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An Energy Efficient and Delay Sensitive Centralized MAC Protocol for Wireless Sensor Networks
Celal CEKEN
Kocaeli University, Technical Education Faculty Electronics and Computer Education Department
41380 Kocaeli, TurkeyTelephone: +90 262 303 22 40 Fax: 0 262 3058010
cceken@kou.edu.tr
Abstract. Energy consumption is one of the most crucial design issues in wireless sen-
sor networks since prolonging the network lifetime depends on the efficient manage-
ment of sensing node energy resource. In this research study, a new TDMA based MAC
protocol, which is not only energy aware but also delay sensitive, is introduced for
wireless sensor networks. In the proposed MAC, to achieve energy conservation, sens-
ing nodes employing the proposed MAC sleeps periodically to reduce duty cycle and
minimize idle listening. In addition, to provide lower message delay, time critical sens-
ing nodes request extra time slots form the central node. Unlike common wireless sen-
sor network models with a multi-hop topology, the proposed WSN architecture has a
centralized structure especially for energy efficiency and fulfillment of the delay re-
quirement of time critical networking applications. The proposed MAC has been mod-
eled and simulated using OPNET Modeler Software for performance evaluation. Simu-
lation results of the WSN model employing the new MAC are also presented including
comparisons with those of a WSN counterpart employing conventional IEEE 802.11
DCF MAC protocol. By varying the interarrival time between 1 and 8 seconds for 100
wireless sensing nodes, in the best case, as a consequence of the new scheduling algo-
rithms developed 15000 times better end to end message delay result and 4.325 times
lower energy consumption ratio have been obtained for WSN employing the proposed
MAC when compared with the WSN model employing IEEE 802.11 DCF MAC.
Keywords: Wireless Sensor Network, Energy Efficiency, MAC, TDMA, Latency.
1. Introduction
Recent progresses in micro electronics and wireless communication technologies have
led to need for widespread use of small, mobile, low-power, low-cost, multifunctional
sensor nodes with sensing, local processing and wireless transmission capabilities. In a
traditional sensor network system, to carry out a specific task, sensing nodes transmit
the data obtained from the working environment to a central processing node through
wired medium. These systems have relatively less number of nodes and the sensors de-
ployed have no local processing power. However, the new tendency is moving towards
building distributed networks consisting of sensing nodes small in size as well as with
local processing and wireless transmission abilities, namely Wireless Sensor Networks
(WSNs).
Because of their ease of deployment, low cost, flexibility, and ability to self-organize,
WSNs can be deployed in almost any environment, especially those where conventional
wired sensor systems are impossible, unavailable or inaccessible. Their potential appli-
cations included environmental detection and monitoring, smart spaces, disaster preven-
tion and relief, medical systems, home automation, scientific exploration, interactive
surrounding, robotic exploration etc. [1, 2].
WSN applications have quite different characteristics and requirements from traditional
wireless applications. A Sensing Node (SN) in a WSN is expected to be battery
equipped, and to change or recharge the power supply is usually very difficult. There-
fore energy conservation, which is essential for prolonging the lifetime of the SN and
thus of the network, is a more crucial issue in WSNs than such other performance met-
rics utilized for traditional network systems as throughput and delay. Most of the ongo-
ing researches about WSNs aim at fulfilling the low energy consumption requirement.
Like in any other wireless systems, maximum energy is consumed by radio functions
such as sending, receiving, and idle listening periods in WSNs. To reduce the energy
consumption an efficient MAC (Medium Access Control) protocol that provides effec-
tive allocation of medium resources shared by many different SNs must be utilized.
The primary goal of this research study is to implement a new energy-aware TDMA
(Time Division Multiple Access) based MAC protocol for WSNs. With the scheduling
algorithms developed for the proposed MAC, it is intended to achieve relatively better
end to end message delay results for especially time critical application traffics as well
as to fulfill the lower energy consumption requirement. Computer modeling and simu-
lation of the new approach and its application for a WSN scenario are realized using
OPNET Modeler software. Simulation results are also presented together with compar-
isons those of a WSN counterpart employing classical IEEE 802.11 DCF (Distributed
Coordination Function) MAC protocol.
The remainder of the paper is organized as follows. In the next section, a brief
introduction on WSNs and their network component is given. Section 3
presents general information about the WSN MAC protocols with comparisons. It also
provides a detailed overview of contention based CSMA/CA MAC protocol that will be
used for performance comparisons. Overall properties and design stages of the proposed
MAC protocol together with related algorithms are described comprehensively in Sec-
tion 4. Section 5 includes an example WSN scenario, consisting of several SNs and a
central access point all incorporate with the proposed MAC, which has been modeled
and simulated under different networking conditions. The simulation results obtained
are compared with those of an other WSN scenario with nodes employing CSMA/CA
MAC protocol that are also obtained under the same networking conditions as former
network scenario, followed by performance evaluation of both networks. The last sec-
tion gives the summary about the proposed MAC protocol with final remarks.
2. Wireless Sensor Network Architecture
In Fig. 1, the general architecture of a wireless sensor node is presented. As seen from
the figure, commonly, a wireless sensor node is composed of four major components
which are namely, the sensing unit, the processing unit, the power unit and finally the
wireless transceiver unit [2].
Location Finding System Mobilizer
Sensor ADCProcessor
StorageTranceiver
Power Unit Power Generator
Sensing UnitProcessing Unit
Fig. 1. General architecture of a wireless sensing node.
The sensing unit converts such measured physical quantities as humidity, pressure, tem-
perature, fuel tank level, flow rate, position, velocity, acceleration, chemical concentra-
tion, etc. into a voltage signal and thereafter digitizes it to produce digital output for
processing. The processing unit with a microcontroller controls all of the functions of
the sensor node and manages the communication protocols to carry out specific tasks.
Communication between the SN and the network it is attached to is provided by the
transceiver unit. And finally the power unit, which is the most crucial component of a
sensor node, supplies mandatory power to all of these units.
In addition to these major components, a sensor node may also include application de-
pended components such as power generator, location finding system and mobilizer.
Power generators, like solar cells, may be utilized to support the power unit for pro-
longing the sensor node lifetime. The applications requiring the location information of
the sensed data must be equipped with a location finding unit. Some of the WSN sys-
tems with mobility supported SNs must be provided with a mobilizer system to tackle
mobile sensing processes.
The protocol stack of SNs and the center node, gathering sensed information from the
sensor nodes, consists of application, transport, network, data link and physical layers
together with power management, mobility management and task management planes
[2].
Since the WSN applications and their requirements vary significantly, the architecture
of the WSN and service requirements may also be different. While the bit error rate
(BER) is a vital service requirement for some applications entailing a powerful error
control technique, the others such as healthcare applications may need to ensure low
time delay for the packets transferred.
In this research study presented, a new energy aware MAC protocol which is employed
in data link control layer is proposed. The data link layer provides SNs with communi-
cation functions to share the wireless medium efficiently as well with essential error
control tasks. In the following sections, WSN MAC protocols and the proposed MAC
technique will be explained in detail.
3. WSN MAC Protocols
As mentioned before, one of the most crucial issues in WSN is energy efficiency and
many enduring researches about WSN subject are intended to fulfill this requirement.
The major energy consumers in WSNs are radio communication functions such as
transmitting, receiving and idle listening. To reduce energy consumption of a wireless
SN an effective MAC protocol, an algorithm that defines in which manner the wireless
medium will be shared by the nodes constructing the network, must be utilized.
Although the WSN concept is relatively new, there are several studies found about
WSN MAC protocols in literature. The MAC techniques proposed for WSNs can be di-
vided into two category namely contention-based and TDMA protocols [3, 4].
IEEE 802.11 DCF (Distributed Coordination Function) is a contention based MAC pro-
tocol that is mainly built on the MACAW [5] and widely employed in early WSN ap-
plications. The frame format and timing schema of an IEEE 802.11 DCF MAC is illus-
trated in Fig. 2.
In this technique based on CSMA/CA (Carrier Sense Multiple Access with Collision
Avoidance), before data transmission starts, the source node firstly listens the medium.
If the channel is sensed "idle" for D interval then it sends a short RTS (Request to Send)
packet to the destination node informing upcoming packet transmission. When the des-
tination node receives the RTS, if it is proper, after a SIFS (Short Inter Frame Space)
interval it sends a CTS (Clear to Send) reply packet allowing source node to begin
transmission. RTS and CTS packets employed in CSMA/CA are utilized to avoid hid-
den terminal problem. Consequently the possibility of packet collision can be reduced,
but can not be eliminated. In this paper, the new MAC protocol proposed will be com-
pared with IEEE 802.11 DCF [3,4].
Node 1
Node 2
Node 3
Node x : Wireless Terminals MPDU : MAC Protocol Data Unit
D : DCF Inter Frame Space (DIFS) A : Ack
S : Short Inter Frame Space (SIFS) CW : Contention Window
RTS
CTS
MPDD MPDDAS CW
Fig. 2. Frame structure and timing schema of the IEE 802.11 DCF MAC protocol.
A contention-based SMAC protocol is described in [3]. For this protocol that is based
on CSMA/CA, energy conservation and self-configuration are primary goals, while per-
node fairness and latency are less important. To provide energy conservation, the
SMAC protocol tries to reduce undesirable energy depletion due to collision, overhear-
ing, packet overhead and idle listening as well as it turns the radio on and off based on
the fixed duty cycles. The main drawback of SMAC is that the use of fixed duty cycles
can waste considerable amounts of energy since the communication subsystem is acti-
vated even though no communication will take place.
The TMAC [6], another contention based protocol, uses an adaptive duty cycle to ob-
tain higher energy efficiency when compared to the fixed duty cycle used in SMAC.
The DSMAC [7] adds dynamic duty cycle feature to SMAC to achieve better latency
for time sensitive applications. In DMAC [7] protocol, that can be considered as an im-
proved version of Slotted Aloha, the primary goal is not only the energy conservation
but also achieving lower latency. The WiseMAC [8] protocol which combines TDMA
and CSMA techniques determines the length of the preamble dynamically to reduce the
power consumption and thus it results better performance under especially variable traf-
fic conditions. The detailed information on WSN MAC protocols can be found in [4,9].
4. The Proposed MAC Protocol
The energy consumption of each node is dominated by the cost of communication,
rather than computation in WSN. The basic wireless communication operations are re-
ceive, idle and transmit processes. The energy consumption rate for the transmit mode
is calculated based on the distance of the neighbors, the transmission capacity, and the
size of the message to transmit. Measurements have shown that idle mode, on which the
SN only listens the medium, consumes 50-100% of the energy required for receiving.
In [10], the ratios of idle: receive: send are measured like 1:1.05:1.4.
Major energy wasting sources determined in a wireless transmission process are colli-
sion; when an SN receives more than one packet at the same time, this results in dis-
carding of the packets and therefore, retransmission of the packets is required which in-
creases the energy consumption, overhearing; means an SN receives packets destined to
other SNs, control packet overhead; number and size of control packets for control sig-
naling should be as minimum as possible, idle listening; listening of medium for possi-
ble traffic reception and finally overemitting; occurs although the receiving node is not
ready to accept, a message is sent to destination [9,3].
Usually, the traditional wireless network nodes are in idle mode for most of the time.
However, they must listen to the channel to receive possible traffic. Since the energy
consumption is crucial for WSNs and the idle mode consumes considerable amount of
energy, turning off the radio if no traffic exists is quite reasonable. In the proposed
MAC the non time critical SNs periodically sleep to reduce the energy consumption ra-
tio (Fig. 3).
Active Time
Sleep Time Time
Fig. 3. Duty cycle of the proposed MAC protocol.
A centralized TDMA based MAC protocol, which is also studied in this work, is a good
solution for most of these problems. This work introduces a demand assignment scheme
to realize the proposed WSN MAC protocol. As a property of TDMA multiplexing
technique, radio spectrum is divided into time slots which are assigned to different SNs
and an SN can send data sensed only in its own dedicated slot(s). Due to the FDD du-
plexing technique utilized in the proposed MAC protocol, two distinct carrier frequen-
cies are used for the uplink and downlink channels. The frame structure and timing
schema of the proposed MAC protocol is illustrated in Fig. 4.
When an SN has data to send, it initially asks for a transmission channel, i.e. time slot,
from the CN (Central Node) which coordinates the available bandwidth usage and col-
lects the data sensed by SNs in its coverage area. The CN then assigns a time slot for
this connection using a dynamic Scheduling Table (ST) that is controlled with an algo-
rithm explained in the following sub-sections.
Frequency
Central Node (CN)
Downlink CC D D D D D CC D D D D(ISM Band)
Uplink
DownlinkSensing Node (SN)
Uplink CT D D D D D D D D D(ISM Band) 1 2 3 4 5 N-1 N
CC: CN Control Slot D: Data SlotCS: SN Control Slot N: Number of Slot / Frame
Time
Fig. 4. Frame structure and timing schema of the proposed MAC protocol.
In the proposed model, it is considered that all the SNs except delay sensitive ones have
three operational modes; transmit, idle and sleep. Since the energy consumption ratio of
receive and idle modes are approximately the same, the receive mode is omitted and its
energy consumption ratio is added to that of idle mode. The energy consumed depends
on the operational modes the node is in. Sleep mode is utilized to accomplish less en-
ergy consumption and in this context, all the non time critical SNs sleep periodically.
Furthermore, when an SN needs more bandwidth, again it request for extra time slot
from the CN. Then, CN assigns extra slot for this SN if there is available empty slot in
ST. Thus, relatively better delay results can be supported for especially delay sensitive
data traffics.
The properties of the proposed MAC can be summarized as follows:
Due to the centralized structure and TDMA scheduling technique utilized, all
the energy west sources mentioned before such as collision, overhearing, control
packet overhead and overemitting will be discarded.
Non time critical SNs sleep periodically to reduce the energy consumption,
which prolongs the lifetime of the network.
In a centralized structure, the SNs are directly connected to the CN; therefore, it
is not necessary to execute a routing algorithm, which means less energy con-
sumption end less message delay.
Time synchronization process is relatively simpler.
Self-configuration can also be achieved easily by the control packets namely
connection request and extra slot request.
Finally, with the scheduling algorithm employed in the CN, effective utilization
of resources such as bandwidth and energy can be satisfied. Especially, the extra
time slots dedicated for delay sensitive traffics results relatively better latency
performance.
The MAC protocol proposed in this research study is divided into two complementary
parts operating at the SN and CN. In the following sub-sections, these parts and their
simulation models realized using OPNET Modeler software are explained with all func-
tions.
4.1 Wireless Sensor Node MAC Model
The SN wireless functions of the proposed MAC protocol include four main processes.
These are; requesting a connection establishment from the CN, demanding extra time
slot(s) for delay sensitive traffics from the CN, getting its own time slot(s) from the CN
and finally sending data in its own time slot(s). Besides, for non time critical SNs there
is an extra function namely sleep mode which is crucial for energy conservation. The
SNs sleeps periodically to reduce energy consumption. In the WSN scenario studied,
any new added SN, to inform CN about its bandwidth requirement, creates a control
packet called cc_WSN_conreq_pk (Fig. 5a) and sends it in the first available empty
slot. Slot number 0, namely control slot, in the ST is reserved for control packets such
as connection establishment and extra time slot request. When an SN wants to send a
control packet, it uses the first empty data or control slot.
SourceID CRC DestID DataSlot CRC(1 byte) (2 byte) (1 byte) (1 byte) (2 byte)
a) b)
SourceID CRC(1 byte) (2 byte)
c)
SourceID CRC DestID ExtraSlot CRC(1 byte) (2 byte) (1 byte) (1 byte) (2 byte)
d) e)
Information(47 byte)
Fig. 5. (a) Connection request packet, (b) Connection replay packet, (c) Data packet, (d) Extra slot request packet, (e) Extra slot replay packet.
When the CN gets the connection request packet, if the resources are sufficient, it allo-
cates a time slot for the request and sends the slot number to the related SN using the
connection replay packet (Fig. 5b). After an SN gets its time slot(s),which means con-
nection has been established, the data sensed is conveyed with the data packet illus-
trated in Fig. 5c in its own time slot(s). A data packet comprises 48 bytes, consisting of
a 1–byte header (SourceID), and a 47–byte information field for sensed data. If an SN
needs more bandwidth for delay sensitive traffics it requests extra time slot again from
the CN using extra slot request packet (Fig. 5d). If there are adequate number of empty
slots, CN allocates one more time slot and sends the slot number to the related SN using
the extra slot replay packet (Fig. 5e). A 2-byte error correction field (CRC) which is
used for detection and correction of the possible packet transmission errors is also
added to all data packets. The process model of the proposed WSN MAC module em-
ployed in SN is illustrated in Fig. 6.
Fig. 6. The SN MAC layer process model.
The process starts with the big arrow, pointing the init state. This state performs a delay
until the other processes in the simulation are initialized and loads the control variables.
Then the process enters the idle state and waits here until a specific interrupt arrives.
The conReq state machine creates connection request packet informing connection es-
tablishment and sends it to the CN. The reqResp state machine obtains the number of
time slot assigned by the BS. The fromSrc state machine gets the data sensed from the
upper layer, segments it to the data packets and inserts them into the queue. The data
packets received from the upper layer are sent to destination in the time slot(s) dedi-
cated to the SN in toTX state machine. The sleep state machine turns off the radio
functions for a specific time interval to conserve energy. The extSlotReq state machine
creates extra slot request packet to inform extra bandwidth requirement for delay sensi-
tive traffics. The fromRx state machine delivers any arrived packets destined to the SN
to MAC layer. All SN MAC layer process model functions are outlined in Fig. 7.
State Machines
init
idle
conReq
fromSrc
reqRep
fromRx
toTx
Initialize
Wait for an interrupt.
Connection request
Sensed dataarrival
Control packet from CN
Slot && DataENQ
Create connection request packet and send it to the CN in f irst empty slot.
If the connection has been established, then put the data sensed to the packet.
SNs slot time
Send the packet.
Set up an interrupt for the SN next slot time.
Destroy received packet.
Packet for this SN
Get the SNs slot from the packet and destroy
extraSlotReqExtra slot
request
Create extra slot request packet and send it to the CN in f irst empty slot.
Y
N
Y
Y Y
Y
Y
Y
N
N
N
N
N
N
Functions
sleepSleep mode
Turn off the radio for 50 sec.
Y
NSleep mode
off
If the connection has been established, then put the data sensed into the buffer.
YN
Sensed dataarrival
Wait for an interrupt.
Y
N
Fig. 7. The SN MAC layer process model algorithm.
4.2 Central Node MAC Model
The CN gathers all the data sensed from the environment by the SNs in the cluster and
coordinates how the SNs will access the wireless medium fairly. The CN functions of
the proposed MAC protocol include three main processes. These are namely, assigning
time slot for any SN, forwarding any arrived data packets to upper layer and allocating
extra time slots for delay sensitive data traffics using the ST scheduling algorithm. Fig.
8 shows the proposed CN MAC model realized using OPNET Modeler.
Fig. 8. The CN MAC layer process model.
Like in the former process model, this process also starts with the init state, then enters
the idle state and waits here until a specific interrupt arrives. The fromRx state machine
delivers arriving packets to the next state machine according to the packet formats. The
bwReq state machine handles connection and extra time slot requests and also executes
a fair scheduling algorithm that manages the ST which stores the SNs slot usage infor-
mation. The data state machine delivers the sensed information to the upper layers to
execute a specific task. The CN MAC layer process model algorithm is outlined in Fig.
9.
State Machine
init
idle
bwRequest
fromRx
data
Initialize
Wait for interrupt
Packet from SNs
Destroy received packet.
N
N
Sensed data packet
Get the packet and deliver it to upper layer.
Connectionrequest
Extra slot request
Allocate a slot for the related SN. Create a connection response packet and send it to the SN.
ES
N
ES :Is there any empty slot (i.e. in ST dedicated=0 )LPS :Is there any low priority slot (i.e. in ST priority=0 )
Y
Allocate a slot for the related SN. Create a connection response packet and send it to the SN.
LPS
N
Y
ES
N
Y
Allocate a slot for the related SN. Create a extra slot response packet and send it to the SN.
Y
Functions
Y
Y
Y
N
N
Fig. 9. The CN MAC layer process model algorithm.
5. Computer Simulation of WSN
In the example scenario shown in Fig. 10, to generate sensed data traffics there are sev-
eral SNs which are implemented using OPNET Modeler and employing the proposed
MAC protocol explained in the previous section. The sensed data traffic introduced to
the network by any SN is destined to the CN for executing a specific task. Some of
these nodes considered as generating delay sensitive application traffics while the others
generating non time critical data traffics. Diameter of the cluster which constructs the
network topology is chosen 100 meters.
Fig. 10. Example WATM scenario.
Another WSN model analogous to the one above except that IEEE 802.11 DCF MAC
protocol is utilized instead of the proposed MAC is also simulated using OPNET Mod-
eler. Working conditions of both network models are chosen to be same for consistent
performance comparisons.
5.1 Simulation Results and Discussion
Simulation results of the both WSN models described above are presented under vary-
ing network load conditions followed by performance comparisons and analysis. In the
simulation environment a free space channel propagation model that supports to predict
received signal strength when the transmitter and receiver have a clear, unobstructed
line-of-sight path between them is utilized.
In the proposed MAC, an uplink frame consists of 125 time slots each has 1 ms length
and contains 2 data packets. The simulation parameters used are given in Table 1. The
simulation was run for 3600 second.
Table 1: Simulation parameters
Parameter Value
Message Size 20 packets x 50* Bytes
Interarrival Time 1*-10* sec
Data Rate 1 Mb/s
Frequency Band Uplink=3 GHz and Downlink=4 GHz
Transmitter Power CS= 10 mW and SNs=10 mW
Modulation Schema BPSK
Number of SNs 100
Area size 100 m x 100 m
Channel Model Free Space Propagation Model (LoS)
*Generated using Exponential Distribution Function Exp(Mean).
In most of the previous research related to WSNs, the major goal is to minimize the
power consumption of SNs. However, the focus of this work is not only improving the
power conservation performance but also providing a better average packet transfer de-
lay for especially time critical application traffics. The packet loss ratio metric is not
considered here since the buffers are assumed to have enough capacity so that no data
packet is lost due to buffer overflow. Moreover, it is also assumed that the CRC bits
added to the packets avoids the possible bit errors.
In the example scenario, while most of the SNs are deployed to generate non time criti-
cal sensed data, the SN1 is deployed to produce delay sensitive application traffic. All
non time critical SNs put themselves into sleep mode after 50 seconds of being idle and
stay this mode for next 50 seconds and this process repeats during the simulation run
time. Varying the message size of all SNs application traffics, power consumption and
average EED (end-to-end delay) results of the delay sensitive traffic transfer between
SN1 and CN, of non time critical traffic transfer between SN2 and CN have been col-
lected during the simulation run time for both WSN models.
In the proposed MAC, there are two parameters that effect the power consumption and
latency performance of the SNs. The first is the sleep mode, for non time critical SNs,
on which the power consumption ratio is considerably reduced while it results in in-
creasing end to end message delay. The second is the extra slot usage for delay sensitive
SNs, which provides lower latency performance but conversely results in higher power
consumption ratio due to the increasing channel utilization.
In Fig. 11, average EED results of the WSN models are presented as a function of the
interarrival time. To compare the results easily, Fig. 12 also shows the average EED re-
sults for the proposed MAC based WSN model, which are normalized with those of the
IEEE 802.11 DCF MAC based WSN counterparts. For heavy traffics (i.e. interarrival
time is up to 3 sec), in the best case, the delay sensitive application traffic (i.e. between
SN1 and CN) experiences approximately 15000 times lower (due to the burst slots em-
ployed in the proposed MAC), the non time critic application traffic (i.e. between SN2
and CN) experiences approximately 299 times lower average message delays in the pro-
posed MAC based WSN model compared to the same traffic carried with the IEEE
802.11 DCF MAC based WSN model. However, for the light traffics (i.e. interarrival
time is between 3 sec and 8 sec) the EED results of the IEEE 802.11 DCF MAC are
generally better than those of the both proposed MAC models. Moreover, it can be ob-
served from the figure that, for the proposed MAC, the longer duty cycle results in an
increase in message delay as expected.
0.01
0.1
1
10
100
1000
10000
1 2 3 4 5 6 7 8Interarrival Time (s)
Ave
rag
e E
nd
-to
-En
d D
elay
(s)
IEEE 802.11 DCF MAC Proposed MAC SN1-CN (delay sensitive) Proposed MAC SN2-CN (w ith sleep mode)
Fig. 11. Average EED results of the MAC protocols.
0.00001
0.0001
0.001
0.01
0.1
1
10
100
1000
1 2 3 4 5 6 7 8Interarrival Time (s)
Ave
rag
e E
nd
-to
-En
d D
elay
(s)
IEEE 802.11 DCF MAC Proposed MAC SN1-CN (delay sensitive) Proposed MAC SN2-CN (w ith sleep mode)
Fig. 12. Normalized average EED results of the MAC protocols.
In Fig. 13, measured average power consumption results of the WSN models are pre-
sented as a function of the interarrival time. Fig. 14 also shows the average power con-
sumption results for the proposed MAC based WSN model, which are normalized with
those of the IEEE 802.11 DCF MAC based WSN counterparts. As it can be seen from
the figure, power consumption results of the proposed MAC are better than those of the
IEEE 802.11 DCF MAC for all traffic conditions. In the best case, non time critical
SN2 employing the proposed MAC consumes 1.8 times lower energy than the one em-
ploying the IEEE 802.11 DCF MAC. For the proposed MAC model, non time critical
SN2 provides 1.1 - 1.7 times lower power consumption than SN1. This is not a surpris-
ing outcome since SN1 uses extra slot(s) to accomplish better latency performance and
this consequently results in increasing channel utilization, meaning additional power
consumption. Besides, SN2 puts itself into the sleep mode periodically and this pro-
vides a significant amount of reduction in power consumption ratio because the idle and
transmit modes consume rates are higher than the sleep mode consume rate.
4
5
6
7
8
9
10
11
1 2 3 4 5 6 7 8Interarrival Time (ms)
Ave
rag
e P
ow
er C
on
sup
tio
n (
mW
)
IEEE 802.11 DCF MAC Proposed MAC SN1-CN (delay sensitive) Proposed MAC SN2-CN (w ith sleep mode)
Fig. 13. Average power consumption results of the MAC protocols.
0.5
0.6
0.7
0.8
0.9
1
1.1
1.2
1 2 3 4 5 6 7 8Interarrival Time (ms)
Ave
rag
e P
ow
er C
on
sup
tio
n (
mW
)
IEEE 802.11 DCF MAC Proposed MAC SN1-CN (delay sensitive) Proposed MAC SN2-CN (w ith sleep mode)
Fig. 14. Normalized average power consumption results of the MAC protocols.
For the network model employing the proposed MAC, when an SN enters a sleep
mode, its transmission, receiving and idle operations are halted. Thus, the sensed data is
accumulated in the buffer. In Fig. 15, queuing statuses of SN1 and SN2 are shown. As
it can be seen, size of the data in the SN2 queue is more than that of SN1queue during
the simulation run time as a consequence of the sleep mode operation and this result in
increasing message transfer delay.
100
1000
10000
100000
0 10 20 30 40 50 60
Simulatin Time (minutes)
Qu
eue
Siz
e (b
ytes
)
Proposed MAC SN1 (delay sensitive) Proposed MAC SN2 (w ith sleep mode)
Fig. 15. Queuing statuses of SN1 and SN2 with the proposed MAC.
5. Conclusions
Many ongoing researches on WSN subject focus only on the energy efficiency. In this
study a new energy aware and delay sensitive MAC protocol for WSNs has been pro-
posed and simulated using OPNET Modeler software. The simulation results have also
been compared with those of the IEEE 802.11 DCF MAC protocol. According to the
performance results obtained, with the scheduling algorithms developed for the pro-
posed MAC protocol, not only have lower energy consumption ratios been fulfilled but
also lower end to end message delay results have been achieved for especially delay
sensitive data traffics. For the proposed MAC, in the best case, 1.8 times lower energy
consumption results and 15000 times lower latency performance have been obtained
when compared with those of IEEE 802.11 DCF MAC protocol.
Acknowledgement
The author would like to thank Assoc.Prof.Dr. Ismail Erturk for his invaluable contri-
butions to this study.
References
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Celal CEKEN received the M.Sc. and Ph.D. degrees from Kocaeli Univer-sity, Turkey in 2001 and 2004, respectively. His active research interests include wireless communications, broadband networks, ATM networks, high speed communication protocols, and Wireless Sensor Networks.
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