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T-TMAC: Energy Aware Sensor MAC Protocol for
Health-care Monitoring

Youssouf Zatout1,2, Eric Campo1,2and Jean-Fran?ois Llibre1,3
1Universit? de Toulouse; UPS, INSA, INP, ISAE, UTM, F-31703 Blagnac, France

2CNRS; LAAS; 7 Avenue du Colonel Roche, F-31077 Toulouse, France
3CNRS; LAPLACE; 2 rue C. Camichel, F-31071 Toulouse, France

{zatout,campo,llibre}@iut-blagnac.fr

Abstract?Wireless sensor networks (WSN) have received
much attention during the last few years especially with regard
to energy consumption. Many Medium Access Control (MAC)
protocols were proposed to minimize the energy consumption
in WSN, however they cannot be applied in all application
contexts. Healthcare monitoring is an important application
requiring adapted MAC protocol. This paper presents a new
MAC protocol, called T-TMAC, based on simple mechanisms
that organize data exchange and reduce collisions in many-to-one
architecture. It includes maintenance mechanisms that permit
mobility management and topology reconfiguration, which are
needed for healthcare. We evaluated the performance of the
protocol by analytical model. We propose also real prototyping
using Imote2 platforms. We studied the impact of position
of nodes and sleep modes on energy and delay. The results
emphasize the interest of the protocol.

Index Terms?Wireless Sensor Network (WSN), Healthcare
Monitoring, MAC Protocol, Energy Saving, Performance Evalu-
ation.

I. INTRODUCTION

Over the past decade, the aging of population has lead to
an increasing of the elderly [1]. Therefore the number of frail
or dependent people has grown steadily in the world. The
deployment of new systems which reduce the hospitalization
costs by maintaining people at home is a real challenge.
Nowadays, new remotely managed systems and domestic
devices (sensors and actuators) are being developed [2, 3] to
facilitate and improve the quality of healthcare at home, and
to reduce the cost of this dependence.

Wireless sensor network (WSN) is a promissing technology
for a wide range of potential applications including healthcare
monitoring [6]. In fact, they are characterized by their ease of
deployment and their self-organization, which is an advantage
for monitoring persons with risks and their living environment.
Their benefits for healthcare include: continuous recovery
of physiological data, medication management, motions and
shocks detection (fall of a person), localization, diagnosis
and early intervention for various diseases, observation of the
living environment (recording the activities), monitoring of
health status during training and sports, etc.

Wireless sensors are usually powered by batteries with
limited capacity and the autonomy varies widely following
the use. Replacing / recharging the batteries by the elderly
/ patients can be difficult (large number of sensors, etc.),
expensive (charging forgotten), and sometimes impossible

(particularly for intra body sensors). The ideal would be to
extend their lifetime for several months or even for few years,
to collect and relay medical data permanently to a management
center or to a remote medical center (hospitals or doctors).

Many works were conducted to extend the lifetime of sensor
nodes using techniques of recovering energy from ambient
sources such as solar (photovoltaic) and vibrational energy
[4]. However, the energy recovered (in home environment)
stills limited and must be extended by other effective means.

Furthermore, many energy conservation techniques reducing
power consumption of sensors are proposed at each layer in
the networking stack: from the physical layer and modulation
techniques, to the application layer and the development of
specialized power-control tools [5]. In this paper we focus on
energy-efficient MAC layer. The rest of the paper is organized
as follows: related work is presented in Section II. We describe
the protocol and its principle phases in Section III. We provide
the analysis and the implementation of our protocol in sections
IV and V. We conclude the paper in Section VI.

II. DESIGN OF MAC PROTOCOLS

Reducing power consumption at the MAC layer can be very
significant [3, 5, 6, 7]. Approaches at this layer turn the wire-
less transceivers off when it is not necessary to transmit or to
receive data. Several protocols based on this mechanism have
been developed under IEEE-802.15.4 standard [8]. However,
this technique requires a mechanism that synchronizes sensors
between each other and organizes data exchanges.

They are three main categories of MAC protocols: con-
tention based protocols such as: B-MAC, S-MAC and
WiseMAC [9-11]; TDMA based protocols such as TRAMA
[12], and Hybrid protocols such as Z-MAC [13]. In this paper,
we present a MAC protocol that combines the strengths of
slotted and contention channel access, while offsetting their
weaknesses for healthcare monitoring needs.

In [14], we developed a possible runway based on the ?event
driven? approach. Simulation results showed on the one hand
its advantages in terms of the early detection of anomalies
and emergencies. On the other hand, they showed some limi-
tations regarding to energy consumption. In [15], we presented
a primary mobility aware protocol based on ?sleep/active?
mechanism. In this paper, we extend this approach by two
key elements: a) Improving maintenance mechanisms, b) Real
prototyping of the protocol.

978-1-4673-1881-5/12/$31.00 ?2012 IEEE
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III. T-TMAC PROTOCOL DESIGN

A. Assumptions and Network Architecture

We propose a heterogeneous and centralized WSN archi-
tecture described in Figure 1. The sensor nodes are organized
into groups: Medical (M ), Coordinator (C), Video (V ) and
Sink (S). The network architecture is composed of three
tiers (Each tier has its own characteristics and requirements):
(M, C), (C, V ) and (V, S). A sensor node may interact with
other nodes in inter-tiers or intra-tiers to achieve the common
goal (healthcare monitoring). This type of architecture offers
many advantages in terms of capacity, coverage, and reliability
compared to single tier Ad hoc networks as described in [16].
Medical nodes collect and relay physiological medical data
(temperature, ECG, etc.), and Video nodes collect and relay
ambient data (image, humidity, etc.).

V

V

V

V

V

V

S

M
M

M
M

C

WBAN 1 WBAN 2

Wireless link

M

V

C

S

Medical node

Coordinator node

Video node

Sink node

Mobility

Figure 1. Global network architecture for healthcare monitoring at home

We summarize below the main characteristics retained for
this architecture: (i) Low density of sensors: the deployment
area of the global network is relatively small; we are con-
ducting this study in the case of a house. (ii) The Wireless
Body Area Network (WBAN) has a cluster / star topology
that consists of (M) and (C) nodes. (iii) Video nodes are
stationary, while the WBAN nodes are mobile. (vi) Video
nodes act as relay nodes (forwarding data received by (C)).
(vii) The traffic pattern is periodic: “many-to-one” (from the
bottom to the top (M ) ? (C) ? (V ) ? (S), managed
by the Sink. The data flow is initiated by (M ) node. (v)
(C) node is associated with only one video node at a time
following multi-hop transfer to reach the Sink. Thereafter, we
propose the appropriate mechanism for mobility management.
To enhance the lifetime of sensors, three principle assumptions
are considered.

? Data aggregation: (C) node aggregates medical data
of its WBAN, (V ) node can aggregate data from multiple
Coordinators within range.

? Power tuning: we propose to adjust the power transmission
(TPL: Transmission Power Level) of each sensor node in
the architecture while maintaining hop-by-hop connectivity
between: (M ), (C), (V ) and (S), as shown in Figure 1. This
leads not only to limit the over-consumption of energy but can
also leads to limit interferences between nodes [5].

? Sleep / active schedule: nodes operate under activity /
inactivity mode. (M ) and (V ) nodes can turn off their radio
during sensing data.

B. Structure of T-TMAC

To organize the data exchange between sensors in the
three tier network we propose simple mechanisms that fit the
application needs. The sensors of each level follow a dynamic
scheduling (on / off). They wake up when needed and sleep
the rest of the time. The scheduling is organized level by level
as follows: in level 1 between Medical nodes (M ) and their
associated Coordinator (C), in level 2 between Coordinators
(C) and Video (V ), and finally in level 3 between Video nodes
(V ) and Sink (S).

1) T-TMAC Superframe: We consider an access method
close to the IEEE-802.15.4 protocol with some modifications.
Indeed, we adapt the parameters setting of the Superframe
according to the requirement of each tier taking into account
the sleep / active scheduling. In the first tier, the commu-
nications between (C) and (M ) nodes are organized into
Superframes managed by the coordinator. The Superframes
are delimited by Beacons sent by the coordinator, within it
provides information about synchronization, GTS (Guaranteed
Time Slot) allocation, etc. The first Superframe (Superframe 0)
may not contain CFP (Contention Free Period). In fact, there
will be only CAP (Contention Access Period) for initialization
(cf. section 2) where medical nodes compete to associate to the
Coordinator and reserve some GTSs (cf. section 4). The other
Superframes (1 to n) contain only CFP period and remove the
CAP. Figure 2 shows the parametrized Superframe.

B

CFP CAP

Superframe nGTS

B

CFP CAP

Superframe 1GTS

?.

Figure 2. T-TMAC Superframes

The number of reserved GTS depends on the type and the
length of data. In the CAP period (called later ?Reporting?
period), the coordinator sends the collected data to (V ) node
to which it is associated. This later, reports data to the Sink.
During this period, medical nodes can turn off their radios
(sleep mode).

2) Principle phases of the protocol:
Initialization: Its principle role is to synchronize the four

groups of heterogeneous nodes between each other for mutual
recognition, and to organize data transmission that will be used
in the data collection phase. During this phase, the network
is created level by level according to a top-down messages
transfer from (S) to (M ). At the end of network creation,
collection phase begins in bottom-up sense from (M ) to (S)
with periodic data transfer.

Data Collection and topology reconfiguration: This phase
takes place immediately after the topology creation. It rep-
resents the crucial phase of the protocol. In one hand it
allows relaying medical data hop by hop to reach the Sink,
according to the schedule defined in the creation phase. In
other hand, it includes mechanisms for topology maintenance
and reconfiguration (cf. section C).

3) Organization of Data Exchange: Both phases operate
in different ways. Figure 3 describes for each data flow,
the different messages exchanged between active nodes per

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level. Initially, the Sink node initiates the topology creation by
sending “S_Beacon” message to Video (V ) node. This later
sends an association request message “ASC_RQ” to the Sink,
which accepts the request by sending “ASC_ACK” message.
Thus, the node (V ) is associated with the Sink. Then, the
association between (V ) and (C) nodes begins. The node
(V ) sends “B_Beacon” message to node (C), followed by the
exchange of “ASC_RQ” and “ASC_ACK” messages whose
finalize their association. Then the initialization of the WBAN
network starts between (M ) and (C) nodes with the exchange
of “C_Beacon”, “ASC_RQ” and “ASC_ACK” messages. After
setting up the WBAN network, the data collection begins.
The node (M ) collects data, builds the first data message
“DATA” and sends it to its associated Coordinator (C). Then
(C) responds with acknowledgment message “ACK”. “DATA”
message will be then relayed by (C) to (V ), and finally
relayed by (V ) to the Sink (S), with the exchange of “DATA”
and “ACK” messages. As shown in Figure 3, after receiving
the “ACK” message, nodes can turn to sleep mode to save
energy.

Sink V C M

S_Beacon

ASC_RQ

ASC_ACK

S_Beacon

ASC_RQ

ASC_ACK

B_Beacon

ASC_RQ

ASC_ACK

C_Beacon

ASC_RQ

ASC_ACK

C_Beacon

DATA

ACK

B_Beacon

DATA

ACK

S_Beacon

DATA

ACK

Topology creation
phase

Data collection and
reconfiguration phase

Sleep mode

Active mode

Start of data
collection of (M)

Level 1Level 2Level 3

DATA Reporting

Figure 3. Principle mechanisms of the protocol

? Medium access: to minimize collisions in the three tier
architecture we manage the medium access as follows: we
use ?Data reporting? period to manage ?inter-tier? interactions
between nodes belonging to different levels (nodes report data
(by level) as shown in Figure 3. However, it is necessary, to
assign the appropriate access method to minimize collisions
between nodes belonging to the same level. In fact, we propose
a hybrid access:

– Slotted access for M and C nodes (WBAN): it provides
a guaranteed access and a reduced delay for medical data.

– Contention access for (C, V ) and (V, S): this is appropri-
ate for mobility.

? Maintaining synchronization: during the data collection
phase, the network must operate under a regular schedule to
ensure the transit of the data between levels 1, 2, and 3 in
order to reach correctly the Sink. To this end, we propose that
Coordinator, Video and Sink nodes send periodically Beacon
messages. These messages have a crucial role because they
permit to resynchronize nodes (to prevent the clock drift
phenomenon) while keeping the data exchange hop by hop.

? Slots request by (M): the activity periods of (M ) nodes
may differ depending on the data size (temperature, fall
detection, ECG, etc.). Indeed, if a medical node wants to
send more than one packet in an activity period, we propose
that it sends a request to its associated Coordinator. In fact,
during initialization, (M ) nodes request a certain number of
slots (subsequently appointed GTS in Section 1) via ASC_RQ
message. Then the response will be indicated in C_Beacon
message (with the number of allocated slots), for use in the
collection phase. However, in Data collection phase, the re-
quest could be integrated in DATA message, and the response
will be in the C_Beacon message (in the next cycle). This
mechanism responds to the dynamic behavior of network.

? Reliability: to reduce collisions / transmission errors that
could occur during the two phases, it is necessary to retransmit
all messages (the number of retransmissions is parametrized)
including Beacon messages (except acknowledgments). This
leads to increase the reliability of the data exchange.

? Traffic model: we assume that the traffic model made in
the Data collection phase is periodic with the same period
throughout the network. Each node (M ) is the origin of one
or more data packets in each period (one data flow). (M )
nodes can also aggregate all medical data in one packet (the
maximum size of PPDU in IEEE 802.15.4 is 127 bytes). To
meet the energy needs of the sensors, the activity period should
be optimized and reduced as much as possible.

C. Complementary Mechanisms for Topology Maintenance

We have improved the topology maintenance with new mech-
anism. Sending Beacon messages periodically offers other ad-
vantages that meet the application requirements. Particularly,
they can be used for mobility management, re-allocation of
new slots for WBANs, and topology re-configuration: addition
of new sensor, and removal of a sensor (depleted battery,
sensor breakdown, etc.). Actually, each level has a manager
node that takes decisions while an event occurs: (C) node for
tier 1, (V ) node for tier 2 and (S) node for tier 3.
The mobility of a person has an impact on communications
of tier 1 and tier 2: (i) In tier 1, when 2 WBANs are situated
in the same range, to reallocate new slots, the (C) node sends
C_Beacon message containing the new allocated slots. (ii)
In tier 2, the link between (C) and (V ) could be interrupted:
node (C) should re-associate with a new (V ) node (we can use
the initialization mechanism via the exchange of B_Beacon,
ASC_RQ and ASC_ACK messages). Then the new (V ) node
relays the received data to the Sink (via DATA and ACK
messages).

IV. DIMENSIONING AND PERFORMANCE EVALUATION

A. Analytical Model

The delay and energy consumption are the most important
performance criteria for the application. Below we evaluate the
performance of the protocol in the two phases: initialization
and data collection. We used three important parameters:
network size, transmission interval and data size.

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? Initialization phase analysis: The first association phase
between all medical nodes and the Coordinator is represented
by the duration D :

D = TC_Beacon +
?nM

i=1 DASC (i) (1)

Where DASC (i) is the association duration of one node i and
nM the number of medical nodes. Then, let DASC (i) is the
mean association time of node i with the (C) of its WBAN:

DASC (i) = Tcs + TASC_RQ + TASC_ACK (2)

Tcs is a random duration before each node i sends its
?ASC_RQ?. To reduce collisions, each node initially senses the
channel during a random duration Tcs uniformly distributed in
the interval [0, Tf ], where Tf is the maximum of the duration.
For the sake of simplicity, we consider in a similar manner to
[10] the mean value of Tcs: Tcs =

Tf
2

(3)

? When the other medical nodes hear the first ?ASC_RQ?
they must wait for a time equal to (TASC_RQ +
TASC_ACK ) before starting to draw again a random
duration Tcs.

? The number of reserved GTS (reserved by (M )) depends
on the kind and the length of data.

The association duration of the other nodes can be written as
follows:

DASC (i)i?=1 = DASC (i – 1) + Tfi+3
+TASC_RQ + TASC_ACK

(4)

Energy consumption: To calculate the energy consumption
of the first node we can reuse the formula (2) by adding
consumption corresponding to each mode (reception or trans-
mission), then we obtain:

EASC (i)i=1 = erx ? (Tcs + TASC_ACK )
+etx ? (TASC_RQ) (5)

To calculate the total energy consumed we add the amount
(erx?TC_Beacon) that corresponds to the receiving of the Coor-
dinator Beacon (?C_Beacon?) and erx, etx are respectively the
energy consumed when receiving and transmitting data. The
energy consumption of the other nodes during the association
phase can be written as follows:

EASC (i)i?=1 = erx ? [DASC (i – 1) + Tfi+3
+TASC_ACK ] + etx ? (TASC_RQ)

(6)

As shown in Figure 3, in the reporting period, (C) sends
the collected data to (V ) to which it is associated. During this
period, medical nodes may turn off their radios (sleep mode)
to save energy.
? Data collection phase analysis: It corresponds to the data
sending and differs from the association, because during this
time, medical nodes don?t have to compete for the medium
access, however they have to send ?DATA? messages larger
than ?ASC_RQ?.

DDC = TC_Beacon + TDAT A + TACK (7)

DT otal = Tslots.
?nM

i=1 N (i) (8)

Where Tslots is the slot duration and N (i) is the total number
of slots allocated to medical node (i). To calculate the energy
consumption in data collection we reuse the formula (7):

EDC = erx ? (TC_Beacon + TACK ) + etx ? (TDAT A) (9)
? Other Superframes analysis: In the same way, we can
evaluate the upper tiers (C, V ) and (V, S). The principle
parameter that changes is the number of nodes per level
(nC ,nV ). However, in data collection analysis, the Tcs duration
must be added because (C) and (V ) nodes compete for the
medium access.

B. Hardware Implementation

? Platforms used: we have implemented T-TMAC in Imote2
hardware platform. The Imote2 transceiver operates at ISM 2.4
GHz frequency, 17.4 mA with (0 dBm) power output and it
allows data rates of up to 250 Kbps. The micro-controller runs
at 13-416MHz. This device requires a supply voltage between
3.2-4.5 Volts, and is powered by three 1.5V (AAA) batteries
in series. The sensing unit includes: temperature, acceleration
and humidity measurements. Two kinds of cards [14] may be
embedded on Imote2 radio card: Sensing card and Video card.
? Protocol implementation: Figure 4 shows the implemented
sensor network and Table 1 shows the measured real parameter
values of the Imote2. Four important tasks are realized to build
the network architecture and to test the network operations:
power tuning, frames setting (S_Beacons, DATA, ACK, etc.),
WBAN implementation (aggregation functions for (C), slots
management) and Data forwarding.

PARAMETER VALUE UNIT

S_Beacon, B_Beacon 11, 7 ms

CBeacon 12, 8 ms

TASC _RQ 12, 2 (M), 11, 7 (C, V ) ms

TASC _ACK 11, 9 (M), 11, 7 (C, V ) ms

TDAT A(M), TDAT A(C), TData(V ) 13, 7 (M), 14, 9 (C, V ) ms

TACK 11, 9 (M), 11, 7 (C, V ) ms

ST 1083 (M1), 450 (M 2) ms

etx 74, 2 (92 bytes) mA

erx 97, 2 (92 bytes) mA

el 56, 4 (listening) mA

epx 37 mA

epx(sleep) 500 ?A

esgx 6, 4 (procOn : 43, 4) mA

LED 2 (procOn : 39) mA

N umber of retransmissions 3 / O

T x power (M1, M2, C1, V1, S) -25, -25, -10, -10, -10 dBm

Table I
MEASURED PARAMETER VALUES

V. RESULTS AND DISCUSSION

Figure 5 shows the prototyping results for initialization
and data collection phases. The graph on the left side shows
the current consumption during initialization of each node
(M 1), (M 2), (C), (V ) and (S). We see that it increases de-
pending on the nodes position in the architecture. (M ) and (C)

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nodes are the larger consumers of energy. This is due to the
waiting time that these nodes spent to receive their appropriate
Beacon message (B_Beacon for (C) and C_Beacon for (M 1)
and (M 2) (as shown in Figure 3). The graph on right side
shows the current consumption of each node during data
collection phase, during 1 hour of operation, with Deep Sleep
period of 20 seconds. The results show clearly the advantage
of the Deep sleep mode implemented on Imote2 platforms, to
save the energy of all nodes.

Exchange of messages
between neighbor nodes

Terminal Serial Dump

Sniffer PC Xsniffer

M1

C1

V1

M2

WBAN 1

0x01

0x05

0x07

0x09

0x02
1) “Radio” card
2) “Sensor” card

1) “Radio” card

1) “Radio” card
2) “Vid?o” card

1) “Radio”card

1) “Radio card”

V2

0x08

M3

C2

M4

WBAN 2

0x03

0x06

0x04

Sink

V2

0x08

M3

C2

M4

WBAN 2

0x03

0x06

0x04

Figure 4. Implementation of the sensor network

Type of node

Consumption of each node in
the network

C
ur

re
nt

c
on

su
m

pt
io

n
du

ri
ng

d
at

a
co

lle
ct

io
n

(m
A

)

Sleep mode
Deep Sleep mode

Type of node

C
ur

re
nt

c
on

su
m

pt
io

n
du

ri
ng

in

it
ia

liz
at

io
n

(m
A

)

Figure 5. Prototyping results: initialization and data collection phases

We estimated analytically the average energy consumption
(EASC ) in initialization and Data collection phases. Figure 6
shows the comparison between analytical and real prototyping
results, for one hour of operation of the network, with Deep
sleep of 20 seconds (180 cycles). We added in the analytical
calculation the values assigned for data sensing ((M 1): tem-
perature and (M 2): all Data). We show that analytical results
fit with the prototyping results.

VI. CONCLUSION

In this paper a new MAC protocol for healthcare moni-
toring is presented. Simple mechanisms based on sleep/active
schedule are proposed for energy efficiency. We showed the
advantages of data aggregation and allocation of slots in a
multi-tiers architecture. The performance evaluation has been
realized with an analytical model and with real prototyping on
Imote2 platforms. The results fit very well. From all results,
it seems that T-TMAC protocol provide a significant amount

of energy saving. Our on-going work is focused on detailed
modeling analysis and scenarii evaluation and on the compari-
son between T-TMAC and other MAC protocols such as IEEE
802.15.4. Other perspective of this work concerns extending
the protocol with scalable slot allocation mechanism. This
mechanism could be appropriate for large applications with
dense number of nodes such as in the case of hospitals.

C
ur

re
nt

c
on

su
m

pt
io

n
du

ri
ng

in

it
ia

liz
at

io
n

(m
A

)

Type of node Type of node

Reel prototyping
Analytical model

co
lle

ct
io

n
(m

A
)

C
ur

re
nt

c
on

su
m

pt
io

n
du

ri
ng

d
at

a

Reel prototyping
Analytical model

Figure 6. Comparison of results obtained by the two methods: current
consumption by each node during initialization and data collection phases

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