networks. IEEE Communications Surveys & Tutorials 2011; 99: 1-14.
Djenouri D, Balasingham I. Traffic-Differentiation-Based Modular QoS Localized Routing for Wireless Sensor
Networks. IEEE Transactions on Mobile Computing 2011; 10: 797-13.
Wang C, Li B, Sohraby K. In: Zhenog J, Jamalipour A, Eds. Transport Protocols and Quality of Service. New
York: John Wiley & Sons, Inc. 2009: 343-26.
Munishwar VP, Tilak SS, Abu-Ghazaleh NB. In: Misra S, Woungang I, Misra SC, Eds. Congestion and Flow
Control in Wireless Sensor Networks. London: Springer 2009: 205-24.
Volume 2, Issue 4, April 2013
Page 232
Web Site: www.ijaiem.org Email: editor@ijaiem.org, editorijaiem@gmail.com
Volume 2, Issue 4, April 2013
ISSN 2319 - 4847
[36] D. Chen and P. K. Varshney, \Qos support in wireless sensor networks: A survey," in Int. Conference on Wireless
Networks (ICWN 2004). CSREA Press, June 2004.
[37] B. Braem, B. Latr_e, C. Blondia, I. Moerman, and P. Demeester, Improving reliability in multi-hop body sensor
networks," in Second International Conference on Sensor Technologies and Applications ( SENSORCOMM
2008), Cap Esterel, France, 25-31 August 2008, pp. 342-347.
[38] G. Zhou, J. Lu, C.-Y. Wan, M. Yarvis, and J. Stankovic, Bodyqos: Adaptive and radio-agnostic qos for body
sensor networks," April 2008, pp. 565-573.
[39] D. Vergados, D. Vergados, and I. Maglogiannis, “Ngl03-6: Applying wireless diffserv for qos provisioning in
mobile emergency telemedicine,” in Global Telecommunications Conference, 2006. GLOBECOM ’06. IEEE, nov.
2006, pp. 1 –5.
[40] U. Varshney and S. Sneha, “Patient monitoring using ad hoc wireless networks: reliability and power
management,” in Communications Magazine, IEEE, vol. 44, no. 4, apr. 2006, pp. 49 – 55.
[41] O. Gama, P. Carvalho, J. A. Afonso, and P. M. Mendes, “Quality of service support in wireless sensor networks
for emergency healthcare services,” in Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th
Annual International Conference of the IEEE, aug. 2008, pp. 1296 –1299.
[42] A. Zvikhachevskaya, G. Markarian, and L. Mihaylova, “Quality of service consideration for the wireless
telemedicine and e-health services,” in Wireless Communications and Networking Conference, 2009. WCNC
2009. IEEE, apr. 2009, pp. 1 –6.
[43] H. Mei, B.-J. van Beijnum, I. Widya, V. Jones, and H. Hermens, “Enhancing the performance of mobile
healthcare systems based on task-redistribution,” in INFOCOM Workshops 2008, IEEE, apr. 2008, pp. 1 –6.
[44] C. Otto, A. Milenkovic, C. Sanders, E. Jovanov, “System Architecture of a Wireless Body Area Sensor Network
for Ubiquitous Health Monitoring,” In Journal of Mobile Multimedia, vol. 1, no. 4, pp. 307- 326, 2006.
[45] A. Peiravi, M. Farahi, “Reliability of Wireless Body Area Networks used for Ambulatory Monitoring and Health
Care,” In Life Science Journal, Vol. 7, No. 2. 2010.
[46] G. Wu, J. Ren, F. Xia, Z. Xu, “An Adaptive Fault-Tolerant Communication Scheme for Body Sensor Networks,”
In Sensors 2010, 10, pp. 9590-9608. DOI: 10.3390/s110201383.
[47] B. Braem, B. Latre, I. Moerman, C. Blondia, P. Demeester, “The Wireless Autonomous Spanning tree Protocol for
Multiple Hop Wireless Body Area Networks,” In Proceedings of the First International Workshop on Personalized
Networks, 2006, pp. 284-291, July 2006, DOI: 10.1109/MOBIQW.2006.361753.
[48] B. Latre, B. Braem, I. Moerman, C. Blondia, E. Reusens, W. Joseph, P. Demeester, “A Low-delay Protocol for
Multihop Wireless Body Area Networks,” In Proceedings of MobiQuitous 2007: Fourth Annual International
Conference on Mobile and Ubiquitous Systems: Networking & Services, 2007, pp. 1-8, August 2007. DOI:
10.1109/MOBIQ.2007.4451060.
[49] A. Willig, H. Karl, “Data Transport Reliability in Wireless Sensor Networks — A Survey of Issues and
Solutions,” In Praxis der Informationsverarbeitung und Kommunikation, vol. 28, pp. 86-92, April 2005.
[50] K. Ali, J. Sarker and H. Mouftah, "Urgency-based mac protocol for wireless sensor body area networks," in
Communications Workshops, pp.1-6, May.2010.
[51] H. Cao, S. Gonza andlez Valenzuela and V. Leung, "Employing ieee 802.15.4 for quality of service provisioning
in wireless body area sensor networks," in Proc. of Advanced Information Networking and Applications, pp.902909, Apr.2010.
[52] J. Garcia and T. Falck, "Quality of service for ieee 802.15.4-based wireless body sensor networks," in Proc. of
Pervasive Computing Technologies for Healthcare, pp.1-6, Apr.2009.
[53] M. Barua, M. Alam, X. Liang and X. Shen, "Secure and quality of service assurance scheduling scheme for wban
with application to ehealth," in Proc. of Wireless Communications and Networking Conference, pp.1102-1106,
Mar.2011.
[54] C. Li, L. Wang, J. Li, B. Zhen, H.-B. Li and R. Kohno, "Scalable and robust medium access control protocol in
wireless body area networks," in Indoor and Mobile Radio Communications, pp.2127-2131, Sept.2009.
[55] B. Otal, L. Alonso and C. Verikoukis, "Highly reliable energy-saving mac for wireless body sensor networks in
healthcare systems," in Journal Selected Areas in Communications, vol.27, no.4, pp.553-565, May.2009.
[56] J. Yoon, G.-S. Ahn, S.-S. Joo and M. Lee, "Pnp-mac: Preemptive slot allocation and non-preemptive transmission
for providing qos in body area networks," in Proc. of Consumer Communications and Networking Conference,
pp.1-5, Jan.2010.
[57] 15-09-0326-00-0006-medwin-mac-and-security-proposalpresentationpart- 1-mac.
[58] 15-09-0366-01-0006-inha-mac-proposal.
[59] 15-09-0341-01 -0006-imec-narrowband-mac-proposalpresentation.
[60] 15-09-0346-01-0006-nict-s-mac-proposal.
[61] 15-09-0315-01 -0006-samsung-mac-proposal-part- 1-apower-efficientmac- for-ban.
[62] 15-09-0286-01-0006-fujitsu-partial-phy-mac-proposal.
Volume 2, Issue 4, April 2013
Page 233
Web Site: www.ijaiem.org Email: editor@ijaiem.org, editorijaiem@gmail.com
Volume 2, Issue 4, April 2013
ISSN 2319 - 4847
[63] Annette Böhm, “State of the Art on Energy- Efficient and Latency-Constrained Networking Protocols for Wireless
Sensor Networks”, Technical Report, IDE0749, June 2007.
AUTHOR
Shah Murtaza Rashid Al Masud is a lecturer at the faculty of Computer Science and Information Systems, Najran
University, Najran, KSA. He received his M.Sc and B.Sc in Computer Engineering in the specialization of Computer
intellect systems and networks in 2000, and 2001 respectively from Khrakov State University of Radio Electronics,
Kharkov, Ukraine. His current research interest include parallel and distributed systems, GIS, GRID, Cloud computing,
wireless BAN, expert systems, fuzzy logic, physical computation and thermodynamics, reversible logic, , and quantum
computation. He has also published papers in accredited national and international journals and conference
proceedings. Besides that, he also serves as a reviewer for various conferences and journals. Currently he is the member
in various academic and scientific organizations.
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