International Journal of Computer Information Systems,
Vol. 3, No. 2, 2011
Comparative Study and Design of a Multihop Protocol in a Wireless Body Area
Network towards Energy Efficiency
1
D.V.Srihari, 2 T.Ravi Kumar, 3 V.Karunakar Reddy, 4 K.Naresh
1
Assoc. Professor Dept. of ECE, SKTRM College of Engineering, Kondair, MBNR (Dt.), A.P,
Student, M.Tech(ECE), Dept. of ECE,SKTRM College of Engineering, Kondair, MBNR (Dt.), A.P,
3
Student, M.Tech(ECE), Dept. of ECE, SKTRM College of Engineering, Kondair, MBNR (Dt.), A.P,
4
Student, M.Tech(ECE), Dept. of ECE,SKTRM College of Engineering, Kondair, MBNR (Dt.), A.P.
2
Abstract : - Wireless Body Area Networks (WBANs) have
characteristic properties that should be considered for
designing proper network architecture. Low quality wireless
links, and demand for a robust data transmission scheme at
low energy are important issues in WBANs. Using ultra low
power wireless transceivers to reduce power consumption
causes a limited transmission range. This implies that a multihop protocol is a better design choice. In this paper we design
and compare a basic multihop scheme against a single-hop
protocol stack in a duty cycling MAC and other conditions to
analyse the effect such changes have on the throughput. It is
our goals here to improve the throughput by using lesser
transmit power and a better routing mechanism. The discrete
simulation framework Omnet++ was used to design the
algorithm and conduct the experiments.
Keywords : Wireless Body Area Network, Omnet++.
I. INTRODUCTION
A Wireless Body Area Network (WBAN) consists of tiny
sensor nodes that measure the vital signals of the body, such
as blood pressure, fever, heart beat rate, and movement
activities. The information is relayed to a gateway node on
the body and then to a base station for further analysis.
Important issues to be considered while designing a network
architecture and protocol stack for this kind of wireless
networks are as follows –
1. Power constraint and short RF transmission range: The
power and size constraints of body sensors are tighter than in
other wireless sensor applications. A short transmission
range is a common limitation of low-power RF transceivers.
Therefore the amount of consumable energy is strictly
limited.
2. Low quality of wireless links: Several investigations using
simulations and experiments show that the propagation loss
around and in a human body is considerably high.
3. The general conclusion is that wireless links in WBANs
are more unreliable than in other Wireless Sensor Networks.
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II. PROTOCOL STACK DESIGN FOR WBAN
The challenges in WBANs demand particular attention while
designing an appropriate protocol stack. On the other hand,
the limited network size provides opportunities to relax some
constraints on the protocol. To realize an appropriate
protocol stack, we use a multihop ring based mechanism for
data routing on top of a duty-cycled MAC layer. Assume that
there are 6 sensor nodes deployed on a body each with a
unique ID from 0 to 5.All these nodes are of the same type.
The nodes are #0 at right hip , #1 at left wrist , #2 at right
wrist,#3 at left ankle,#4 at right ankle, #5 at chest. A path
loss map is constructed based on empirical measurements on
a WBAN. The protocol stack design follows a layered
model. The application layer consists of a “throughputTest”
model where all nodes send packets to a sink/hub node at a
constant (configurable) rate. The hub is node 0. The network
layer consists of a multihop mechanism for data
transmission. The MAC layer implements a simple CSMA
mechanism where duty cycle and some other parameters can
be controlled.
III. DATA ROUTING USING A MULTIHOP APPROACH
In this algorithm, nodes do not have a specific parent. A node
just gets a level number (or ring number) during setup. The
first setup packet sent from the sink has level 0.Any node
that receives it adds 1 to the level and retransmits it. The
process continues with every node adding 1 to the level of
the received packet. Eventually all connected nodes will have
a level number (there is also a possibility for unconnected
nodes). When a node wants to send a packet to the sink it
does not send it to a particular node but rather broadcasts it,
attaching its level number. Any node with a smaller level
number will rebroadcast it. The process continues until the
sink is reached.
Therefore the creation of multiple paths to the sink node
provides robustness to the routing strategy. In comparison to
single route algorithms this is quite reliable but if traffic
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International Journal of Computer Information Systems,
Vol. 3, No. 2, 2011
passes a certain threshold, congestion will affect the
performance.
Table 1 shows the configuration for the WBAN. In addition
TX Power levels, a delay transition matrix, and a power
transition matrix are also defined.
As seen with -10dBm maximum throughput is achieved.
Range is normally in (93, 99) percent. With -12dBm
throughput range is (90,100) percent .With -15dBM
throughput range is (83.5, 99) percent .With -20dBM
throughput range is (70, 98.7) percent One can observe that
between nodes 0 & 2, throughput is very high in all cases i.e.
between (R-hip & R-wrist). Between 0 and 4, throughput on
average is 234(R-hip & R-ankle) and between 0 and 1,
throughput on average is 229.5(R-hip & Lwrist). Therefore
these are the links with best quality throughput in the system.
Setting up paths using the above 3 links may therefore
decrease the overall energy consumption of the network.
In comparison to 0-4 link, the 0-1 link falls drastically when
power is reduced to -20dBm.This fall may be due to the
distance between the 2 nodes.
The energy consumption varies little at 0.158 Joules.
In 50 seconds each node sends 249 packets to node-0.So total
number of packets sent to node-0 is 249*5=1245 packets. On
an average, as TxOutputPower decreases average throughput
varies between (205,242).So at -10dBm throughput is 97%
whereas at -20dBm throughput has fallen to 82.3%.The
objective would therefore be decreasing this
range by better mechanisms.
The average energy consumption is therefore 0.158 joules for
the network. The total energy consumption is 0.158*6=0.948
Joules in 51 seconds. The table shows that the energy
consumed by all nodes is uniform.
The receiver node-0 listens all the time so it consumes
3.1mW * 51sec =0.1581 Joules.
The sender nodes draw either 2.93mW (when transmitting)
or 3.1mW (when just listening), to find the energy we need
to know what percentage of the total time are they
transmitting.
We see that each sender node sends 5 packets per second.
And the default size for packets = 130bytes = 1040 bits. At
1024Kbps data rate, a packet transmission takes
approximately 1ms.
So only 5msec out of a second is a sender node in TX mode.
This means that the total energy consumption of a sender
node is: (0.005*2.93mW + 0.995*3.1mW) *51 sec =
0.15805 Joules
The total energy consumed for the network is given by
[(Time*TrasmitPower+Time*TransitionPower+Time*IdleLi
st ening_Power)*No. of Nodes].
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International Journal of Computer Information Systems,
Vol. 3, No. 2, 2011
The transition time is 20micro seconds per transition, so it is
0.2msec in a second where 5 transmissions happen. The
transition power is 3mw (in between 2.93 and 3.1) so the
effect at the end energy number is extremely less.
It is important to note here that energy consumption in the
network should not be skewed leading to premature death of
some nodes with maximum load. Therefore energy
consumption should be properly distributed across all nodes.
Therefore it helps if there are nodes that periodically load
balance the packet distribution process.
As per simulations above , it can be seen that with dutycyle
as 1.0, energy consumption always remains constant and it
never decreases, instead the throughput gets affected due to
interference and fading of packets.
Therefore the key to minimizing energy consumption of a
node is by tuning the duty cycle and thereby minimizing idle
listening.
The next few experiments show the results of the various
duty cycles:-
The above table shows that on an average the energy
consumption per node has decreased after duty cycling the
MAC.
Therefore while designing the protocol stack our main
objectives would be –
1) Building a packet dissemination mechanism that can yield
a high throughput than the baseline above, for a duty cycle of
1.0 and with the minimum TxOutputPower i.e. -20dBm.
2) The next step would be to devise a strategy that does not
affect the throughput much yet can work with the least duty
cycle of 0.2.
By our multi-hop mechanism, we now improve the
throughput as below –
As seen with duty cycle as 1.0, the results are the same as
earlier cases. With anything below 0.8, the throughput drops
extremely low. The best among these values is 132.8 at 0.6
duty cycle and -10dBm power.
On duty cycling the MAC, beacon packets are sent before
data. This increases the packet flow in the network
increasing chances of collision. Also as the duty cycle is
decreased the beacons increase.
So the single hop throughput range of (205,242) was now
improved by having an 86.3% improvement as compared to
the earlier 82%. Also more robustness is now achieved since
at all power levels throughput has increased by a multi-hop
approach. This is because multiple paths to the sink are now
possible.
The average energy consumption still remained as 0.158
Joules since the experiment was done with a duty cycle of
1.0.
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International Journal of Computer Information Systems,
Vol. 3, No. 2, 2011
Therefore with a multi-hop approach the robustness and
reliability was dealt with at the routing layer with the same
energy consumption as the single hop approach.
V. CONCLUSIONS
This paper has presented a basic study and design factors to
be taken into consideration towards energy efficiency
improvement for a WBAN.
While designing the protocol stack our main objectives were
as follows –
• To build a packet dissemination mechanism that can yield a
high throughput than the baseline above, for a duty cycle of
1.0 and with the minimum TxOutputPower i.e. - 20dBm.This
was achieved by the multihop protocol as described earlier.
• As future work, the next step would be to devise a strategy
that does not affect the throughput much, yet can work with
the least duty cycle of 0.2.For this, adjustments towards the
MAC layer are still required.
2].
T.Ravi
Kumar,
Student
M.Tech(ECE), SKTRM College of
Engg & Tech., Dept .of ECE, Kondair,
A.P.
His research interests in areas of
Computer
Networks,
Mobile
Computing, DSP, MATLAB, Data
Mining, Sensor Networks. He attend so many Workshops
and National & International Conferences
3]. V.Karunakar Reddy, Student
M.Tech(ECE), SKTRM College of Engg
& Tech., Dept .of ECE, Kondair, A.P.
His research interests in areas of
Computer
Networks,
Mobile
Computing, DSP, MATLAB, Data
Mining, Sensor Networks. He attend so
many Workshops and National &
International Conferences
REFERENCES:
[1] OMNeT++ website. http://www.omnetpp.org.
[2] B. Braem et al. The wireless autonomous spanning tree
protocol for multihop wireless body area networks. In Proc.
of 3rd Int’l Conf. on Mobile and Ubiquitous Systems
(MobiQuitous), pages 284–291. IEEE, July 2006.
[3]E. Jovanov et al. A wireless body area network of
intelligent motion sensors for computer assisted physical
rehabilitation. In Journal of NeuroEngineering and
Rehabilitation, pages 2–6, March 2005.
. atr et al. A low-delay protocol for multihop wireless
body area networks. In Proc. 4th MobiQuitous, pages 1–8.
IEEE, 2007.
5 David . Johnson and David A.Maltz, “Dynamic source
routing in Ad hoc wireless networks”. In Mobile Computing,
edited by Tomasz Imielinski and Hank Korth, chapter 5,
pages 153-181. Kluwer Academic Publishers, 1996.
[6] A. Natarajan et al. Investigating network architectures for
body sensor networks. In Proc. of the 1st ACM SIGMOBILE
Int’l workshop on Systems and networking support for
healthcare and assisted living environments, pages 19–24.
ACM, 2007.
4].K.Naresh, Student M.Tech(ECE),
SKTRM College of Engg & Tech., Dept
.of ECE, Kondair, A.P.
His research interests in areas of
Computer Networks, Mobile Computing,
DSP, MATLAB, Data Mining, Sensor
Networks. He attend so many Workshops
and National & International Conferences.
AUTHORS PROFILE:
1].D.V.Srihari, M.Tech(ECE), Assoc.
Professor, SKTRM College of Engg &
Tech., Dept .of ECE, Kondair, A.P.
His research interests in areas of
Computer
Networks,
Mobile
Computing, DSP, MATLAB, Data
Mining, Sensor Networks. He attend so
many Workshops and National & International Conferences.
August Issue
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ISSN 2229 5208