NETWORK NODE SIMULATION OF ROUTE IDENTIFICATION ALGORITHM (NNSRIA) USING RESOURCE LOCATION PROTOCOL IN VANETS

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[Subalakshmi *, 5(11): November 2018] ISSN 2348 – 8034 DOI- 10.5281/zenodo.1689937 Impact Factor- 5.070

(C)Global Journal Of Engineering Science And Researches 353

G ^LOBAL J ^{OURNAL OF} E NGINEERING S CIENCE AND R ^ESEARCHES

NETWORK NODE SIMULATION OF ROUTE IDENTIFICATION ALGORITHM (NNSRIA) USING RESOURCE LOCATION PROTOCOL IN VANETS

Dr. M. Subalakshmi

Principle, Sri Saradha College for Women Perambalur-621113

ABSTRACT

Vehicular ad hoc network (VANETs) is a technology in the field of communication. Vehicular ad hoc network nodes provide real observed information from the different environmental conditions for monitoring and controlling systems. A track in VANET is considered to be a smart mobile node, and it is capable of communicating with its neighbors and other tracks in the network. A problem of uncertainty location of a network node route identifying a long time. So that, the development of Network Node Simulation of Route Identification Algorithm (NNSRIA) is the best route identification of shortest time in network window. In VANETs three feasible algorithm created by the network node for initial location node simulation, the stationary location of route simulation, the shortest time in route identification. For the node simulation of distinct localization minimize the energy on the network, improve communication effectiveness, and maximize the throughput and efficiency of the network. The fixed location of route simulation improvement in the network lifetime is also achieved by using various route such as Road Side Units (RSUs) techniques ongoing by the node. Shortest time in route identification algorithm will complete the efficient data transfer and optimal route identification of all the anchor nodes. In this method using have route identification of most concise time network route view from system nodes.

Keywords: Location-based service, VANET, Node Identification of Route Simulation, resource location protocol.

I. INTRODUCTION

Mobile Ad-hoc network (MANET) is data globally as a communication system. A MANET is generally defined as a network that has many free or independent nodes often composed of the mobile node or other mobile pieces that can arrange themselves in various ways and operate without strict top-down network system. Mobile Ad-Hoc Networks is integrated with wireless nodes that can communicate anywhere.

Vehicular Ad Hoc Networks is technology that assimilates the skills of new generation wireless networks to trucks.

A VANET node is an internet connected device whose position and point of the route to the internet may traditional be changed. This kind of location node is often a mobile phone or laptop computer, although a node can also be a router identification. Different support is required to maintain internet connections for a network node as it moves from one node to another subnet node, because traditional internet routing assumes a device will always have the same address. Therefore, using standard routing procedures, a network user would have to change the device address each time they connected through another network or subnet.

A mobile device to wireless short on the operating with hand type mobile use among providing a touchscreen, touch keyboard or physical keyboard in the mobile application. In this mention by the mobile apps, Google drive, Google maps, what apps, telegram, Facebook, etc. In point out the application denote on a network node connected with a mobile device. It used for VANET network location identification of map with a network node in the active position. The mobile network device multiple route tracking with providing software developed to live video user point out the location. Software technology advance location further allowed network domain in this area place on the active server.

It performs the world level working for real-time node we identification the global position targeted by the most significant web application attack traffic, cities with the slowest web connections — a person various application

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visited from shortest time work thoroughly. In this technologies VANET module node reveals privacy technologies turn on with device tracking. That person is tracking user transportation attacker focus commonly in a network node.

Network node possible on application download, the installation of the malicious with permissions related to location.

The mobile node positioning the operation will be wireless singles location like suffers from current permission smartphones — all the VANET device multiple bandwidths on frequency radio signals. Since the earth magnetic data access accordingly functions digital compass implement the smartphones. The driver may random data read by the angle key area available extracting node technical challenges enable rotation. In this idea from smartphones sensor mode active and release data in performance the network wireless data communication.

A mobile network node is a visual node of a computer device or network node. It shows the components that make up a network node and how they interact, including the mobile device. Route our network, and all the elements it communicates with can be done using a cellular network software like communication. When the VANET chip installed in a brilliant smartphone gets signals from more than four distinctive satellites, the three-dimensional area of this savvy cell phone can be resolved dependent on trigonometry.

The sensor provides touring every scheme pedestrians about service neighboring information current geo-location:

wired and wireless network node using 3G/3.5G/4G even if they keep moving or a stationary system. The network members have inspected this archive, it was software developed, and the other supported by a director as a node recommendation node gatherings and invested individuals. It is a steady record and might be the utilized as reference material or referred to from another archive. The network node is to attract consideration regarding the determination and to advance its great organization.

Website login to your mobile device view in the page all the node location monitor from an application. In current location view tracking moment find out the zoom in selected one location. In the location history inside view, address, neighborhood, city, latitude, longitude under the map. In mobile site, location control history option the touch map view from all area. It can perform a transmission function that is not available mobile phone. Tracking status full data view inside location joining with setting with user editing. VANET location finds out the zoom in and zooms out exploring, driving, transport different map type. In this type default, satellite route individual tracking moving, update on the device. In the one device view, you can view tracker state tracking or stopped battery level, and its track interval. If there are any new tracker errors, you will see a link to access to the errors.

Route rotation of utilizes your mouse on the guide stamp your location. Right snap an area of the guide and select include marker. When the tag is made, you can move it anyplace on the guide by hauling it. Network location can include a name by right tapping the marker and choosing include content. Route identifier the make in various markers by rehashing this procedure. Your tags will be evacuated when you reload or close the guide page.

The procedure pursues a basic numerical rule called trilateration. To finish the utilizes the exact position of something mathematical diagrams like four satellites and the separation VANET beneficiaries to each to gauge 4 esteems: earth scope, earth longitude, rise and time. The position and departures to a given satellite decide the situation of the beneficiary. The precise location of a satellite is more than once transmitted to all beneficiaries in the observable pathway and more often than not require open sky. The separation to a satellite is found by the transmission touches base at the beneficiary exact time the satellite. The time produced each clock is transmitted by the satellite at preset interims satellite's nuclear.

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Figure 1.1 VANETsystem connection

Figure 1.1 in the main idea VANETsystem vehicle unit to data for list local database. In the device from network main station connecting identification location. Each microwave signals of in orbit send to a receiver these satellites.

The finally all device determined system exact position the planet meters based on distances triangulates. Object or person in real time certain determination of location.

Network node and mobile node protocols can be shared up based on their intended range of system. Node with minor ranges of size to have minor node requirements and often have less sound to deal. However, minor node are only able to communication with minor network of user, to compare with larger mobile nodes. Increasing the number of user in a mobile network is often more useful, but more aggressive techniques need to be employed to prevent information collisions among multiple users in a large mobile network.

Required all information in this method plan a touring scheme where location search in the map. For source address to destination address will be binding list marker point at the end of this location. Every object synchronizes or effective asynchronous cost. The same time or different time multiple user various conditions source data proximity of bandwidth availability. VANET with enables device process of transferring a single type user.

II. RELATED WORK

The popularity of social media over the past several years, web sites such as twitter, has presented a network for up to the minute information on events across the globalVANET. The information presented on these sites can be extremely helpful in the case of an emergency, however, the amount of data to examine and the low node of geo location on this site makes it difficult, if not impossible, for emergency services to respond to information gathered from social media [1]. The mobile node development of the data over the web makes a pivotal undertaking to make arrange protected and secure with numerous user hits and network. VANET based system gives setting mainful

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administrations that assistance connect area with users. This method an overview between various strategies to which is identified with node based networks [2].

The Aim at the direct geo-location application of high-resolution applicationSpecific absorption rate (SAR) images, this method discussed the theoretical principles and mathematical models for effects on direct VANET from attitude angles errors of flight platform, through the phase errors and image pixels geometric, inputting indirectly into the corresponding geo-location model and influencing the final positioning accuracy. And, the relative simulation test and quantitative analysis based on true flight area record data have been executed in the last part of it [3]. Specific absorption rate is naturally contains the mistakes from the beginning nonlinear and earth turn. The combination of SAR picture data may update the SAR picture quality by refresh the network which is a user point of service by the VANET and landscape error [4].

The development of Geographical location standards has open the doors for new strategies and ideas for location- based services, specifically for wireless mobile devices. With the help of VANET, it has become easy to get information of a specific location or find the current locations on our mobile devices. Using networks like Wi-Fi, Cellular networks or VANETpositions, it has become a function of second nature for location our wireless mobile devices know our locations [5]. Specific absorption rate (SAR) satellite mission with scientific and commercial applications, which will be launched. It allows operation in livemap, scan fromSAR and sliding spotlight modes in different polarizations. The sliding spotlight mode is a new imaging mode widely used in high-resolution SAR imaging [6].

To tacking the issue, an exact model of the VANETtravel on the node is determined dependent on the range doppler conditions and the geo line of the uneven geo SAR. The proposed model impeccably coordinates the recreation results and can be generally utilized in both the broadside mode and the line method of the spaceborne SAR [7].

The previously mentioned Doppler attributes effectsly affect the count of VANETreal time monitoring, which are not considered in the customary model. To take care of the issue, a precise model of the network node is determined dependent on the range-Doppler conditions and the geo line of the map.Authentication driven system that gives a strong layer in the field of lost node localization and that limits the access of information content to specified locations or times with respect to lost node [8] [9].

A method to calibrate the VANET accuracy of optical sensors is presented which is based on a novel multi-modal image matching strategy. This concept enables to transfer points from highly accurate Terra SAR-X imagery to optical images. These points are then used to register the images or to update the optical sensor models [10].The demonstrate a novel method which deploys very fast template matching using location accelerated convolution. The method can be used with template samples from a globally consistent reference set [11].

Our testbed consolidates creation equipment and programming to permit copying of sensible and repeatable versatility situations, in which the portable client can travel long separations, while being served by an application server. The system permits (I) VANET data, (ii) customer organize conditions, for example, transmission capacity and misfortune rate, and in addition (iii) the application remaining burden to be copied synchronously. To delineate the intensity of the structure we additionally present the plan, evidence of-idea execution, and assessment of a location scheduler for application refreshes in cell phones [12].

For the measurement error will significant increase the locate uncertainty, the Recursive Least Square (RLS) estimation is used to estimate the target position and the relative height. The RLS estimation can give agreat estimation of the target position which means the target location accuracy can be greatly improved by accumulating a large quantity of measure points. Simulation results have verified the efficiency of the method [13]. One of the most important features of smart distribution networks is handling fault situations in an efficient way. This work describes a fault location algorithm for three-terminal transmission lines based on wavelet transform and Artificial Neural Network (ANN). Because of small size database, Recurrent Neural Network (RNN) was utilized and for the

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purpose of synchronized time tagging, the restricted stock units (RSUs) with the highly-accurate timing capabilities is used [14].

The locator installed at each bus bar in a distribution network is used to capture the fault generated high-frequency voltage transient signals and recorded the instance when the initial travelling wave generated by the fault arrives [15]. A power line fault produces a fast rise-time traveling wave that emanates from the fault point and propagates throughout the power grid. Each remote time-tags the traveling wave leading edge as it passes through each corresponding substation equipped with a fault locator wireless. The system requires a valid remote time tag on both sides of the fault point to calculate a fault location [16].

A point of area can easy the activity weight. In this method, a substantial arrangement of worldwide situating framework location information of taxi in city is utilized to find the taxi stand. By breaking down in excess of 300 million taxi driving information in Jinan, serviceconnecting, the parallel K-implies calculation is connected on the group investigation dependent on spark disseminated figuring system [17]. Within the cellular networks, movement track of mobile station (MS) is provided by the location management. Location of mobile station has great attention and has potential for application and services to improve both location-based services and cellular network performance. So, several research are worked to develop methods and algorithms which increase the positioning accuracy and execution time [18].

Because of the developing number of area based administrations in vehicular digital physical frameworks (VCPS).

In vehicular confinement, node blackout is a testing issue considering the developing urbanization including elevated structures, staggered flyovers and scaffolds [19]. Moreover, this assault neither solicitations client consents identified with areas for establishment, nor does its task depend on remote signs like Wi-Fi situating or experience the ill effects of flag spread misfortune. Just the points of an auto's turning estimated by the magnetometer sensor of a driver's cell phone are used. Without loss of consensus, we center on auto following, since autos are prominent transportation devices in created nations, where cell phones are regularly utilized. Motivated by the instinct that an auto may display distinctive turning edges at various street crossing points, we find that an aggressor can coordinate auto swinging edges to a guide to surmise the genuine way that the driver takes [20].

III. MATERIALS AND METHODS

The proposed method of Network Node Simulation of Route Identification Algorithm (NNSRIA) of route identification was used to get the network node, location of data simulation in the shortest time to get from the route feasible. Simulation of node traveling by the network system in the identification of source node. NNSRIA algorithm to solve the problem of network node route deployment is possible. In VANETs distinct Localization Approaches, Routing protocols are used to minimize the energy requirement, improve communication effectiveness, and maximize the throughput and efficiency of the network. It generates from the mobile node in the sequence of group node simulation. The group node creates by the networking system for data available from the node with send from source. The packet sends from source to other child node information sharing for the shortest time. Source location one text, and destination another text collection of data draw the polyline code with a map. Polyline code is a Road Side Units (RSUs) of with allowing customize visual aspects. The minimum polyline range or maximum range symbol it appears on the VANETs. Follow the Android device and configure instructions to the enable developer options on your system to detect the device. In VANET greedy node or the other user can be the network to a greater extent by network mechanism that ensures that the actual nodes send the messages.

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Figure 3.1 Implementation of propose work architecture

Figure 3.1 Internet service and without service in VANETs tracking device location bind on the mobile application.

In user registration of device location updated in receiving the data only sending call location route draw. Node initial data are adding within server retrieved from network system. Which route searching device in server catch all information.

3.1 Initial Location Node Simulation

The traditional network method is often implemented using initial node creating by the VANETs. To apply the VANETs to the location identification problem a network model and a dimension model must be provide the number network node create. We use a simple random location model as our network model the mobile model used in the filter is different from the mobile model used in the initial simulation node to enable with node movement of network service code by VANETs. The system assumes that at any initial in shortest time the node moves with a random. For ultimate latitude and longitude place on point identification object position. In where is place motion of the pedestrian would send a location add in database current location. Location based service result determined by the VANETs.

. Algorithm

Input: search place (sp)

Output: draw on node location (dgl) Step1: Start

Step2: user plan efficient touring scheme in where location not identification dynamically mobile application. On current location placed Google map.

Step3: in mobile application live from location by the VANETs.

Step4: VANETs node location draw in map color fill different route. For condition check place on route (R).

Step5: if (R! = null)

User which route selected for data position location.

Else

Not selected location VANETs node device de actives Step6: initial location success on object.

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Step7: draw from VANETs Step8: Stop

Figure 3.2 Initial Location Node Simulation Data Flow

Figure 3.2 User plan efficient touring scheme different area from source to destination geo-location draw the map user selected from route.

3.2 Stationary Location of Route Simulation

Previously, we wireless node simulation of initial the statement that the complete route identification is received from the neighbor. This is wireless node communication by the VANETs given to limited bandwidth of mobile ad hoc networks, as it consists of a large number of node and their route data provide. Therefore, we proposed system of a simple yet effective route simulation that allows the data distribution to be transmitted in a compact form.

Start

User plan efficient touring scheme

Mobile application live from location by theVANETs

if (R! = null)

User which route selected for data position location

Not selected location

Draw from node- location

Stop

No

Yes

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Algorithm

Input: draw on geo-location (dgl)

Output: Geo-location Data bind Stationary (gbs) Internet available - IA

Step1: Start

Step2: network route node available If (IA == ‘Yes’)

Network route Else

Spectrum sensing

If (Spectrum sensing Data Stationary == ‘Yes’) Spectrum sensing Data Stationary Else

Denotes by network map place on location bind Stationary Location sensing spectrum list

Step3: network map place on location bind Stationary search in data will be list out the maps Step4: Stop

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Figure 3.3 Stationary location search data flow diagram

Figure 3.3 internet available on geo-location with data transmission condition checking with map. Stationary of location to bind Google location search all information.

3.3 Shortest Time in Route Identification

Computer monitoring in collection of data exploring location search. In device variety pedestrian Maximum Searching Range (MSR) must be sum of location range. According to VANETs accuracy walking and any vehicle travelling speed in different calculation range. In maximum latitude point, longitude point traveling speed 30 meters position of sensor Road Side Units (RSUs) method. In an implementation of VANETs sample route with drawing the place on different position on the time seconds in marker view from network. Hence, the proposes a simple network 3-axis displacement embedded field exploring search estimation mechanism based on the sensor in this work.

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Algorithm

Input: VANETs Data bind Stationary, location x1, x2, location y1, y2 Output: Route icon of direction destination location identification Step1: start

Step2: Read the VANETs

Step3: condition of location is not detected checking the VANETs signal loading the network Step4: location identification of Road Side Units (RSUs) desired with map

Step5: different location source to destination calculation for example Location x1, location x2, location y1, location y2

In all location source to destination travelling route.

Step6: the location distance between areas of original point reign Placed.

Step7: icon of direction destination route with network location and displaying Step8: stop

Figure 3.4Shortest Time in Route Identification data flow diagram

Start

Location x1, x2, location y1, y2 initial VANETs ON / OFF

Valid ON / OFF

Read the network location

Location identification of Road Side Units (RSUs)

desired with map

Location distance between areas from the route identification

Stop

Off

On

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Figure 3.4 Location x1, x2 another location y1, y2 VANETs location ON / OFF valid for location read the database on geo-location identification POI implementation desired with map. It between the wireless node areas.

IV. RESULTS AND DISCUSSION

In this Purpose of our data communication in the wireless local area network simulated in NS-2, in that delivers results for wireless networks. Network Simulator was is an object-oriented programming tool use command type language. The simulated sessions in each run, with random source and destination pairs. Proposed idea from approaches are simulated using network simulator, then the all code is created into TCL script. Different kind of proposed approaches are here in our work they are Network Node Simulation of Route Identification Algorithm (NNSRIA)with compared to existing system for Location Signature Obtain from Mobile Node (LSON) and Synthetic Aperture Radar (SAR).

4.1 Packet delivery ratio Impact:

Data packet transmission of one node to another node data delivery represents all packet in this network.

PDR = Packets received/Produced parcels * 100 --- (4.1) Table 4.1 data packet transmission analysis

No. of. nodes SAR in % LSON in % NNSRIA in %

10 12 19 22

20 25 35 39

30 35 42 49

40 45 58 68

50 56 68 89

Table 4.1 Packet delivery ratio compare with existing system the Synthetic Aperture Radar (SAR) and Location Signature Obtain from Mobile Node (LSON) better this proposed system high level data delivery Network Node Simulation of Route Identification Algorithm (NNSRIA).

Figure 4.1 Comparative Analysis

Figure 4.1 shows about the packet delivery as percentage. In this graph x-axis represent the number of nodes and y- axis represent the packet delivery percentage. From this graph Synthetic Aperture Radar (SAR) indicates orange, Location Signature Obtain from Mobile Node (LSON) indicated in yellow, Network Node Simulation of Route

12

25 35 45

56

19

35 42

58 68

22

39 49

68

89

10 20 30 40 50

Packet delivery ratio In %

Number of nodes

SAR LSON NNSRIA

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Identification Algorithm (NNSRIA) indicated in green with all system comparison of the new propose system of data packet delivery high position range.

4.2 Analysis of End- End Delay

Packet in a network end to end delay data transmission is nothing but between the times to take from one packet to another.

Table 4.2 End to End Delay Analysis No. of. nodes SAR in % LSON in %

NNSRIA in %

10 14 12 10

20 26 25 24

30 38 37 33

40 49 48 44

50 62 60 53

Table 4.2 exhibitions the conclusion to termination defer examination of the planned framework with the current frameworks.

Figure 4.2 End to End Delay Ratio

Figure 4.2 exhibits the E2E examination of the prearranged schemes with the present structures.

4.3 Throughput Ratio

Sometimes called overall network performance is named as throughput ratio, it considers all the QoS parameter to conclude the result in the network. The throughput is the number of bits transferred per second. The performance of the application traffic Time taken, which is denoted by transferred packets, is obtained as,

Throughput= Total number of transferred packets / Time taken --- (4.2) 0

10 20 30 40 50 60 70

10 20 30 40 50

End to end in %

Number of node

End to End Delay

SAR LSON NNSRIA

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Table 4.3 Analysis Table

No. of. nodes SAR in % LSON in %

NNSRIA in %

10 19 22 29

20 25 45 52

30 39 59 69

40 49 61 78

50 62 82 91

With comparison table 4.3 two existing system one propose system of Network Node Simulation of Route Identification Algorithm (NNSRIA) high rate service in the network.

Figure 4.3 Throughput ratio analysis

Figure 4.3 shows about the packet delivery as percentage. In this graph x-axis represent the number of nodes and y- axis represent the packet delivery percentage. Network Node Simulation of Route Identification Algorithm (NNSRIA)shows the proposed system throughput data packet delivery high point range.

4.4 Transmission Ratio

Ns2 entirely reproduces a layered system from the physical radio transmission channel to abnormal state applications. It is something overall network data sender to receiver transaction rate high speed memory point of system.

Table 4.4 Comparison data Transmission Rate No. of. nodes SAR in % LSON in %

NNSRIA in %

20 32 36 45

40 46 47 57

60 55 56 68

80 66 79 84

100 79 85 95

0 10 20 30 40 50 60 70 80 90 100

10 20 30 40 50

Throughput Ratio in %

Number of Nodes

Throughput Ratio

SAR LSON NNSRIA

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The above table 4.4 shows the data transmission communication data send sender to receiver high speed service data passing one device to other device.

Figure 4.4: Comparison of Transmission Ratio

Figure 4.4 it data transmission node source to destination travelling on network. In this data values high level transfer for good output. .

V. CONCLUSION

The User Mobile Planning for Network Mobile Phone has been proposed from the identity card for the VANETs system. Some of the VANETs Knuckle Impact Some of these strength contact will be the live compilation of your physical space terminal. Mobile node even in the city or registered voters mail area ID below. MANET can be made to relate to the real location and the node can be allowed to achieve a higher confidence level. As for the law enforcement agencies trying to make an online mobile node, from the international locality, the solutions need very simple time. This is the VANETs of the mobile terminal for performing various simulation tasks, and they will be useful for an individual's physical location to better serve online advertising.In this proposed work scheduling scheme achieves improved throughput in 91% resource location protocol using high data transmission. In future work, Google maps on database retrieved from the server that data time calculation of traveling node. In this node location bind on physical node type. The architecture allows a target of driver on-road outage Network Node Simulation of Route Identification Algorithm (NNSRIA)with data send from road include on the straight path traversed angles.

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NETWORK NODE SIMULATION OF ROUTE IDENTIFICATION ALGORITHM (NNSRIA) USING RESOURCE LOCATION PROTOCOL IN VANETS

G LOBAL J OURNAL OF E NGINEERING S CIENCE AND R ESEARCHES

NETWORK NODE SIMULATION OF ROUTE IDENTIFICATION ALGORITHM (NNSRIA) USING RESOURCE LOCATION PROTOCOL IN VANETS

User plan efficient touring scheme

Mobile application live from location by theVANETs

if (R! = null)

User which route selected for data position location

Not selected location

Draw from node- location

Location x1, x2, location y1, y2 initial VANETs ON / OFF

Read the network location

Location identification of Road Side Units (RSUs)

desired with map

Location distance between areas from the route identification

End to End Delay

Throughput Ratio

G ^LOBAL J ^{OURNAL OF} E NGINEERING S CIENCE AND R ^ESEARCHES