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Simulation and Evaluation of ZigBee basedSmart Home using Qualnet Simulator

Conference Paper · December 2015

DOI: 10.1109/ICSensT.2015.7438456

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7 authors, including:

Hemant Ghayvat

Massey University

10 PUBLICATIONS 8 CITATIONS

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Arun Babu

Massey University


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Md Eshrat E Alahi

Massey University


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S.C. Mukhopadhyay

Massey University

262 PUBLICATIONS 1,796 CITATIONS

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Simulation and Evaluation of ZigBee based Smart

Home using Qualnet Simulator

H.Ghayvat, Liu.Jie, A.Babu, M.E.Alahi, U.A.B.U.A.Bakar, S.C.Mukhopadhyay and X.Gui

School of Engineering and Advanced TechnologyMassey University, Palmerston North, New Zealand

Email: [email protected], [email protected]

Abstract — This research aims to represent the ZigBee mesh

routing and the performance under simulation

environment for smart home. In the realistic smart home,

researcher does not get some of the analysis and results.

Hence, we designed and developed ZigBee best virtual

smart home environment on Qualnet simulator. Finally, we

suggest mixed-mode simulation methodology that

integrates the smart home environment with realistic

wireless sensor network tested hardware to get optimized

system performance.

Keywords- ZigBee, Wireless Sensor and Networks (WSNs);Smart Home; Industrial grade; QOL (Quality of Link); Packet Delivery Ratio (PDR); Packet Success Rate (PSR) and Packet

Error Rate (PER)Energy consumed, simulation, smart home.

I. I NTRODUCTION

The smart home technology was primarily developed forautomation of commercial structures, and gained globalacceptance for commercial property. Technical improvementsare getting smart homes that reverts to individuals’requirements and desires within range. People spend most ofthe time of their life either at home or workstation. In the 21stcentury, science developments have allowed us to enhance thecomfort and housing offered by the home environment.Understanding the user behavior into the home ambient isuseful in making the home environment smarter and relativetowards our necessities. The smart home technology is theintegration of wireless communication network and embeddedelectronics devices. A wireless sensor network is a distinct kind

of communication and sensing network that usually comprisesdata logging, storage, distribution, and analysis system. Thedata storage and energy constraints requirements differentiatethe WSNs from other communication networks technologies.Every research and development work should be tested andevaluated before its implementation in the realistic domain. Asuccessful WSNs based smart home deployment requires thedesign methodologies and approaches be verified before theyare applied for a specific hardware solution. Developing andanalyzing the model, testing and evaluating the WSN protocoland associative architectures and services for WSNs can beexamined by test-beds as well as simulation. The approach of

test-beds and analytical models is quite effective, but it is notfeasible in terms of time required to setup the network, cost andcomplexity associated with deployment. Analytical methodsdemand some simplifications to model and forecast the system

performance. Hence, analytical methods are incongruous dueto the complication and diverse nature of node density, nodemobility, network architecture, communication medium and

channel characteristics. On the other way overgeneralizedmodels, most of the times lead to erroneous results. Accordingto the research study, 53% of the researchers used simulation intheir research [1,9 and 10].

Fig.1 represents the different methods of performanceevaluation that are analytical modeling, simulators, realdeployment and testbed. The urban environment constraints ofWSNs restrict their genuine communication and data

processing potential. Hence, by the application of these above performance evaluation tools the analysis of deploymentenvironment and management of sensor nodes is a puzzlingendeavor [10-12].

Figure1. Performance evaluation techniques

Simulators, test beds, and emulators are significant tools toexamine the algorithms and methodologies at design anddevelopment process before implementing in the real world.In the recent time, much simulation tools have been developedto address the issues of WSNs deployment and these tools arefurther extended to application-specific simulators. These toolsare built by different designer and companies that differ indesign goals, protocol, and standards abstraction level. The

2015 Ninth International Conference on Sensing Technology

978-1-4799-6314-0/15/$31.00 ©2015 IEEE 579

mailto:[email protected]://www.researchgate.net/publication/257719648_An_Overview_and_Assessment_of_Wireless_Technologies_and_Co-_existence_of_ZigBee_Bluetooth_and_Wi-Fi_Devices?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/224154272_Enhanced_Self-Configuration_Scheme_for_a_Robust_ZigBee-based_Home_Automation?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/260586065_An_Intelligent_Self-Adjusting_Sensor_for_Smart_Home_Services_based_on_ZigBee_Communications?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/260586065_An_Intelligent_Self-Adjusting_Sensor_for_Smart_Home_Services_based_on_ZigBee_Communications?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/224154272_Enhanced_Self-Configuration_Scheme_for_a_Robust_ZigBee-based_Home_Automation?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/257719648_An_Overview_and_Assessment_of_Wireless_Technologies_and_Co-_existence_of_ZigBee_Bluetooth_and_Wi-Fi_Devices?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==mailto:[email protected]


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below table 1 represents different WSN specific simulation tools with their relative features and limitations [13-15].

Table 1: Summary of reviewed simulation tools

Simulationtool

License Simulationcode support

Simulationcodeexportable

Protocoldesign andimplementation

possible

Dynamicchanges innetworktopology areallowed

CustomextensionforindividualWSNsimulation

Key Features Deficiencies

Qualnet Commercial

C,C++ Yes Yes Yes Yes -User-friendly GUI tosee 3D view

-Capabilityof generatingthe results forlower to upperlayer

-Supportsimulation andemulation

-One of theexpensive simulationtool

OPNET Commercial

C, C++ Limitedextend

Yes Yes Yes -Feasible toapply full potential of programminglanguage

-For systemcharacteristicsdescription, ituses hierarchicalmodel

-Scalability andmeasurability

issues

NS-3 Opensource

C++ Limited Yes Yes Limited -Supports areal-timeschedule

-Supports

simulation andemulation

-GUI is very limited

- Does not allowreal hardware code

- Scalability problem

OMNET++ Openaccess foracademicand fullversioncommercial version

C, C++ Limited Yes Yes Yes -Supportsstandard energymodeling

-Doest allow real-time OS execution timemodeling

-Does not have 3Dradio modeling

TOSSIM Opensource

C, C++,nesC

Yes Yes No Yes -Can bedirectlymodified at end-device node

-All thenodes share thesame codeimage

-This is moretowards the lot ofassumptions about thetarget hardware platform

GloMoSim Opensource

C/Parsec Limited Withsomelimitation

Yes Yes -follows alayeredapproach

-usesstandard APIs betweendifferentsimulation

-accuracy is low


978-1-4799-6314-0/15/$31.00 ©2015 IEEE 580

https://www.researchgate.net/publication/259996710_Management_and_applications_of_trust_in_Wireless_Sensor_Networks_A_survey?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/259144114_Context_Aware_Adhoc_Network_for_Mitigation_of_Crowd_Disasters?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/262578209_A_Ubiquitous_and_Low-Cost_Solution_for_Movement_Monitoring_and_Accident_Detection_Based_on_Sensor_Fusion?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/262578209_A_Ubiquitous_and_Low-Cost_Solution_for_Movement_Monitoring_and_Accident_Detection_Based_on_Sensor_Fusion?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/259144114_Context_Aware_Adhoc_Network_for_Mitigation_of_Crowd_Disasters?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/259996710_Management_and_applications_of_trust_in_Wireless_Sensor_Networks_A_survey?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==


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layers

SensorSim Opensource

C++ Limited Limited up tosome of theWSNs

Yes Yes -Its mainfeature itsupports protocolmodeling withvariouscommunicationchannels and

relative powerdemand

-Supportdifferentscenarios ofurban andsuburbandeployment

J-Sim Opensource

Java Yes Yes Yes Yes -It is goodto generatesome patternfrom the WSNsdeployment

- Providegood interface

to implementthe simulationcode to realsensor nodes

-Quite complicatedto use and difficult to program

-It includes extraoverhead informationfor internetworkcommunication

Dingo Opensource

Python Yes Limited

Limited Yes -Offersexcellentvisualizationand GUI

-Programminglanguage can beexploredcompletely

-Tools arespecifically designed toWSNs but failed to offerfull support at physicallayer

This paper is organized as follows. Section-II describes thesmart home system and description of deployment. Section-III

presents the results of real smart home and details thelimitation of these results. The necessity of Qualtnet simulatorand emulator is discussed in detail with experimental analysisand results in section-IV. Lastly, the conclusion and futurework is presented in Section V.

II. SMART HOME SYSTEM DESCRIPTION:

WSNs based smart home system we have designed andimplemented for ambient assisted living. This system contains

heterogeneous sensors. The wireless sensor nodes are deployedaccording to individual ambient requirement. The wirelesssensors data is collected into local home gateway serverthrough the receiver. These data packets are further analyzedthrough data mining and machine learning algorithm. The finalinformation is uploaded onto the website for remote access [2-8]. Fig.2 shows the heterogeneous sensor deployment into thehome for ambient assisted living.


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https://www.researchgate.net/publication/224193460_A_Zigbee-Based_Wearable_Physiological_Parameters_Monitoring_System?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/273393907_Wearable_Sensors_for_Human_Activity_Monitoring_A_Review?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/276070664_WSN-_and_IOT-Based_Smart_Homes_and_Their_Extension_to_Smart_Buildings?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/276070664_WSN-_and_IOT-Based_Smart_Homes_and_Their_Extension_to_Smart_Buildings?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/273393907_Wearable_Sensors_for_Human_Activity_Monitoring_A_Review?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/260508373_Towards_the_Implementation_of_IoT_for_Environmental_Condition_Monitoring_in_Homes?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/260581551_Wireless_Sensor_Network_Based_Home_Monitoring_System_for_Wellness_Determination_of_Elderly?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==https://www.researchgate.net/publication/224193460_A_Zigbee-Based_Wearable_Physiological_Parameters_Monitoring_System?el=1_x_8&enrichId=rgreq-0b2c4d28-40a9-49f1-8df1-e37d03f3859f&enrichSource=Y292ZXJQYWdlOzI4NjcyMjQyMjtBUzozMDYxMzQ1NDI0MjIwMTlAMTQ0OTk5OTU3MDMzNQ==


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Figure 2: Home layout to represent wireless sensor deployment

III. SMART HOME RESULTS AND LIMITATION:

The research emphases on the statistical description ofIEEE 802.15.4 ZigBee’s physical and medium access layer(MAC) consistency towards smart home. Smart homemonitoring is moreover, utilizing the building automationsystems to the urban residential environment. So we candescribe the smart home monitoring as the application of

computerization to integral systems of accommodationfacilities to enhance and improve the everyday life of aresident. The testing of ZigBee wireless sensor communicationwith its characterization is not documented thoroughly in anurban scenario. In this research, we use ZigBee protocol basedXBee series 2, and packet delivery ratio and latency isobserved in genuine, smart home monitoring system instead ofany testbed setup. These results are functions of distance,hopping, and obstacles.

Fig.3, 4, 5 and 6 shows the packet reliability parameter as afunction of end-device and coordinator spacing and someobstacles between them. With the increase in distance andnumber of obstacles between wireless nodes the packet

delivery ratio (PDR) and packet success ratio (PSR) reduces,while packet loss rate (PLR) and packet error rate (PER)increases. In the figure, obs1 means one obstruction, obs2means two obstructions, obs3 means 3 obstructions and obs4means 4 obstructions between transmitter and receiver. Fig.7shows how the delay varies with respect to spacing betweennodes and obstructions.

Figure 3: PDR as a function of distance and number of obstacles betweentransmitter and receiver

Figure 4: PSR as a function of distance and number of obstacles betweentransmitter and receiver

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Figure 5: PER as a function of distance and number of obstacles betweentransmitter and receiver

Figure 6: PLR as a function of distance and number of obstacles betweentransmitter and receiver

Figure 7: delay as a function of distance and number of obstacles betweentransmitter and receiver

For complete system performance analysis, we need someother parameters of different layers. The simulation is the onlysolution to generate these parameters.

IV. QUALNET BASED SIMULATION FOR SMART HOME:

The qualnet simulator we have used to design and generatethe WSN based smart home environment. Below results showsome of the parameters that we do not get in realistic, smarthome setup. These results are simulation based and help up tosome extend to analyze system performance. Fig.8 representsthe deployment of wireless sensors in the home environment.The home environment is generated through the Qualnet

simulator with the use of C/C++ programming language. Wekept same technical specification and parameters for RFmodule, electronic appliances and other household stuffs whichwe have implemented in real world smart home. Thisdeployment environment contains local home gateway serverwith coordinator. Fig.9 shows the consumption of energy inidle mode. Wireless nodes 3, 9, 10 and 12 consumed lessenergy as compared to other nodes. These nodes are end-devicenodes which transmits the data and return to idle mode.Remaining nodes are router-end device nodes, these nodeshave the responsibility to transmit their own data and relay thedata of neighbor nodes. Fig.10 shows the beacon requestsgenerated by different wireless nodes. The majority of requests

are generated by the wireless nodes which we configured as arouter- end device. Fig. 11 represents the average path loss indB of all wireless nodes. This path loss is the function ofdistance and multi path fading. All wireless nodes faced theslightly different level of path loss.

Figure 8: Wireless sensors deployment in the smart home simulation

environment

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Figure 9: Energy consumption in idle mode by all nodes in the network

Figure 10: Number of beacon requests generated by nodes

Figure 11: The average path loss (dB) comparison between node


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CONCLUSION:

The smart home system environment implemented at twodifferent levels, first at real world home and another one issimulation environment. The results of simulation environmentcould help another researcher to understand the characteristicsof other different parameters that we do not find in realistic,

smart home results.

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No.5, pp. 8961-8983

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