Anenergy Efficient and Delay Sensitive Centralized

8/6/2019 Anenergy Efficient and Delay Sensitive Centralized

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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, Turkey

Received 13 February 2007; accepted 11 June 2007

Available online 30 June 2007

Abstract

Energy consumption is one of the most crucial design issues in wireless sensor networks since prolonging the network lifetime depends on the

efficient management 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, sensing nodes

employing the proposed MAC sleeps periodically to reduce duty cycle and minimize idle listening. In addition, to provide lower message delay,

any time critical sensing node requests extra time slots form the central node when its queue size exceeds the upper threshold value. Unlike

common wireless sensor network models with a multi-hop topology, the proposed WSN architecture has a centralized structure especially for

energy efficiency and fulfillment of the delay requirement of time critical networking applications. The proposed MAC has been modeled and

simulated using OPNET Modeler Software for performance evaluation. Simulation 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 s for 100 wireless sensing nodes, in the best case, as a consequence of the new scheduling algorithms developed

9448 times better end to end message delay result and 1.9 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.

2007 Elsevier B.V. All rights reserved.

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 networksystem, 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 deployed 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 applications included environmental detectionand monitoring, smart spaces, disaster prevention and relief,

medical systems, home automation, scientific exploration,

interactive surrounding, robotic exploration, etc. [1,2].

WSN applications have noticeably different characteristics

and requirements from traditional wireless applications. An SN

(Sensing Node) in a WSN is expected to be battery equipped,

and to change or recharge the power supply is usually very

difficult. Therefore energy conservation, which is essential for

prolonging the lifetime of the SN and correspondingly of the

network, is a more crucial issue in WSNs than such other

performance metrics utilized for traditional network systems as

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throughput and latency. Accordingly, most of the ongoing

researches about WSNs aim at providing lower energy con-

sumption ratio. Like in any other wireless systems, maximum

energy is consumed by radio functions such as sending, re-

ceiving, and idle listening periods in WSNs. In order to reduce

the energy consumption ratio, an efficient MAC (Medium

Access Control) protocol that provides effective allocation ofmedium 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.

In the proposed MAC, in order to reduce latency of any delay

sensitive application, an extra slot is assigned to the relevant

SN. Extra slot request takes place when any time critical SNqueue size exceeds the upper threshold value. The scheduling

algorithms developed to perform these functions are the major

contribution of this study. In addition, for energy efficiency, the

non-time critical SNs put themselves into sleep mode

periodically to reduce the duration of idle listening which is

the major energy consumer. And this operation is the other

contribution of the paper.

Computer modeling and simulation of the new approach and

its application for a WSN scenario are realized using OPNET

Modeler software. Simulation results are also presented

including comparisons with those of a WSN counterpart

employing classical IEEE 802.11 DCF (Distributed Coordina-

tion Function) MAC protocol.The remainder of the paper is organized as follows. In the

next section, a brief introduction on WSNs and their network

components 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 Section 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 networkingconditions as former network scenario, followed by perfor-

mance evaluation of both networks. The last section 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].

The sensing unit converts such measured physical quantitiesas humidity, pressure, temperature, fuel tank level, flow rate,

position, velocity, acceleration, chemical concentration, etc.

into a voltage signal and thereafter digitizes it to produce digital

output for processing. The processing unit with a microcon-

troller 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 depended components such as power

generator, location finding system and mobilizer. Powergenerators, like solar cells, may be utilized to support the

power unit for prolonging 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 systems 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

Fig. 1. General architecture of a wireless sensing node.

21C. Ceken / Computer Standards & Interfaces 30 (2008) 2031


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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 require-

ments may also be different. While the bit error rate (BER) is a

vital service requirement for some applications entailing apowerful 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 communica-

tion 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 challenging problems

in WSN design is energy efficiency and almost all of the

enduring researches about WSN subject consider this require-

ment. 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.

There are several studies found about WSN MAC protocols

in literature. The MAC techniques proposed for WSNs can be

divided into two categories, namely contention based andTDMA based protocols [3,4].

IEEE 802.11 DCF (Distributed Coordination Function) is a

contention based MAC protocol that is mainly built on the

MACAW [5], and widely employed in early WSN applications.

In this study, the performance results of the new MAC protocol

proposed will be compared with those of IEEE 802.11 DCF

[3,4]. The frame format and timing schema of an IEEE 802.11

DCF MAC is illustrated 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 destination 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. After that, the

packet can be delivered to destination node. This process isrepeated for all new packet transmission requests. RTS and CTS

packets are utilized to avoid hidden terminal problem that result

in collisions. Accordingly, the possibility of packet collision can

be reduced, but can not be eliminated entirely. The performance

results of the IEEE 802.11 DCF MAC are given in Section 5.2

including comparisons with those of the proposed MAC.

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, overhearing, packet overheadand 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 sub-system is activated even

though no communication will take place.

The TMAC [6], another contention based protocol, uses an

adaptive duty cycle to obtain 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 delay sensitive applications. In the DMAC [7]

protocol, that can be considered as an improved 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 traffic conditions. Comprehensive informa-

tion on WSN MAC protocols will not be given here due to

space limitation, however, it can be found in [4,9].

4. The proposed MAC protocol

In most of the previous researches related to WSNs, the major

goal is to minimize the energy consumption of SNs. However, the

Fig. 2. Frame structure and timing schema of the IEEE 802.11 DCF MAC protocol.

22 C. Ceken / Computer Standards & Interfaces 30 (2008) 2031


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focus of this work is not only improving the energy conservation

performance but also providing a better average packet transfer

delay for especially time critical application traffics.The energy consumption of each node in a WSN is

dominated by the cost of communication, rather than compu-

tation. The basic wireless functions for an SN are; receive, idle,

and transmit processes. The energy consumption 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 show that idle mode, in

which the SN only listens the medium for possible traffic

reception, consumes 50100% of the energy required for

receiving. In [10], the ratios of idle, receive, and send processes

are measured like 1, 1.05, and 1.4, respectively. Major energy

wasting sources determined for wireless functions of an SN are

[9,3]:

Idle listening; means listening of medium for possible data

flow. Energy consumed in idle listening dominates all other

costs.

Collision; takes place when an SN receives more than one

packet at the same time. Collision results in discarding of the

packets and entails retransmission which boosts the energy

consumption.

Overhearing; means an SN receives packets destined to

other SNs.

Control packet overhead; size of the control packets for

control signaling should be as small as possible. Overemitting; takes place even though the receiving node is

not ready to accept, a message is sent to destination.

A centralized TDMA based MAC protocol, which has also

been studied in this work, is a good solution for most of these

problems. This work introduces a demand assignment sched-

uling scheme to be utilized in the proposed WSN MAC

protocol. As a property of TDMA multiplexing technique, radiospectrum 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 duplexing technique utilized,

an SN with the proposed MAC has two distinct carrier

frequencies for uplink and downlink channels. The frame

structure and timing schema of the proposed MAC protocol is

shown in Fig. 3.

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 collects

the data sensed by SNs in its coverage area. The CN then

assigns a time slot for this connection request using a dynamic

ST (Scheduling Table) that is controlled with an algorithmexplained in the following sub-sections.

Furthermore, when a time critical SN needs more band-

width that means the queue size exceeds the upper threshold

value, it asks again 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 end to end delay results can be

provided for delay sensitive data traffics. This scheduling

schema utilized in the proposed MAC is the major contribution

of the study. Especially in the light traffic conditions,

traditional wireless network nodes are in idle mode for most

of the time. However, they must listen to the channel to receive

possible data traffics. Since the energy consumption is crucialfor WSNs and the idle mode consumes considerable amount

of energy, turning off the radio, if no traffic exists, is quite

reasonable.

In the proposed model, it is assumed that all the SNs, except

delay sensitive ones, have three operational modes; transmit,

Fig. 4. Duty cycle of the non-time critical SNs.

Fig. 3. Frame structure and timing schema of the proposed MAC protocol.



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idle, and sleep. Since the energy consumption ratios of receive

and idle mode operations are approximately the sameaccording to the results measured in Ref. [10], the receiving

function has been omitted and its energy consumption ratio has

been added to that of idle mode operation. The amount of

energy consumed depends upon the operational modes the SN

is in. Sleep mode operation is utilized to accomplish less

energy consumption and in this context, all the non-time

critical SNs sleep periodically (Fig. 4).Besides, in the proposed MAC, in order to reduce latency,

time critical SNs are allowed to utilize the time slots of other

SNs when they are in sleep mode. To achieve this function, the

duty cycle of non-time critical SNs are chosen periodic (i.e. not

time variant).

Fig. 6. The SN MAC layer process model.

Fig. 5. (a) Connection request packet, (b) Connection reply packet, (c) Data packet, (d) Extra slot request packet, (e) Extra slot reply packet, (f) Release slot packet.



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The overall properties of the proposed MAC can be sum-

marized as follows:

Due to the centralized network topology and TDMA

scheduling technique utilized, all the aforementioned energy

west sources such as collision, overhearing, control packet

overhead, and overemitting can be decreased.

Non-time critical SNs put themselves into sleep mode

periodically to reduce the energy consumption, which

prolongs the lifetime of the network. Besides, delay

sensitive SNs are allowed to utilize the time slots of any

SN that is in sleep mode, which results is lower end to end

message delay.

In a centralized structure, the SNs are directly connected to

the CN. Therefore, it is not necessary to execute a routing

algorithm, which results in less energy consumption and

provides lower end to end message delay.

Time synchronization process is relatively simpler.

Self-configuration can also be achieved easily by the

control packets namely connection request, extra slot

request, and release slot request.

Finally, with the scheduling algorithm employed in the

proposed MAC, effective utilization of resources such as

bandwidth and energy can be satisfied. The extra time slots

dedicated for delay sensitive traffic results in relatively better

latency performance.

Fig. 7. The SN MAC layer process model algorithm.



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On the other hand, scalability is the major drawback of he

proposed model with centralized structure when compared with

the model with multi-hop topology.

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 explainedin detail.

4.1. Wireless sensor node MAC model

The SN wireless functions of the proposed MAC protocol

include; requesting a connection establishment, asking for extra

time slot(s) for delay sensitive traffics, getting its dedicated time

slot(s), informing deallocation of extra time slot(s), and sending

data in its own time slot(s). Besides, for non-time critical SNs

there is an extra function, namely sleep mode process in which

SNs defer their wireless operations to reduce energy consump-

tion. In the WSN scenario studied, any new added SN creates acontrol packet called cc_WSN_conreq_pk (Fig. 5a) in order to

inform the CN about its bandwidth requirement and transmits it

in the first available empty slot. Slot number 1 in the ST, namely

control slot, is reserved for such control packets as connection

establishment, extra time slot request and release slot request.

When an SN requires sending a control packet, it uses the first

empty data or control slot.

When the CN gets the connection request packet it allocates

a time slot, if the resources are sufficient, for the request and

sends the slot number to the related SN using the connection

reply packet (Fig. 5b). After an SN gets its time slot(s), which

means the connection has been established, the information

sensed is transferred by the data packet illustrated 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. When 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 usingthe extra slot reply packet (Fig. 5e). Finally, the CN is informed

to release extra slots allocated to time critical SNs, using release

slot packet (Fig. 5f) when the queue size is less than the lower

threshold value. A 2-byte error correction field (CRC) which is

used for detection and correction of the possible bit errors is also

added to all packets traveling over the network. The process

model of the proposed WSN MAC employed in SN and all its

functions are illustrated in Figs. 6 and 7, respectively.

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 specificinterrupt arrives. The conReq state machine creates connection

request packet, informing connection establishment, and sends

it to the CN. The reqResp state machine obtains the number of

time slot assigned by the CN. The fromSrc state machine gets

the data sensed from the upper layer, segments it into the

packets and inserts them into the queue. The data packets

received from the upper layer are sent to destination in the time

slot(s) dedicated to the SN in toTX state machine. The sleep

state machine, for non-time critical traffics, 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 sensitive traffics.

Extra slot release packet is created and sent to the CN in

Fig. 8. The CN MAC layer process model.



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releaseSlot state machine. The fromRx state machine handles

any arrived packets destined to the SN.

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 accessthe wireless medium fairly. The CN functions of the proposed

MAC protocol include three main processes. These are namely;

assigning time slot for any SN, delivering any arrived data

packets to upper layer and allocating/releasing 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.

The scheduling algorithm operates in the CN allocates

available bandwidth, i.e. time slots, for the requesting SNs. The

information about which slots will be used by SNs is hold in a

table called ST (Scheduling Table). There are three fields for

each slot in ST, which are Terminal Number, Dedicated, andPriority. The Priority field can get two values; 1 for high

priority, and 0 for low priority, and is used especially to

handle extra slot requests. When any SN asks for an extra slot

from the CN, the scheduling algorithm assigns an empty slot for

it and set the Priority field to 0. The slot whose Priority field is

Fig. 9. The CN MAC layer process model algorithm.



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0 may be reassigned for a new connection request, in case

empty slot does not exist.

The process starts with the init state, then enters the idle

state and waits here until a specific interrupt arrives. The

fromRx state machine delivers any arriving packet to the next

state machine considering its format. The bwRequest state

machine handles connection requests and allocation/deal-location extra time slot requests, and also executes a fair

scheduling algorithm that manages the ST. The data state

machine delivers the sensed information to upper layer to

execute the specific task. The CN MAC layer process model

algorithm is outlined in Fig. 9.

5. Computer simulation of WSN

5.1. Assumptions

In the example scenario, shown in Fig. 10, in order to

generate sensed data traffics there are numerous SNs which are

deployed randomly and equipped with 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, which is the sink node where the results of sensor

measurements are collected, for executing a specific task. It is

assumed that some of these nodes are generating delay sensitive

application traffics while the others are generating non-timecritical data traffics. Diameter of the cluster which constructs the

network topology has been chosen 100 m.

In the simulation environment a free space channel propaga-

tion 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. 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.

Another WSN model analogous to the one above except that

IEEE 802.11 DCF MAC protocol is utilized instead of the

Fig. 10. Example WATM scenario.



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proposed MAC has also been simulated using OPNET Modeler.

Working conditions of both network models have been chosen

similar for consistent performance comparisons.

5.2. Simulation results and discussion

In the proposed MAC, an uplink frame consists of 220 time

slots each has 1 ms length and contains 2 data packets. The

simulation parameters are given in Table 1.

Simulation results of the both WSN models described above

are presented under varying network load conditions followed

by performance analysis and comparisons. The simulation was

run for 3600 s.

In the example scenario, all non-time critical SNs put

themselves into sleep mode after 50 s of being idle and stay this

mode for next 50 s, and this process repeats throughout 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 collected during the simulation

run time for both WSN models.

In the proposed MAC, there are two factors that impact the

power consumption and latency performance of the SNs. The

first is the sleep mode operation, for non-time critical SNs, in

which the power consumption ratio is considerably reduced

while it results in increasing 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. For heavy

traffics (i.e. interarrival time is up to 3 s), in the best case, the

delay sensitive application traffic (i.e. between SN1 and CN)

experiences approximately 9448 times lower (by virtue of extra

slot utilization and demand assignment scheduling algorithm),

and the non-time critic application traffic (i.e. between SN2 and

CN) experiences approximately 271 times lower average

message delays in the proposed MAC based WSN model

when compared with those of the IEEE 802.11 DCF MAC

based WSN model.

However, for the light traffics (i.e. interarrival time isbetween 3 s and 8 s) EED results of IEEE 802.11 DCF MAC are

generally better than those of the both proposed MAC models.

Moreover, it can also be observed from the figure that, for the

proposed MAC, the longer duty cycle (in the scenario, SN1 has

a longer duty cycle than SN2 has, as a consequence of sleep

mode operation), results in a decrease in message delay as

expected.

In Fig. 12, measured average power consumption results of

the WSN models are presented as a function of the interarrival

time. As 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 equipped with the proposed MAC consumes 1.8times lower energy than the one employing the IEEE 802.11

DCF MAC.

For the proposed MAC model, non-time critical SN2

provides 1.11.8 times lower power consumption than SN1

does. This is not a surprising outcome since SN1 uses extra

slot(s) to accomplish better latency performance. Accordingly,

Fig. 11. Average EED results of the MAC protocols.

Table 1

Simulation parameters

Parameters Value

Message size 20 packets 50 a Bytes

Interarrival time 1 a10 a s

Data rate 1 Mb/s

Frequency band Uplink = 3 GHz and Downlink = 4 GHzTransmitter power CS = 10 mW and SNs = 10 mW

Modulation schema BPSK

Number of SNs 100

Queue threshold values 12,0009000 bits

Area size 100 m 100 m

Channel model Free space propagation model (LoS)

a Generated using exponential distribution function exp (mean).



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it results in increasing channel utilization that boosts energy

dissipation. Besides, SN2 puts itself into the sleep mode

periodically and this provides aforementioned significant

amount of reduction in power consumption. IEEE DCF

MAC based SNs consume more energy than SNs employing

the proposed MAC for all load conditions as can be seen from

the figure.

For the network model employing the proposed MAC, when

an SN enters in sleep mode to save energy, its wireless functions

such as transmit, receive, and idle are halted. During this period,

all the data sensed are stored in the buffer. In Fig. 13, queuing

statuses of SN1 and SN2 are shown. As can be seen from the

figure, size of the data in the SN2 queue is more than that of

SN1 queue for the duration of the simulation run time as a

consequence of sleep mode operation. The SN2 turns off radio

functions periodically, provides lower energy dissipation, and

conversely results in increasing message transfer delay as

explained before.

In Fig. 14 that stands to reveal the effect of extra slot usage,

queuing statuses of SN1 both with extra slot and without extra

slot are shown. Any time critical SN asks for extra slot from the

CN when its queue size exceeds the upper threshold value. After

a new time slot assigned for the SN, accordingly, its queue

size decreases below to the upper threshold value until the

Fig. 12. Average power consumption results of the MAC protocols.

Fig. 13. Queuing statuses of SN1 and SN2 with the proposed MAC.



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simulation end as can be seen from the figure. It is obvious that

the queue status of SNs impacts the end to end message delay,

namely the lower queue size result in the lower end to end

message delay as can be seen in Fig. 11.

6. 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 proposed andsimulated using OPNET Modeler software. In the proposed

MAC, in order to reduce latency of any delay sensitive appli-

cation, an extra slot is assigned to the relevant SN when its queue

size exceeds the upper threshold value. The scheduling

algorithms developed to perform these functions are the major

contribution of this study. In addition, for energy efficiency, the

non-time critical SNs put themselves intosleepmode periodically

to reduce the duration of idle listening which is the major energy

consumer. This operation is the other contribution of the paper.

The simulation results have been compared with those of

the IEEE 802.11 DCF MAC protocol. According to the

performance results obtained, with the scheduling algorithmsdeveloped for the proposed 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, 1.9 times lower energy consumption results

and 9448 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 contributions to this study.

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Celal Ceken received the M.Sc. and PhD degrees

from Kocaeli University, Turkey in 2001 and 2004,

respectively. His active research interests include

wireless communications, broadband networks,

WATM, QoS, high-speed communication protocols,

and wireless sensor networks.

Fig. 14. Queuing statuses of SN1 and SN2 with the proposed MAC.


Anenergy Efficient and Delay Sensitive Centralized

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