Scholarly article on topic 'A Review Over Genetic Algorithm and Application of Wireless Network Systems'

A Review Over Genetic Algorithm and Application of Wireless Network Systems Academic research paper on "Computer and information sciences"

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Abstract of research paper on Computer and information sciences, author of scientific article — Bimlendu Shahi, Sujata Dahal, Abhinav Mishra, S.B. Vinay Kumar, C. Prasanna Kumar

Abstract Tele-communication and network industry are becoming extremely fascinated by the use of evolutionary smart sensor nodes in wireless sensor networks. This technology promises to overcome several challenges within WSNs needed for real time data protection via optimization technique: Genetic Algorithm. This paper reviewedthe use of Genetic Algorithms (GAs) to solve certain limitation of wireless sensor networks. It further presents major application areas of wireless sensors networks. Longerdistance gap between a sensor and destination in a sensor network can remarkably reduce the energy of sensors and can degrade the life of a network. GA can prolong the network lifetime by minimizing the total communication distance.

Academic research paper on topic "A Review Over Genetic Algorithm and Application of Wireless Network Systems"

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Procedía Computer Science 78 (2016) 431 - 438

International Conference on Information Security & Privacy (ICISP2015), 11-12 December 2015,

Nagpur, INDIA

A Review over Genetic Algorithm and Application of Wireless

Network Systems

Bimlendu Shahia, Sujata Dahalb,Abhinav Mishrac, Vinay Kumar.S.Bd, Prasanna

Kumar.C6

a'bM.Tech 1s sem in Embedded system Design,School of Engineering & technology,Jain University,Bangalore-5621121ndia cB.Tech 3rd sem in ECE,School of Engineering & technology,Jain University,Bangalore-562112, India. dAssistant Professor,Department ECE, School of Engineering & Technology, Jain University,Bangalore-562112,1ndia eAssociate Professor,DepartmentECE,Sahyadri College of Engineering & Management,Mangalore-575007, India

Abstract

Tele-communication and network industry are becoming extremely fascinated by the use of evolutionary smart sensor nodes in wireless sensor networks. This technology promises to overcome several challenges within WSNs needed for real time data protection via optimization technique: Genetic Algorithm. This paper reviewedthe use of Genetic Algorithms (GAs) to solve certain limitation of wireless sensor networks. It further presents major application areas of wireless sensors networks. Longerdistance gap between a sensor and destination in a sensor network can remarkably reduce the energy of sensors and can degrade the life of a network. GA can prolong the network lifetime by minimizing the total communication distance.

©2016 The Authors.PublishedbyElsevierB.V. This is an open access article under the CC BY-NC-ND license

(http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-reviewunder responsibility of organizing committee of the ICISP2015

Keywords/Wireless sensor network, Genetic algorithm, Sensor nodes, Internet

* Corresponding author. Tel.: 91-9465360473; fax: E-mail address.■bimlendu_yo@yahoo.com

1877-0509 © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license

(http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of organizing committee of the ICISP2015

doi:10.1016/j.procs.2016.02.085

1. Introduction

Variation of applications from small home environment to large habitat monitoring has made Wireless Sensors Networks (WSNs) more popular nowadays. With the recent advancement in micro-electro-mechanical systems (MEMS), wireless communication and digital electronics, Wireless Sensors Networks (WSNs) is becoming more popular and give rise to development of smart sensors nodes.Node placement, network coverage, clustering, data aggregation and routing are general operational stages of Wireless Sensor Networks. Node placement is a compulsory stage before establishment of Wireless Sensor Networks. Types of nodes layout depends upon the application. Depending upon the coverage area, layout and connection of sensors within the network must be done in an effective manner to achieve optimum utilization of energy and financial resources. In optimization of WSNs, clustering is another important stage. By clustering, division cluster each having cluster head is formed. Cluster head collects data from the nodes and forward data either to the other clusters for further operations or directly to the sink to reduce communication heading. There may be one or more sink nodes (Base stations) too in a wireless sensors network to accumulate information and pass it to a central processing unit and storage system. Multiple sinks help in minimizing worse case delay for message transfer. Thus, clustering is better approach for load attenuation within the networks. Moreover, it is better approach to save energy and increase sensor's lifetime in network. This also provides improved data security, less unused data and better scalability. While aggregating valuable data are collected from the sensors and those data are forwarded to the base stations. Data latency and residual energy balance among the nodes are two important factors to be considered in this period.

In Wireless Sensor Networks, smart nodes collaborate with each other and perform specific sensing task in an existing environment. The smart nodes have one or more sensors depending upon circumstances to sense the data within the application area. Nodes of Wireless Sensors Networks are smaller in size, cheap, robust and consume low power as compared to traditional sensors. Since the sensors are deployed in difficult location a radio can be used to transfer data to the base station. In a sensor node a rechargeable battery is used for power supply. Solar cell can be another option for chargeable power source. So, optimum energy utilization is one of the factors to be considered during WSNs design. To complete certain tasks right and reliable sensors, computational unit, adequate memory and optimum communication prerequisites are mandatory in a sensor node. Generally, a smart sensor node consists of one or more sensor elements, a battery, a memory and embedded processor unit and transceiver. A node might comprise of secondary application dependent components like a mobilizer, a power generator or a position detecting system. Sensors and analog to digital converter (ADC) are main components of sensing units. Signals converted by ADC are received by the processing units. Then the processor manages and executes further sensing tasks. For storing data flash memories can be used to reduce cost factor. Transceiver is used to transmit and receive data. Deployment of sensor nodes is shown in fig [1]. The information is sensed, measured and collected from the environment by the smart sensor node and finally through internet passed to the user. Depending on the architecture and complexityof WSNs, many protocols are proposed to meet different application requirement. Since there are relatively small numbers of sensor nodes, global addressing into WSNs is not needed. So, conventional IP-based protocols will not be applicable to WSNs. Similarly self-organization, lifetime, energy limitation, processing, storage and limited bandwidth are other challenging factors to be considered during the deployment of WSNs. Many algorithms have been proposed to address above mentioned problems.In [7], based on technical survey of the operational stages of WSNs limitations were pointed out. Ideal parameters of the networks with optimum efficiency were achieved based on result of simulation in NS, MATLAB and JPAC using Genetic Algorithm. In [20],Heinzelman proposed adaptive protocols called Sensor Protocols for Information via Negotiation (SPIN) that circulates all the information at each node to every node in the network assuming all other nodes within the network are capable base-stations. Though wireless Sensor Networks are very promising technology for various futuristic applications these are not devoid of security threats. Data security is one of the main challenges in WSNs. Techniques like data encryption-decryption (cryptography), steganography (image protection), and physical layer secure access by means of frequency hopping are some of the approaches for secure transmission in WSNs [25].In [31], Babamir and Norouzi presented signcryption method to maximize data security in a type of wireless medical network. Similarly in their next paper they proposed new secure process to provide confidentiality, authentication and integrity. This technique efficiently improves data protection, verification and recovery within the networks.

Fig.l. Wireless Sensor Networks

2. Related Work

The complications of optimal design and management of WSNs increases when principle, characteristics and necessities of application are considered. All these issues have to be dealt with multi-objective non-linear optimization techniques. Thus, the main complication is in finding many near-optimal solutionswithin a limited computing time. Genetic Algorithms (GAs) is one of the most powerful tool, which is suitable for the applications in the multi-objective optimization problem. Various research papers have been proposed by using genetic algorithm in wireless sensors networks [5]. Vinay Kumar Singhet al. (2012) [4] proposed energy efficient routing scheme for wireless sensor networks based on elitist Genetic algorithm. This method allows using improved genetic algorithm to minimize the path length which results in maximum network life.SandeepKaur et al. (2014) [l]proposed wide range of application areas based on genetic Algorithm in Wireless Sensor Network for solving Network optimization Problem.Large distance gap between sensor nodes and base station is one of the main reasons of loss of energy in sensor networks.PuqiNing et al. (2014)[26]proposed optimization procedure based on Genetic Algorithm for high efficiency and low cost coil system design for Wireless sensor Network.HarpreetKauret et al. (2015) [2], proposed the use of genetic algorithm to overcome energy consumption problem in sensors and thus increase the lifetime of network.Wint Yi Poe et al (2008) proposed the use of GA based search mechanism called GASP (Genetic Algorithm-Based Sink Placement Strategy) to place multiple sinks to minimize worse case delay keeping energy consumption as low as possible.Similarly, Jin Fan [3], discuss the IEEE 802.15.4 MAC protocol to address the need for low rate, low power, low cost wireless networking. Clustering algorithm performance can be -enhanced by the use of Genetic Algorithm (GA). Similarly, in [21], A.B.M Alim Al Islamet et al. proposed SSN, dynamic clustering technique for stabilization of wireless sensor networks based on LEACH (Low Energy Adaptive Clustering Hierarchy).

3. Genetic Algorithm

Genetic algorithm is the direct, parallel, problematic search mechanism.GA is one of the main techniques of search and optimization, which is inspired by the Darwinian principle such as natural selection and genetics. In solving the problem of finding the path optimization for WSN,it has been shown that GA performs well.During the search, GA works on a group and gives an optimal and sub optimal solutions and gives the optimal search path within the minimum period of time. It stores the useful information of the individuals from the current population either by the implicitly redundant representations.The lifetime of the network can be increased by this process.lt begins with a population consisting random chromosomes including genes with a binary sequence of 0s and Is. Afterward, optimal solution is achieved by the individuals via iterative processes consisting crossover and selection operators.On the basis of qualification of chromosomes fitness function is determined. Minimum consumption of energy within the network and maximum coverage of WSNs is determined with the help of fitness ofchromosome.lt further ensures to achieving greater energy efficiency in data collection and balancing a residual energy within the nodes to increase network lifetime.

Fig.2.Functional description ofGA

4. Applications

There are various types of smart sensors like thermal, seismic, radar, visual, acoustic etc. in wireless sensor networks. This has broadened the application areas of wireless sensors networks. Better understanding of these application areas and their requirements is compulsion to design the wireless sensor networks. The major application areas are military, health, environment, home and other commercial and industrial areas. Further possibilities of WSN are space exploration, disaster reliefand chemical processing.

4.1Military

Wireless Sensor Network can be implemented in military applications for various functions such as observing protection of forces and terrorist activity in remote zones [9]. With the use of appropriate sensors within the specific wireless network area, detection of enemy movement, identification of enemy force, analysis and the progress of their movement can be done[10]. Sensor networks are implemented with success in the military applications with the formation ofDARPA [11]. In battlefield context, the sensor node provides the following services:

• Monitoring friendly forces and equipment: The sensor nodes will monitor the movement of troops and tanks, providing the relative information to base camps.

• Intrusion detection: Presence of the intruder will be sensed by the sensor nodes and alert alarm will go on. Defense system is then responsible for the prevention ofintrusion, as given in[13].

• Battlefield surveillance: Information from the border, battleground or other critical activities in the area will be gathered by the sensor.

• Targeting: The precise statisticsregarding the target like distance, angle, moving direction etc. can be collected via sensors placed in weapons and this information can be sent to the shooter. So the sensors being placed in the weapons are useful for better target estimate.

• Battle damage evaluation: Smart sensor nodes can be deployed to estimate the damage ofthe battle affected area.

• Enemy tracking and target classification: Specially designed sensors can detect objects moving with significant metallic content so that respective authority can track enemies and ignore civilians.In [19], a novel endocrine-based intelligent distributed cooperative algorithm (EIDCA) for target tracking is proposed based on hormone regulating systems ofhuman. The nodes in wireless sensor networks are enabled autonomously by EIDCA without a centralized control for target detection. This helps in tracking soldiers.

• Detection ofNBC attacks: With the help of specially designed sensor networks, any modification in the existing nuclear, biological and chemical systems can be detected and warning can be for further precaution.

4.2 Health Monitoring

Wireless sensor networks are used in health science and health care system. A personal health monitoring application which runs on PDA (Personal Digital Assistant) receives data from various sensors like ECG, EEG, Sphygmomanometer, etc. then the data received from these sensors is recorded in the database and the report is generated for future reference. Presently, in hospitals, sensor networks are actively used to evaluate patient physiological data. They are widely used to control the drug administration track. Further they help in monitoring patients and doctors inside the hospital. When elderly people are affected by cognitive disorder, wireless sensor nodes could examine them and give the proper feedback. Sensors can be used to store patient's medical history, take a note of vital symptoms in real time and give that data to the computers. Harvard University in collaboration with School of medicine at Boston developed Code Blue, a wireless supporting device that can be used to diagnose patients in various medical conditions. Early detection ofsigns and symptoms ofdiseases help in early treatment and prevention of disease and this can be done by Wearable health monitoring system designed using special types of sensors. Similarly, it is possible to have the necessary treatment at homes for patients after heart attack, Parkinson disease, sleeps apnea etc. [10]-[12] by the use of wearable sensors. With the help of wearable sensors all the physiological signals and physical activities of the patient can be monitored. These sensors may provide audio feedback, virtual reality images and other rehabilitative services which can be monitored remotely by doctors or caregivers for further treatment [13].Muse is an example of wearable sensor used as EEG device to cure attention deficit hyperactivity disorder (ADHD).

4.3 Environmental Applications

Wireless sensor networks can play an important role to evaluate and monitor environmental conditions like temperature, humidity, rainfall etc. and helps in habitat monitoring, pollution monitoring, forest fire detection and flood detection.[14] Automated Local Evaluation in Real-Time (ALERT [10]), developed by the National Weather Service in 970's, is probably the first well-known wireless sensor network used in real world. The important realtime information regarding rainfall and water levelis provided by ALERT so that further evaluationregardingthe possibility of flooding can be done. In University of Hawaii the researchers use sensor networks equipped with environmental sensors and camera to research about endangered vegetable spices [24].

• Habitat monitoring: This type of sensors indicates the reaction of the vegetation according to the changes in surrounding. They also help in identifying, tracking, and measuring the population of different species. The best representative example is the installation of a sensor network in Great Duck Island (GDI), Maine was used for habitat monitoring.

• Pollution monitoring: The pollution level can be monitored, evaluated and examined by wireless sensor networks. It gives warning when certain level is reached. WSN nodes are deployed around the city and the moving public vehicles to monitor air pollution around the city. This helped in providing monitoring data from both stationary and mobile nodes.Data are collected by LTE-M module via Zigbee wireless sensors which are kept on the stations of public vehicles and are sent to the cloud for further analyzed to find out pollution level. This can be supportive in making smart cities[27].

• Forest fire detection: The sensor nodes when placed in forest can help in the detection of fire. An integral network of sensors nodes to measure temperature, humidity, wind speed and the direction which will help the determination of fire risk level and its probable direction. Wireless sensor networks help to locate origin of fire and help to inform respective department to control fire before it becomes uncontrollable. The firebug project at UC Berkeley, with the concept of real time fire monitoring, uses sensor nodes to gather information regarding temperature, humidity and barometric pressure to detect the initiation and evolution of wildfires.

4.4 Agriculture Monitoring

Agriculture research community has been increasingly interested in wireless sensors networks for agriculture monitoring. The parameters like temperature, humidity and soil moisture are sensed by sensors nodes and the information are sent back to the sink. Proposal has also been made to place nodes in surrounding to optimize irrigation and to increase harvest. Data mules, which are carried either by people or dogs, communicate with sensors nodes to collect data. LOFAR_Agro project [23] used in potato field displays the example of crop monitoring. Here wireless sensor networks were used to detect the location in the field where potato can be infected by disease Phytophthora on the basis of information such as temperature and humidity gathered from the relative surrounding. By locating such areas use of pesticides can be minimized by spraying pesticides only in the susceptible areas.

4.5 Industrial Monitoring

Industries are interested in using sensors for cost reduction, improvement of performance and accuracy of machines. Initially, in industries sensors are used for monitoring and then control. For example, wireless sensors are used in Nuclear Power Plant to monitor and evaluate water level in tank. They are also used to monitor temperature and pressure inside refrigerators. Another important application of wireless sensor networks is Machine Health Monitoring. Intel and Rockwell Automation are another example of industrial monitoring having interest in deployment of sensor network in Semiconductor fabrication. The goal is to detect the faulty parts of the equipment that are needed to be repaired or replaced by sensed vibrations of sensors. Intel research labs and British Petrol(BP), conduct joint research project to provide continuous vibration monitoring of the engines inBP's one of the oil tanker in the Shetland Islands of the northern Scotland[3].Inventory Control is another challenging problem in big industries. Generally these large companies expand all over the world. So, the management of the large pieces of machinery, equipment, and different types of products in these companies can be achieved through the use of wireless sensor networks. The sensor nodes can also be affixed to warehouse items. The sensors can tell the user about the exact location or the number of items of that category in the warehouse.

4.6 Public Safety

There are numerous threats to public safety such as natural disasters, accidents in plants, terrorist attacks and sudden collapsing of civil infrastructure like building, bridges, etc. In public safety activity like fire rescue wireless sensor networks can be used. For example, in case of fire in any part of the building, the sensor installed within the building activates the alarm as smoke reaches there.Similarly, a flexible wireless smart sensors framework has been developed for autonomous structural health monitoring (SHM) with the use of Imote2 to integrate hardware and software components required for designing civil infrastructure. This is successfully implemented in the 2ndJindo Bridge in South Korea and the Government of Bridge at the Rock Island, Arsenal in Illinois, USA[22].Moreover WSNs are also applicable in post disaster road monitoring after calamities like landslide and earthquake.Seismic motion sensors, sound sensors and image sensors which are embedded in smart sensors nodes monitor the changes in condition of roads. If the system found any damages in the road, it send warning message to the command center.

4.7Automobile

Sensors when installed in vehicles and connected to WSN can be used to track vehicle. The vehicle tracking application will use sensors nodes to locate a specific vehicle and monitor its movement. This can prevent vehicle

theft as well.Measurement of traffic volume on the multiple lanes can be done with the help of WSN using ultrasonic detectors and a lateral scanning method [29]. Vehicle monitoring and controlling are being done via sensor network since a long ago. Most traffic intersections have either overhead or buried sensors to control traffic lights and detect vehicles load. Generally, video cameras are used to monitor traffic road segments and the video is transferred to human operators at central locations. Instead, low cost sensors can be installed at every road intersection to monitor, detect and count vehicle traffic. A global traffic picture will be generated that will help human operators or automatic controllers to generate control signals by these sensors nodes. Similarly, WSNs can be used to estimate bus travelling section. In Nissin City, Aichi Prefectture, Japan, novel bus location system is being used where sensor nodes are installed in various places like bus stops, operation centre, transceivers on board individual buses, and street light and utility poles along the bus route. This reduced the operation cost as information is exchanged via wireless sensor networks [28].

4.8 Smart home

Very small sensor nodes can be implemented in household devices like washing machines. Remote management of home appliances may be possible by the integrated use of specially designed sensor networks, existing embedded devices and the internet. In [3], University of Massachusetts deploys a set of distributed smart agents throughout the house in The Intelligent Home Project (IHome) to utilize shared resources. Here, shared resources include water, heater and electricity. Similarly, The Aware home Project of Georgia Tech to provide better care to elder and the Smart Kindergarten Projects of UCLA to improve early childhood nursery are other examples of WSNs in home applications.

4.9 Power grid

In Smart Grid applications, Wireless Sensor Networks can provide the necessary information to electric utilities and make them to have greater efficiencies. The real-time information collected by these sensors can be taken into consideration to diagnose problems and further steps can be taken to solve these problems.Similarly in smart grid measurement and tracking of energy production and consumption can be done by WSNs to optimize energy usage.

4.10 Internet of Things(IoT)

Integration of wireless sensor networks into Internet of Things can be done via certain standards like IPv6, 6L0WPAN (IPv6 over low power Wireless Personal Area networks) and M2M (Machine to Machine Communications). To uniquely identify the things in the internet IPv6 is used. 6LowPAN has been used to connect devices to the internet. For successful integration of WSN into IoT, IPv6 over 6L0WPAN protocols should be implemented and deployed in WSNs and Machine to Machine(M2M) communication standard should be used.

5. Conclusion

This paper presents wide range of applications of wireless sensor networks. Health, military, environment, automobile and security are some of the application areas. For example, with the use of appropriate sensors these networks can detect enemy movement, analyze it, and identify enemy force and their progress. In this way sensor networks will provide the end user a better understanding of the environment. In near future, wireless sensor networks will be an integral part of our lives.

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