Research Article Energy-Efficient Sleep/Wake Scheduling for Acoustic Localization …downloads.hindawi.com/journals/ijdsn/2014/970524.pdf · 2015. 11. 23. · Research Article Energy-Efficient

Research ArticleEnergy-Efficient Sleep/Wake Scheduling for AcousticLocalization Wireless Sensor Network Node

ChengFang Zhen,1 Wenyi Liu,2 Yongrui Liu,1 and Anbin Yan1

1 Key Laboratory of Instrumentation Science & Dynamic Measurement, North University of China, Ministry of Education,TaiYuan 030051, China

2National Key Laboratory for Electronic Measurement Technology, TaiYuan, Shanxi 030051, China

Correspondence should be addressed to Wenyi Liu; [email protected]

Received 18 July 2013; Revised 18 December 2013; Accepted 23 December 2013; Published 25 February 2014

Academic Editor: Frank Ehlers

Copyright © 2014 ChengFang Zhen et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.

Both energy-saving and synchronization issues are the paramount concern in wireless sensor networks (WSNs). In this paper wepropose a simple and efficient WSN node design based on acoustic positioning applications and present an on-demand sleep/wakescheduling synchronization protocol.Three aspects are already considered in the design: (a) power controllable; (b) energy efficient;(c) high synchronization accuracy. Our primary goal is to maximize energy saving and to control power supplying according toenvironments and demands. We establish a model of energy consumption and improve it by the ways of power control and on-demand synchronization. The on-demand synchronization protocols are implemented in sensor nodes and evaluated in a testbed.Analysis and simulation were performed that the proposed protocol has significantly reduced the energy consumption. It is alsodemonstrated by experiments that the platform is accurate and effective.

1. Introduction

The latest developments in distributed computing andmicro-electromechanical systems have enabled in the past years theemergence of variouswireless sensor networks (WSNs) appli-cations comprising military [1], home automation [2], smartbuilding [3], healthy and medical application [4], vehicle andtarget tracking [5], and industry domains [6, 7].TheWSNs fordetection, localization, and tracking of the acoustic sourcesare widely applied in many industries including defense,robotics, and security sectors. The advantage of objects’localization by their sound radiation is that it is, in essence, apassive method which needs no collaboration with the objectin the localization process. Moreover, the localization objectis not aware that it is under observation. This is important indefense and object protection applications ofWSNs. Anothermotivation to use localization by sound is that it can be asupplement to other methods of environmental surveillancewhen visibility is not good enough or when an object is notoptically visible [8]. In this paper, we propose a design and

implementation of a wireless sensor network. Our designmainly focuses on energy saving and clock synchronizationof the acoustic localization node.

In general, a WSN consists of a large number of low costand densely deployed battery-powered sensor nodes withwireless communication, sensing, processing, and storagecapabilities [6]. The sensor nodes are equipped with sensing,computing, power, and communication modules to moni-tor a certain phenomenon such as environmental data orobject tracking [8]. An important characteristic of sensordevices is that their battery capacity is very small, muchsmaller than conventional wireless devices like laptops andeven PDAs, thereby making energy conservation one of themost important issues in sensor networks. As the sensornodes are powered by batteries, it is difficult to replace orrecharge because of cost (e.g., cost of battery and labor) orgeographic (e.g., difficult or unfriendly terrain) reasons andthus the nodes in WSNs are characterized by limited power,processing, and memory resources, making energy saving aparamount concern in WSNs.

Hindawi Publishing CorporationInternational Journal of Distributed Sensor NetworksVolume 2014, Article ID 970524, 14 pageshttp://dx.doi.org/10.1155/2014/970524

2 International Journal of Distributed Sensor Networks

Another great challenge in the design of theWSN node isto find suitable mechanisms for clock synchronization [9] inthe application of localization. In wireless sensor networks,the basic operation is data fusion, whereby data from eachsensor is agglomerated to get a single meaningful conclusion.Sensor readings and timestamps are passed along so thatfusion of such information fromvarious sensorswill be addedup to a global result. In this case, the energy and space mightbe waste when the object motion was first spotted to itsdirection.The fusion of individual sensor readings is possibleonly by exchanging messages that are timestamped by eachsensor’s local clock. This mandates the need for a commonnotion of time among the sensors. Protocols that providesuch a common notion of time are clock synchronizationprotocols. Many clock synchronization protocols have beenproposed for WSNs [9–11].

Even though many energy-saving sleeping mechanismshave been proposed by researchers [12–16], they are unsat-isfactory for every application. Some methods are too com-plicated with many assumptions on application scenarios,and it is difficult to implement them in real sensor nodesgiven the constrained resources. Othermethods are proposedfor general sensor networks, and it is in fact unnecessaryto incorporate all of the functions in several situations. Inparticular, many WSNs are deployed on a small scale inhome automation, intelligent buildings, and patient moni-toring. They only need a feasible and easily implementedsleep scheduling mechanism. Additionally, the problem ofsynchronization accuracy and energy consummation alwaysexists.

In this paper, we propose an energy-efficient, simple, andfeasible synchronous node sleep/wake mechanism for smallscale wireless sensor networks. The node itself can realizepower control to sleep or wake according to the demandof the acoustic signal laicization. Sensor nodes are dividedinto sink nodes and listening nodes. Beacon frame containingsleep command from the sink can be forwarded to sink nodesvia forwarding nodes. All the nodes in the network can entersleep mode about the same time. Through such networksynchronization mechanisms, we can realize synchronoussleeping and waking of the entire network. Furthermore, anew power control scheme based on synchronization in themedium access control (MAC) layer is proposed. We call itOSWSP (on-demand sleep/wake synchronization protocol).It operates with the help of synchronization protocol andcalculates optimal transmission power according to the signaltracking demand. The synchronization protocol includes awake-up command that begins to work only if the signal hasbeen detected. This approach can greatly reduce the use ofenergy and cost of wireless sensor network nodes, extendingits life period. The proposed mechanisms are implementedin sensor nodes and are evaluated in a test-bed. The analysisand evaluation based on the experimental results confirmthat the proposed energy-savingmechanisms are feasible andefficient.

This paper is organized as follows.In Section 2 previous related works on various energy-

saving mechanisms and synchronization protocol based on

existing sensor nodes are summarized. Section 3 introducesthe design and implementation of the sensor nodes weproposed. Section 4 presents the synchronous sleep andwakeschemes forWSNs and describes the operation of each sensornode. Section 5 describes power control scheme and energyefficiency forWSNs. Section 6 shows the experimental resultsand analysis. Finally, Section 7 concludes the paper.

2. Related Work

The sensor nodes are the basic elements of WSNs, which areresponsible for collecting information, fusion processing, anddata transmission. Some WSNs were developed for generalapplications in decades as follows.

At Berkeley, the Smart Dust project [17] aims at devel-oping sensor nodes of micrometric size. They focus onminiaturization of sensor nodes so that it has the size of a dustparticle. Since this is a long-time project, the first step was thedevelopment of Mote’s family. The WeC Mote was one of thefirst types of sensor nodes developed in this project. Then,they upgraded to Mica Mote and finally to Mica2 Mote. Thedesigner claims that theadvantage of this last mote is its radio,which is more robust comparing to TR1000.

The Pico Radio project [18] at BerkeleyWireless ResearchCenter is another project at Berkeley. The objective is todevelop a low-cost and low-power sensor node. Its focus isat the radio hardware, link, and network layer stack. MedusaMk-2 [19] and iBadge [20] are sensor nodes from UCLA.These sensor nodes use more than one processor and iBagdealso includes a bluetooth chip. These devices provide a goodsolution for gateway.

Pushpin [16] is a sensor node, that is, part of a MITproject. Although the main objective is to develop the sensornode for a portable computer, Pushpin’s requirements alsomeet the wireless sensor network needs. It uses a differentapproach for communication: infrared. Its operational sys-tem, Bertha, is for distributed system.

Presently, a few theoretical wireless sensor network nodemodels for monitoring the environment and locating minershave been put forward, but little attention has been given tothe synchronization of sensor nodes and energy saving.

The existing literature identifies the idle state of thepowered radio of the sensor node to be a major source ofpower depletion in WSNs [14]. In some applications thereare instances in which the traffic load is very light mostof the time. It is therefore desirable to turn off the radiowhen a node is not actively delivering data. There are manyapproaches to achieving it, such as scheduling the nodes’sleep pattern [12, 13] and imposing control on the radiofrequency (RF) radio [15]. Furthermore, Subramanian andFekri, in their study, try to find the bounds on the lifetimeand the sleeping probability of nodes independently, whichare valid both for event occurrence detection and continuousmonitoring and sensing of an environment [16]. In [21],Anycast packet-forwarding scheme is proposed, where eachnode has multiple next-hop relaying nodes in a candidate setreferred to as forwarding set. Thus, when a node has data to

International Journal of Distributed Sensor Networks 3

Data collection module

Signal conditioning

circuit

Processor module

GPS FIFO Expansion port

SDRAM Flash USBFlashWireless transceivers

9XTEND

Acoustic sensor

1–6

A/DTransform

FPGAXC3S1400AN

DSPTMS320C6747

PC interfaceUSB (CY7C68013)

Energy supply module(including voltage converter, the constant current source circuit)

(ADS8365)

Figure 1: The architecture of a sensor node.

send, it has to wait for one nearest specified sink node to wakeit up, and then it forwards the packet to the first node thatwakes up in the forwarding set. It reduces the expected one-hop delay. In this paper, we compare the proposed protocolwith the energy-saving mechanism in [13, 21].

Over the last decade, researchers have developed variousclock synchronization protocols for wireless sensor networkswhich can be classified into two categories: continuoussynchronization [10] and on-demand synchronization [11]. Incontinuous synchronization, time synchronization protocolkeeps the clock synchronized at all times so that it can beconsulted whenever an event occurs. Among other problems,this strategy wastes energy: if events occur infrequently, theresources that are used to maintain synchronization duringidle periods are wasted. In acoustic application, the idletime is longer than the object running time in most cases,so the on-demand synchronization protocols are suitable.Throughnetwork synchronizationmechanism,we can realizesynchronous sleep and wake throughout the entire network.

Having studied previous work on node design, energy-saving sleep, and synchronization algorithm, our work isbased on the starting point of these three integrated solu-tions. The implementation of dormancy mechanisms andsynchronization stamp collection are taken into accountfor the node design, and efforts were made to exploremethods for node energy consumption and the accuracy ofsynchronization. In particular, we have implemented all ofthe functions described in this paper in real sensor nodesand set up a test-bed to evaluate the proposed mechanisms.Through the analysis of experimental data, it is confirmedthat the proposed energy-savingmechanisms are feasible andeffective.They can significantly extend the lifetime of networkand improve overall network performance.

3. Implementation of WSN AcousticLocalization Node (Rewhitened)

3.1. System Architecture. WSN nodes are responsible forinformation collection, calculation and judgment, data pro-cessing, and data exchange between neighboring nodes. Thetypical requirements for WSNs are as follows [1, 8]: reliabil-ity, low-power consumption, real-time processing, mobility,accuracy, time synchronization, small size, and low cost. Ournode is designed according to these guidelines.

This paper designed aWSNnode focusing on the acousticlocalization system which can be used for signals detection.Thus, the abnormal status and target movement can besensed. The node is designed in modular mode. A sensornode is made up of four basic components as shown inFigure 1: a sensing unit, a processing unit, a communicationunit, and a power unit. Commensurating with the scalabilityand flexibility, we deployed some function facilities on thenode such as FLASH and FIFO (first in first out) fordata storage, USB (universal serial bus) for interface, andredundancy expansion port for expansion.

3.2. Processing Module. Proper processor is critical in thedesign. Most of the typical sensor data processing modulesare using a single chip orARM(advanced reduced instructionset computing machines) chip as a data processor such asAVR microcontrollers of the ATMEL company, ultralowpower MSP430 series processors of 𝑇

1, and ARM processors.

Though these processors have excellent processing ability,they are not suitable for the application characteristics ofacoustic positioning and synchronization data processingneeds; its digital processing speed cannot transcend specificDSP (digital signal processor). So we use DSP as data


Controlsignal

Radiosignal

Datasignal

SPI

A/D transform

GPS

SDRAM

FIFO

9XTEND

SPI

Serialinterface

SDRAM

USBCY7C68013

XC3S1400ANFPGA

TMS320C6747DSP

Figure 2: The structure of the data processing module.

processing module microprocessors to process the positiondata and run synchronization algorithm. The FPGA (fieldprogrammable gate array) is especially used to collect thetimestamp and send the clock data for DSP.This combinationmakes the sensor more efficient, as shown in Figure 2.

3.3. Power Supply Control Module. Power supply moduleis the cornerstone of the entire node acquisition system,which provides energy for all components. In this design,we specifically designed a voltage conversion circuit and aconstant current source circuit to meet different referencevoltage needs of the rest of the modules that will use differenttypes of chips ensuring that each chip works in the bestpossible conditions. In addition, the adoption of the pluggedoff power chip enabled us to control its power in eachmoduleaccording to the energy-saving requirements.

The power requirements of the sensor nodes are differentaccording to different chips as shown in Table 1.

We use 24V voltage source series of two 12V mobilepower as the power supply device of the system. The LT1084voltage converter switches 24V into 5V and via the voltageswitcher supplies it to other circuits except the sensor, whichneeded 24V constant voltage source direct supply.

Specific power supply module structure design schemat-ics are shown in Figure 3.

We ensure that each module can be individually con-trolled by the power switch in the circuit implementationprocess, which makes it easy to maximize energy savings.Specific design schematics are shown in Figure 4.

3.4. Wireless Communication Module. We use The 9XTendOEM RF wireless chip from DIGI Company for its reliability,high data throughput, long distance ability, and especiallyfor its various switching status shown in Figure 5. 9XTendwireless module is supporting 2.8 V–5.5 V power supply,supporting software programming pin serial port and the

Table 1: Voltage levels type involved in system.

Modules Type of chip Power requirements

Datacollectionmodule

Sensor MPA416 Constant current source,2.5 V reference

ADS8365 Analog 5V, digital 3.3 V

Dataprocessingmodule

DSP, FPGA Digital 3.3 V, 1.2 VDSP USB spared Digital 1.8 VSDRAM, FLASH, GPS,USB68013, Digital 3.3 V

FIFO Analog 5VWirelessmodule 9XTEND Analog 5V

Others LED Analog 5V

cycle sleep mode, and supporting hardware sleep mode thatconsumes only 5mA.

Wirelessmodule supports both hardware off and softwareoff sleep mode, which can achieve low-power design. Whenthe SHDNpin of 9XTend is set low, the wireless module turnsinto the hardware shutdown mode. The VCC pin current isonly 5 uA in this mode. The wireless module will be resetwhen the SHDN pin is set high, and then after about 100msit enters idle mode state. 9XTend can freely be set to sleepmode, serial port sleep mode and cycling sleep mode byusing the SM (sleep mode) command. The consumptionsof these three modes are 147 uA, 10mA, and 1.6mA. Theconsumptions of the transmission and receiver modes aredetermined by the data scale and the network congestionstate. The consumptions in the different models are shown inTable 2.

3.5. Sensor Module. Based on the research background, ourtargeting object is located in audible voice by human ears.Theperception of soundbyhuman ears has a large dynamic range:


Power supply24V (seriesconnectionby two 12V

mobile power)

direct current

5V

ADS8365FIFO

9XTENDLED

DSPSDRAMGPS

ADS8365FPGAFLASHUSB68013

DSP USB spare

3.3V DC

1.8V DC

1.2V DC

2.5V voltagereference

DSP, FPGA

Figure 3: Power supplying schematics.

DGND

DGND

DGND

DGND

DGND

DGND

DGND

DGND

DGND

DGNDDGND

DGND

+C36

22uF

R117

D17 R59

U56

1

23

4

567

8

9

1011

1213

141516

17

1819

20

212223

24

TP1

R57200

TP5

D12

D13

C35

104

R53

R500

R40

TP2

U25

IRF7404

S11S22S33G4 D1 5D2 6D3 7D4 8

D14

R480

D15

TP4

C31

104

TP6

R55

C67106

D11

C33

106

R54

R52

C32

104

R38

C34

104

R11522

C29

104+C30

22uF

VCC5V DSPbrd 5V OUT

VCC5 V

0

0 9XTEND 5V

TP3 9XTEND 5V

OUTDSPbrd 5V

DVCC3 3V

9XTEND 5V

9XTEND 5V

DSPbrd 5V out

DVCC3 3V

1K 1K

1K

1K

DVCC1.2V FPGA V

DVCC3.3V FPGA

VCC5V

TPS70345

GND/HEATSINK4NC2

MR2#MR1#EN#

SEQGND/HEATSINK3GND/HEATSINK2

NC1

RESET#PG1

NC3

GND/HEATSINK1

GND

DVCC3.3V FPGA

1M

DVCC3 3V

1KIRF7404 F

DVCC1.2V FPGA V

DVCC1.2V FPGA V

DVCC3 3V

DSPbrd 5V OUT

1Vin22Vin2

1Vin12Vin1

1Vout12Vout1

1Vout22Vout2

Vsense2 /FB2Vsense1/FB1

Figure 4: Power control circuit principle.

the ratio of permanent hearing-impairing sound in short-time exposure to the silent audible sound is 1012. Such a largerange can be expressed in logarithm: the log of 1012 at 10 is 12,expressed as 120 db. Human hearing does not have the samesensitivity to all frequencies. The most sensible frequencyrange is 2–4 kHz. So a microphone of a frequency rangeof 20Hz∼20KHz is adopted in our design which carried aterminal modulating circuit.

In acoustics, sound intensity is defined as the power ofsound per unit area. In calculating the decibel value, 20 uPa

is the reference value, which is the lower limit threshold inperception of sound by humans. Sound pressure is a fieldquantity and therefore the decibel is determined by soundpressure. The output voltage of the microphone signal can becalculated by the following sound pressure level formula:

𝑌 = 20 log10

(𝑥 (Pa)

𝑃ref) dB, (1)


Transmit mode

Receivermode

Idlemode

Closemode

Sleepmode

Commandmode

Figure 5: The model state transition diagram of 9XTend.

Table 2: The consumption of 9XTend in the different modes.

Type of mode Power valueOff mode 5 uAIdle mode 147 uASerial port sleep mode 10mACycling sleep mode 1.6mATransmission mode Decided by data scaleReceiver mode Decided by data scale

in which 𝑃ref is the standard reference sound pressure,20mPa; we let 𝑌 be 127 dB for experiments command. Thenwe can get

𝑥 = 2 × 10𝑦/20−5

= 2 × 101.35

≈ 44.77 (Pa) . (2)

The peak voltage of microphone output can be calculatedwith the values of the sound pressure and the sensitivity ofthe microphone:

𝑈 = (𝜌 × 𝑥) = (50 × 44.77) ≈ 2.24 (V) . (3)

So the microphone output voltage range is

−2.24V ≤ 𝑈 ≤ +2.24V. (4)

Obviously, the energy consumption of the sensorobserved in the study meets the desired results of an energyefficient design.

4. Sleep/Wake Synchronization Mechanism

Generally, the energy conservation issue is dealt with in fivedifferent ways:

(1) efficient scheduling of sensor node’s states to alternatebetween sleep and active modes;

(2) efficient control of transmission power to ensure anoptimal tradeoff between energy consumption andconnectivity;

Server

SinkSensor node

Monitor area

SinkSensor node

Monitor area

Internet

Figure 6: System architecture of a WSN.

(3) energy-efficient routing, clustering, and data aggrega-tion;

(4) data compression (source coding) to reduce theamount of uselessly transmitted data;

(5) efficient channel access and packet retransmissionprotocols on the data link layer.

Here, we mainly focus on the mechanisms on the firstand second levels, that is, node sleep scheduling and powercontrol.Wename the synchronization protocol we propose asOSWSP (on-demand sleep/wake synchronization protocol).

4.1. The System Architecture of WSN. The energy controllingin OSSP is based on the following WSN topology shownin Figure 6. It consists of sensor nodes, a sink node (coor-dinator), and a server. The sensor node collects environ-mental information according to the type of sensor usedand sends the information to the sink node which may belocated multiple hops away. The sink node is also a gatewayforwarding data to the server via carrier networks. Duringforwarding, other intermediate sensor nodesmay process thedata. The sink node can be an enhanced sensor node or aspecial network gateway with no sensing capability. It is usedto connect a WSN to an exterior network to complete datadelivery between the two types of networks. It may be anethernet gateway if a wired network exists, or it may be awireless gateway connected to a public cellular network thatcan significantly extend the WSNs’ communication range.A server will receive data, and, in some situations, it willperform some computations and send commands back tosensor nodes via the sink node.

4.2. On-Demand Synchronous Sleep and Wake Schemes.Before the sleep and wake schemes are introduced, webriefly describe the beacon frame structure, used to sendsleep commands to the entire network. In the IEEE 802.15.4standard, four types of frames are defined. Data frame is usedfor the transfer of data. Acknowledgment (ACK) frame andMAC command frame are used for confirming successfulframe reception and handling all MAC peer entity controltransfers, respectively. Finally, beacon frame is used by thesink to transmit beacons. In our implementation, the beacon


Table 3: Beacon frame structure as defined by IEEE 802.15.4.

Octes: 2 1 4/10 2 Variable Variable Variable 2Framecontrol

Sequencenumber

Addressingfields

Super-framespecification GTS Pending

addressing fieldsBeaconpayload FCS

MGR MAC payload MFR

Sensor node

Sink

Sink

Sensor nodeSleep mode

Sleep mode

Idle mode

Sink

Receiver modeTransmit

mode Transmit modeWake + syn.

Receiver mode

ACK + syn.

Figure 7: WSN mode conversion.

frame is used to implement network synchronization and itsstructure is shown in Table 3.

In Table 3, MAC header (MHR), MAC payload, andMAC footer (MFR) together form the beacon frame. TheMAC payload contains three nonpayload fields (super framespecification, guaranteed time slots (GTS) for quality ofservice (QoS), and pending address list) followed by thebeacon payload field. The MAC payload is prefixed by MHRand appended withMFR.TheMHR contains theMAC framecontrol field, beacon sequence number (BSN), and addressinginformation fields. The MFR contains a 16-bit frame checksequence (FCS). In this paper, we set “beacon payload” to “01,”which represents sleep command and can be sent by the sinkto the entire network for synchronous sleep.

As depicted in Table 3, the sleep command is sent by thesink labeled as “coor” in the figure using the beacon frame.The cluster receives the sleep command from the sink whenthere is no suspicious target, but the sink is always in the idlemode to monitor the surrounding environment as a sentinel.The synchronization protocol and laicization algorithm doesnot consume the extra energy but becomes effective onlywhen an interested object event occurs. Once the wirelesstransceiver of the sink detects the object at the monitorrange, it will wake the data processing mode and send asynchronization frame with an awaking command to thenodes in this cluster. All the clusters are thereby turned to the

wake mode from sleep and also running the synchronizationprotocol to prepare the position of the object. The technicaldetail of the synchronization protocol is described in otherpapers by the author, and only the energy-efficiency and basicprinciples are shown here.

After the sink sends the beacon frame, it enters thereceiver mode immediately. In order to ensure that eachnode successfully receives the beacon frame, a node that hasreceived the beacon frame sends back an acknowledgementframe. Note that the entire network needs to guaranteeproper time synchronization when implementing the sleepmechanism. Otherwise, it will cause loss of synchronizationamong the nodes and will not complete the sleep procedurecorrectly. The processing of the mode conversion is shown inthe Figure 7.

The flowcharts of the sink and sensor are presented inFigures 8 and 9 for better understanding.

Two problems arise from this basic scheme. One problemis that one node may receive multiple sleep commandscontained in different beacon frames. The solution is to shutdown the receiving function of the wireless communicationmodule after a node has received a beacon frame.The secondproblem is that it may cause broadcast storm if we let eachnode rebroadcast the received beacon frame.This problem issolved by a more sophisticated scheme.


Start

Initialization

Wake mode

Idle mode

Object checking

Receiver mode

Synchronization protocol with

nodes

Data processing

Localization algorithm

End

Object checking

No

Yes

Yes

No

Sleep scheduling

phase

Synchronization phase

Localizationphase

Transmit mode (syn. + wake)

Figure 8: Flowchart of major phases and their interaction of thesink.

4.3. Enhanced Synchronous Sleep andWake Schemes. Consid-ering the problems with the basic sleep scheme, we improveit to optimize network performance by designing a layeredarchitecture of the sensor network. First, we classify thesensor nodes other than the sink into two types: forwardingnodes (FNs) and listening nodes (LNs). Forwarding nodeswill forward sleep commands from upstream nodes (thosecloser to the sink) and data from listening nodes; theywill not collect environmental information or generate data.Listening node will not forward sleep commands but willcollect environmental data and send them out while being

Start

Initialization

Wake mode

Sleep mode

Sink framechecking

Synchronization protocol with sink

Data collecting

Transmit sensor data

End

No

Yes

Sleep scheduling

phase

Synchronization phase

Localizationphase

Localization algorithm

Receiver mode

Transmit syn. + ACK

(syn. + wake)

Figure 9: Flowchart of major phases and their interaction of thesensor.

in wake mode. During node initialization, a sensor node isconfigured as FN or LN. Here, some cluster-based routingprotocols are used to select some cluster heads from thesensor nodes. These cluster heads will be chosen as FNs, andthe remaining nodes will be designated as LNs. By the way, aFN or LN can also be set manually according to the networktopology.

The sink sends out the beacon frame,which contains sleepcommand information (type = beacon, beacon payload =CMD SLEEP). A FN that receives the command will shutdown the receiving function of the communication module


Sensor node

Send out the sleep command

Receive the data

Sink

Enter sleep mode aer receiving the

sleep command

Send out the data

Enter sleep mode aer forwarding the sleep command

Forward the data

LN

FN

Ton

T

T1 T2

T1 T2

T1 T2

w1 w2 w3 w4

t

t

t

t

Figure 10: Node sleeping and waking scheduling.

and will broadcast the sleep command. It will then enter sleepmode immediately. A LN that receives the sleep commandalso enters sleep mode immediately. Even though FN andLN enter sleep mode at a slightly different time, the timedifference is generally negligible. All of the nodes in sleep willproperly set timer counter andwake at about the same time. Itis easy to see that the total number of broadcast beacon framesin the network is reduced because LDs will not rebroadcastthe received beacon frame.

After waking up, LN will wait for 𝑇1and send out data.

It will make sure that all of its surrounding nodes have beenwaken. After the interval 𝑇

1, the sink will wait for another

interval 𝑇2during which the next sleep command is sent out;

that is, the sink will wait for a total of 𝑇0

= 𝑇1

+ 𝑇2before

sending out a sleep command again. The selection of 𝑇1and

𝑇2is affected by the accuracy of the system clock and other

factors such as network size. In our sensor node, an externalcrystal oscillator of 8MHz is used as the system clock with anaccuracy of 100 ppm (10 − 4). If the sleep time is set to 900 s,the deviation is ±0.09 s and maximal deviation Δ𝑇 is 0.18 s.Thus, in order to stabilize the system, 𝑇

1should be much

larger than Δ𝑇. Here we choose 2 s as its value. ConsideringLN having enough time to send out data that can eventuallyarrive at the sink via multiple FNs, we set 𝑇

2to 5 s.

Figure 10 shows the timing of the enhanced schedulingscheme for the sleep and wake of sensor nodes. It is assumedthat the sensor nodes wake at 𝑤

1, 𝑤2, and so on to work for

Ton and then sleep for Toff in each cycle. The sink receivesthe data during 𝑇

2and sends out the sleep command at

the end of 𝑇2. Each LN sends out the data during 𝑇

2and

enters sleep mode after receiving the sleep command. EachFN is responsible for forwarding the data during 𝑇

2and

enters sleep mode after forwarding the sleep command. Notethat different sensor nodes including the sink, LN, and FNenter sleep mode at slightly different times depending onthe network size and the accuracy of clock synchronization.Similarly, they also wake at slightly different times. That iswhy we require that all of the sensor nodes start deliveringdata after 𝑇

1.

In general, the characteristics and advantages of theproposed synchronous sleep and wake schemes are thefollowing.

(1) When the sink sends out a sleep command, all of thesensor nodes in the network should be idle becausethe sink has waited for an extra interval 𝑇

2before

sending out the beacon frame. This avoids the loss


of beacon frame that contains the synchronous sleepcommand.

(2) The scheme uses beacon frame as carrier of the sleepcommand which can be processed in MAC layer.Thus, the processing time is short.

(3) Each node sleeps and wakes at different times. Thesensor nodes in the network will not enter sleepmodeat exactly the same time. Likewise, they will not wakeat the same time either. This can significantly reducecollisions when the sensor nodes have data to send.

(4) The scheme can decrease the number of beaconframes forwarded in the network and energy con-sumption.

(5) After a FN receives a sleep command, it will forwardit out and shut down its receiving function. Thus, itwill not receive and forward the same sleep commandrepeatedly. It can further decrease the number of bea-con frames forwarded in the network, avoid broadcaststorm, and reduce energy consumption.

5. Power Control and Energy Analysis

5.1. EnergyModel. Suppose that the source emits a zeromeanrandom signal 𝑥

𝑠(𝑡) during the time interval of length 𝑇. If

the sampling frequency is 𝑓𝑠, the signal will be represented

by 𝐾 = 𝑇𝑓𝑠samples. The measurements of 𝑥

𝑠(𝑡) correspond

to the reference distance of 1m from the source. Under theassumption that the noise is additive, the signal at the 𝑖thsensor node is

𝑥𝑖(𝑡) = 𝑥

𝑖(𝑡) + 𝑛

𝑖(𝑡) , 𝑥

𝑖(𝑡) =

𝑥𝑠(𝑡 − 𝜏𝑖)

𝑑𝑖

, (5)

where 𝑑𝑖is the distance between the source and the 𝑖th sensor

node, 𝑥𝑖(𝑡) is the delayed and attenuated signal at the 𝑖th

sensor node, 𝑛𝑖(𝑡) is white Gaussian noise 𝑁(0, 𝜕

2

𝑛), and 𝜏

𝑖,

𝜏𝑖= 𝑑𝑖/𝑐, is the time delay.The signal energy at the 𝑖th sensor

node is modeled by

𝐸𝑖(𝑡) =

𝐸𝑠(𝑡 − 𝜏𝑖)

𝑑2

𝑖

+ 𝜉𝐸𝑖

(𝑇) , (6)

where 𝐸𝑖(𝑡) is the 𝐾-samples based energy estimate defined

by

𝐸𝑖(𝑡) =

1

𝑘

𝑡=𝐾/2

∑

𝑙=𝑡−𝐾/2+1

𝑥2

𝑖(𝑙) − 𝜎

2

𝑛. (7)

And 𝐸𝑠(𝑡 − 𝜏𝑖) is the delayed signal energy:

𝐸𝑠(𝑡 − 𝜏𝑖) =

1

𝑘

𝑡−𝜏𝑖+𝐾/2

∑

𝑙=𝑡−𝜏𝑖−𝐾/2+1

𝑥2

𝑠(𝑙) . (8)

The estimation error 𝜉𝐸𝑖(𝑡) is

𝜉𝐸𝑖(𝑡) = 𝐸

𝑖(𝑡) −

𝐸𝑠(𝑡 − 𝜏𝑖)

𝑑2

𝑖

=1

𝑘

𝑡=𝐾/2

∑

𝑙=𝑡−𝐾/2+1

((𝑛2

(𝑙) − 𝜎2

𝑛) + 2𝑥

𝑖(𝑙) 𝑛 (𝑙)) .

(9)

Under the assumption that 𝑥𝑠(𝑡) and 𝑛

𝑖(𝑡) are uncorrelated,

the estimate 𝐸𝑖(𝑡) is unbiased as 𝐸(𝜉𝐸

𝑖(𝑡)) = 0. From (9), the

variance of 𝜉𝐸𝑖(𝑡) is

𝜕2

𝐸𝑖= 𝐸 (𝜉

2

𝐸𝑖(𝑡)) =

2𝜎4

𝑛

𝐾(1 +

2𝜎2

𝑠

𝑑2

𝑖𝜎2𝑛

) , (10)

where 𝜎2

𝑠, 𝜎2

𝑠= 𝐸(𝑥

2

𝑠(𝑡)), is the variance of the signal during

source activity.

5.2. The Influence of log(det(𝑅𝐸)) Term on Estimation of the

Acoustic Source Position by Signal Strength. The covariancematrix 𝑅

𝐸for the signal strength estimates based on 𝐾

samples is

𝑅𝐸

=1

𝐾𝑁𝑅𝐸1

, (11)

where 𝑅𝐸1

is the covariance matrix for the signal strengthestimated by single sample and 𝑁 is the order of the matrix𝑅𝐸1. Substituting (11) into (10), the log-likelihood function

becomes

𝐿𝐸

(𝑥) =1

2log (𝐾

𝑁) −

1

2log (det (𝑅

𝐸1)) −

1

2𝐾𝑁

𝜉𝑇

𝐸𝑅−1

𝐸1𝜉𝐸.

(12)

The first term of (12) is constant and does not influence theestimate of the source position. The second term does notdepend on 𝐾. The third term increases with 𝐾 accordingto the factor 𝐾

𝑁. Then, from (12), we can conclude that thesecond term becomes negligible compared to the third termand can be neglected for sufficiently large 𝐾.

5.3. The Influence of log(det(𝑅𝑇)) Term on Estimation of the

Acoustic Source Position by TOA. The covariance matrix 𝑅𝑇

is proportional to CRLB constant 𝐶𝜏

𝐶𝜏𝑅𝑇

= 𝐶𝑁

𝜏𝑅𝑇, (13)

where𝑅𝑇is a conditional covariancematrix for the unit value

of the CRLB and 𝑁 is the order of the matrix 𝑅𝑇. Taking into

account (13), the log-likelihood function is

𝐿𝑇

(𝑥) =1

2log (𝐶

𝑁

𝜏) −

1

2log (det (𝑅

𝑇)) −

1

2𝐶𝑁𝜏

𝜉𝑇

𝑇𝑅−1

𝑇𝜉𝑇.

(14)

The first term does not depend on the source positionand can be ignored. For high SNR, the noise variance 𝜎

2

𝑛is

small compared to the signal power, and CRLB factor 𝐶𝜏


reduces according to (8).The third termof (14) becomesmoresignificant than the second term, which can be neglected.Hence, the likelihood function can be approximated by thethird term:

𝐿𝑇

(𝑥) ≈ −1

2𝜉𝑇

𝑇𝑅−1

𝑇𝜉𝑇. (15)

5.4. Transmission Power Computation. It is assumed that thedistance between two nodes is 𝑑, the power received bythe receiving antenna is 𝑃

𝑟, and the output power of the

transmitting antenna is 𝑃𝑡. According to the Friis equation

we have

𝑃𝑟

=𝑃𝑡𝐺𝑡𝐺𝑟

𝐿(

𝜆

4𝜋𝑑)

𝑛

, (16)

where𝐺𝑡and𝐺

𝑟are the antenna gains of the transmitting and

receiving antennas, respectively, 𝜆 is the wavelength, and 𝐿 isa system loss factor not related to the propagation (𝐿 ≥ 1).

In the free space, 𝑛 can be set to 2. In urban situationswhere there are strong multipath fading effects and thereis frequently no clear line-of-sight, 𝑛 has to be determinedexperimentally and is typically in the range of 3 to 5.

We assume that 𝑃thr is the minimal power of receivedsignal that can be decoded correctly. It is easy to determinethe minimal transmission power 𝑃min of the sending node toguarantee that the signal can arrive at the receiving node andbe decoded correctly. 𝑃min can be computed by the followingequation:

𝑃min =𝐿𝑃𝑡

𝐺𝑡𝐺𝑟

(4𝜋𝑑

𝜆)

𝑛

. (17)

From (16) and (17), we get the following equation:

𝑃min =𝑃thr𝑃𝑡

𝑃𝑟

. (18)

If a receiving sensor node knows the transmission power𝑃𝑡of the sending node, the power threshold 𝑃thr, and the

received signal strength 𝑃𝑟, then it can figure out the minimal

power that the sending node should use to ensure that thesignal can be received correctly. In the following, we call thisminimal required power the “optimal power.”

6. Simulation and Experiments ResultsAnalysis of the Location Node System

The above described synchronization sleep/wake mechanismwas formulated in a large scale sensor network of acousticpositioning system which was tested by simulation usingOPNET tools. The energy efficiency of our nodes was testedat the National Key Laboratory for Electronic MeasurementTechnology. The results of formulation and experiments areexplained in detail in this section.

6.1. Simulation of the Synchronization Sleep/Wake Mecha-nism. Based on the developed system model, simulationsare carried out using OPNET to evaluate the performance

Table 4: Simulation parameters for sleep/wake mechanism.

Simulation parameter ValueSensing area 200 × 200m2

Bandwidth 38.4 kbpsTransmission range 50mReceiver mode power 30mWIdle mode power 30mWSleep mode power 0.003mwTransition time 2.45msPacket size 96 bytesTime slot size 42msSimulation time 300 s

of the proposed synchronization sleep/wake mechanism.Performance of proposed protocol was compared with thetwo contemporary protocols: TDSS (a target direction-basedsleep scheduling algorithm) [13] and Anycast protocol [16].The following are the details of the simulation setup anddiscussion of the results.

Simulations were conducted in the sensing area of 200 ×

200m2 and the number of sensor nodes varied from 20 to260 for different experiments. Sensor nodes were randomlydeployed and the random deployment was achieved bychoosing (𝑥, 𝑦) locations based on a uniform distribution.The sink node was fixed at the center of the network. Thesimulations were conducted with a communication rangedouble their sensing range. The simulation parameters areshown in Table 4.

The performance of OSWSP is compared with the TDSSand Anycast protocols.

Experimental parameters, such as average delay perpacket and energy per packet, were used to measure theperformance of protocol. The synchronization accuracy isconsidered and described in another paper by the authors[22].

6.1.1. Average Delay per Packet. Delay is referred to as thetime span between the packet sent from a sensor node andpacket received at the sink node. Delay values were measuredby changing the number of sensor nodes from 20 to 260.As shown in Figure 11, the average delay experienced by theproposed OSSP protocol was the least, while Anycast wasthe second and TDSS had the worst delay time. In OSSP,nodes were given different wake intervals according to theirtraffic requirement with respect to their position in network,their topological importance, and their proximity from theevent. The proposed protocol was able to minimize delayat each hop because nodes did not have to wait long forthe wakeup interval of the next hop. As a result, averagedelay per packet in OSSP was less than Anycast protocoland TDSS. In the Anycast protocol, though the node hasmultiple next-hop relaying nodes by virtue ofAnycast packet-forwarding scheme, which helps to find next hop neighborin a quick manner, it still does not consider the variedtraffic requirement of different nodes. Thus, node wait time


0.09

0.08

0.07

0.06

0.05

0.04

0.03

0.02

0.01

0

0 20 40 60 80 100 120 140 160 180 200 220 240

Number of nodes

Aver

age d

elay

per

pac

ket

OSWSPTDSSAnycast

Figure 11: Average delay per packet for different numbers of sensornodes.

increases as the packet approaches to the nodes near to thesink node.

Therefore, it has greater delay than the proposed protocol.In TDSS protocol, nodes have fixed wake interval for thewhole network irrespective of their traffic requirement; thus,each node has to wait for the wake interval of the next hop.However, as all nodes have to relay their data all the way tosink node using multihop communication, it involves manyrelay nodes to reach the sink node, which increases end-to-end delay. Considering the local traffic at each node, senseddata has to wait for some time at each node to get attended;thus delay becomes longer when the packet approaches thenodes near the sink.The problem gets worse when the packetapproaches the nodes near the sink node, where the packetsuffers maximum delay. It makes the Anycast protocol andTDSS prone to longer delays.

Furthermore, as the number of nodes increases, theOSWSP clearly outperforms the other two strategies. ForOSWSP, the performance remains the same for the increasednumber of nodes, since wake interval is adaptive to thetraffic load, whatever may be the size of the network. In thisway, increasing the node number has no effect on OSWSP.Therefore, it suggests that the proposed OSWSP protocol ismore scalable than TDSS and Anycast protocol.

6.1.2. Average Energy per Packet. Average energy per packet isa measure of energy spent for forwarding a packet to the sinknode. It is an indicator of the lifetime that can be achievedby the protocols. In Figure 12, average energy per packet isplotted on𝑦-axis, with varying number of sensor nodes (from20 to 260) on 𝑥-axis. It can be observed that the averageenergy consumption per packet for the proposed OSSPprotocol is less than Anycast protocol and TDSS, indicatingcomparatively extended network lifetime. The reason forincreased lifetime in OSWSP can be attributed to the fact thatit adjusts wake intervals based on traffic loads. By doing so,SMED avoids the case where the nodes remain awake andstay idle when no traffic is to be forwarded. Whereas, in theAnycast protocol, many nodes stay awake to provide alternate

0.045

0.04

0.035

0.03

0.025

0.02

0.015

0.01

0.005

00 20 40 60 80 100 120 140 160 180 200 220 240

Number of nodes

Aver

age e

nerg

y pe

r pac

ket (

J)

OSWSPTDSSAnycast

Figure 12: Average energy per packet for different numbers ofsensor nodes.

Figure 13: The implementation of the sensor node.

paths for routing and mostly they remain idle, as expected,traffic requirements of nodes are considered while setting upsleep/wake schedule. It results in increasing the wake nodestaying idle, which significantly limits the network lifetime.Similarly in OSWSP protocol random sleep/wake scheduleis defined for all the nodes which increases the number ofwake idle nodes especially as it moves away from the sinknode. Nodes away from the sink node have to do less relaying.Ultimately, it uses the energy of the nodes in idle listeningand the lifetime of the network is reduced. Hence proposedprotocol has less energy per packet for both Anycast andTDSS protocols.

6.2. Experiments Results with the Node Power Control. Theproposed power control schemes were implemented in thesensor nodes shown in Figure 13 which were developed atKey Laboratory of Instrumentation Science and DynamicMeasurements. We have set up a test-bed and experimentswith sensor nodes developed by the team. The results andanalysis are presented in the sequel. In the experiments,two batteries are used (the voltage of each battery is 12 V)in series to provide energy for each sensor node. If thevoltage falls below 2.2V, the sensor node will not workcorrectly. Thus, we compare the voltage variation in theexperiments. Figure 13 shows the variation of average voltagein the sensor nodes before and after the synchronous sleepscheme is used, respectively. Without the scheme, the sensornodes continuously sense and send information about the


3.2

3

2.8

2.6

2.4

2.2

20 2 4 6 8 10 12 14 16 18 20 22 24

Time (h)

Volta

ge (V

)

Voltage variation without sleep mechanismVoltage variation with sleep mechanism

Figure 14: Voltage variation analyses before and after sleep mecha-nism.

surroundings to the server. With the scheme, the node is setfreely from sleeping to waking according to the target action.

In our experiment, the sensor was supplied for constantcurrent source in 4mA, so the voltage variation which isshown in Figure 14 is used to analyze the sensor energyefficiency before and after sleep mechanism.

In Figure 14, the vertical axis represents the averagevoltage measured in the sensor node. The unit is “hours” andwe can see that, within about 22 hours, the average voltagewith sleep mechanism is always lower than without the sleepmechanism. The experimental results show that the sensornetwork will survive for one day depending on whether thesleep mechanism is implemented. It demonstrates that theproposed sleep and wake scheme is effective in saving energyand can significantly extend the lifetime of the network.

Our results show that up to 60% energy savings per bat-tery operated node while maintaining efficient data delivery.The scheduling algorithm allows the nodes to save energyby powering off the wireless communication device. We canuse any lightweight timer synchronization mechanism. Asdemonstrated in the experiments, limiting the number ofactive nodes in a wireless network not only saves power butalso reduces contention achieving higher aggregate through-put. The efficiency of this scheduling technique is provedby the measurements made on a test bed network. In short,the scheduling technique can improve throughput up to10.3%, with maximum power saving of 85.54%. In terms ofenergy consumption, a small number of nodes are used foroptimal consumption, ensuring that at any point in timethe majority of nodes are actually sleeping, resulting in highenergy savings (60%).

The above experiment illustrates the operation procedureof the proposed power control schemes implemented in oursensor network. In the following discussion, we compare thevoltage variation in the experiments. In Figure 15, it shows thevariation of average voltage in the sensor nodes before andafter the power control mechanism is used.

In the experiments, the sensor nodes continuously senseand send information about the surroundings such as tem-perature to the server. From the figure, we can see that, withthe proposed power control scheme, the lifetime of sensor

3.2

3

2.8

2.6

2.4

2.2

2

0 2 4 6 8 10 12 14 16 18 20 22 24

Time (h)

Volta

ge (V

)

Voltage variation without power controlVoltage variation with power control

Figure 15: Voltage variation with or without power control.

nodes is about 24 hours compared to 20 hours without powercontrol scheme. The lifetime is improved by about 16.7%,which illustrates the efficiency of the implemented powercontrol scheme.

7. Conclusions

In this paper, we propose a simple and feasible synchronoussleep and wake mechanism for acoustic positioning WSN.The coordinator of the network will send a beacon framecontaining a sleep command to the network and the nodes inthe cluster will be responsible for forwarding the commandto the attached LNs. Through the network synchronizationmechanism, we can realize synchronous sleeping and wakingof the entire network. Furthermore, we propose a new hybridOSWSP. It is located in the MAC layer but is built with thehelp of microsensor synchronization protocol. The FPGAis used to collect the timestamp of the nodes for the sink,and DSP is used for running the on-demand sleep/wakesynchronization protocol according to the tracking of theobject. The proposed scheme is easy to implement and doesnot increase network overhead because it is integrated in theMAC layer. In our study, we have implemented all of theproposed functions in our sensor nodes and set up a realtest-bed to evaluate the mechanisms. Through the analysisand evaluation of the experimental results, it is confirmedthat the proposed energy-savingmechanisms are feasible andeffective.

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper.

Acknowledgments

The authors wish to thank the editors and reviewers for theirvaluable suggestions to improve the quality of the paper.This research was supported by the National Natural ScienceFoundation of China (no. 61071076).


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