border surveillance in wireless sensor network system ... · border surveillance as it differs from...

International Journal on Future Revolution in Computer Science & Communication Engineering ISSN: 2454-4248 Volume: 5 Issue: 6 376 –380

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376 IJFRCSCE | June 2019, Available @ http://www.ijfrcsce.org

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Border Surveillance in Wireless Sensor Network System using Log Shadowing

Sensing Model

Shivam Rohilla1, Sukhmani Chabra

2

Student1 – N. C. C.E, Israna, Department of CSE, Panipat, Haryana, India

Assistant Professor2– N.C.C.E, Israna, Department of CSE, Panipat, Haryana, India

[email protected], [email protected]

2

Abstract – Borders are extremely vulnerable and prone to terrorist attacks, smuggling and illegal immigration. Border surveillance application

has become one of promising application areas of wireless sensor networks. A primary objective of this application is the detection of illegal

crossing; intruder in the border area. However, the quality of the intruders detection affected by various conditions such as the sensor density, the

sensor ranges the area width and the intruder crossing paths. The latter is an important factor for evaluating the performance of the WSN based

border surveillance as it differs from one intruder to another. To achieve enhanced situation awareness it is necessary to fuse sensor and

information data. An estimation of the intruders crossing paths is necessary then to provide a proper and efficient design of the network. Log

shadowing sensing model is implemented in this article for maximizing number of barriers. In this implemented fading model, receive power

enhanced using gamma function. The proposed algorithm used of a round-robin approach where end nodes are relaying a keep-alive message to

other end nodes, in order to minimize the number of messages required to keep a continuously consistent view of safety-critical nodes and links.

This article gives robust distributed approach to the border surveillance in WSNs in order to maximize the number of barriers and minimize energy consumption.

Key Words –Wireless sensor networks, border surveillance, Intruder, Surveillance System

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I. INTRODUCTION

An important problem in WSN based surveillance application

is the intruder detection while obtaining long system lifetime,

as well as maintaining sufficient sensing coverage and

reliability. In that case, the detection level of the intruders

within a border monitored area can be used as a performance

metric of the deployed network. In actual fact, an intruder will

try to traverse the border area and reach the destination

without being detected. For this context, most of researchers in

the past research results consider only linear network

architecture [1] and where the sensors are deployed either

randomly or uniformly according to one surveillance line. This

is particularly useful in idealistic situations with perfect

conditions. However, the border areas separating two countries

are generally long of hundreds of kilometers containing

mountains, valleys and rough terrain that can cause significant

changes in the sensors deployment methods and cause radio

disconnection. In addition to this, due to the irregular

geographic conditions making some areas hard to access, the

intruders trying to avoid detection when crossing the

monitored area can choose to penetrate this area following

different and various paths. In fact, the intruder may prefer

some paths because of their geographical advantages and

penetrate through them. Those paths should be geographically

feasible and differ from one intruder to another. Therefore, a

good designing of the WSN should be dined taking into

consideration the intruder crossing paths in such a way that the

overall cost of the network is minimized while guaranteeing

the desired QoS in terms of intruders’ detection [2].

Furthermore, the presence of different and various intruders

crossing paths requires the sensor nodes to be deployed non-

uniformly. In this context, we consider multi-thick lines

architecture where the monitored area will be divided into

smaller zones that we denote subareas. The size of the

subareas can be determined according to the terrain properties

and the characteristic of the crossing intruders. As mentioned

before, the intruders may cross the area according to different

paths [3]. This parameter inspires us to develop a model that

estimates the time spent to cross the area from its entrance

until the exit point. We further provide a sensor deployment

method for better intruder detection rate where we assume that

the set of possible paths that can be followed by the intruders

are known by the system.

Figure 1 Border Surveillance System


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II. INTEGRATED SURVEILLANCE SYSTEMS

Border surveillance makes use of a number of systems that

detect threats and conspicuous behavior. Within an integrated

surveillance system, disparate technologies that complement

one another are installed, the interaction of the data output is

essential. An integrated surveillance system consists of

sensors, exploitation systems (that might also be deployed as

situational awareness displays) and external information

systems. Border is monitored by a range of different sensor

types. Those sensors deliver data to a border surveillance unit

(BSU). However, the areas that are monitored intersect and

data that is of interest for one surveillance unit may also be of

interest for adjacent units [4]. Our architecture allows the

necessary data sharing and accommodation of additional

information from external systems resulting in enhanced

situation awareness

Exploitation Systems

Exploitation Systems are used for the exploitation of

reproduced data. Exploitation can be done in different contexts

and can be specific to the system, data type, area or task. For

exploitation systems that work on products that are produced

from multiple sensors it is important that data are available in

an inter-coordinated data format. Exploited data normally

already contain more enhanced information similar to the

sensor data it has to be integrated adequately into a common

picture [8-9]. This type of information is of interest for upper

decision bodies. Still some special expertise is needed to read

and decide upon it.

Information Systems

Information systems are relevant for the rating/ evaluation of

derived data and information. Weather data can give essential

advice which product sources are of interest in certain

circumstances, systems such as the Schengen Information

System provide data on detected persons or goods and

databases/information services freely available on the Internet

can provide background information for all kinds of questions.

Public information sources are subject of data protection and

the usage of this data has to be legally defined across borders.

The system type, structure, language and concepts that are

used within those systems differ from region to region and

nation to nation. This is why an integration and combined

usage of such system information is extremely complicated

[6].

Sensor Systems

Sensor systems normally consist of the sensor and a ground

station that does the primary data processing and possibly

some exploitation. Combined sensor systems that consist of

different sensors might use some sensors as triggers for others

and only the secondary information is passed on to an

“outside” exploitation system. Depending on the sensor type

and the processing a proprietary data stream may be created

[10]. To observe land and sea borders it is necessary to make

use of different sensor types with differing ranges and tasks:

Long-Range border surveillance conducted by space borne

and airborne systems is of interest for an all-weather and 24

hour detection of threats that harm a wide area. The sensors

can deliver all kinds of imagery such as IR, electro optical and

synthetic aperture radar as well as motion imagery, signal

intelligence or radar data.

Airborne Sensors, including the use of balloons or zeppelins

can be used for medium-range border surveillance.

Ground-Based or seaborne sensors are mainly used for short-

range surveillance. Real time information can be provided on

critical areas, objects and people [5]. Seaborne sensors can be

installed above or under water. The display of sensor data in a

common picture only makes sense if the operator/analyst is

able to interpret that information correctly. Raw sensor data

have to be interpreted by specialists. Therefore sensor data are

only provided on system, local or at the most the regional

level.

III. METHODOLOGY

Problem Formulation

In implementation of network simulation there are various

problem arises in term of technical and social and these

challenges must be resolved before the deployment. Some of

the challenges are depicted below:

Network Management:

Security Issues

Congestion and collision Control

MAC Design

Data Consistency Liability

Reference work used learning automata approach to solve

coverage problem. It presented distributed border surveillance

(DBS) algorithm that aims to find the minimum possible

number of nodes in each barrier to monitor the network

borders [7]. In DBS approach, learning automaton assists to

find the best nodes to assure barrier coverage at any moment.

In this scheme, used binary sensing model for detect of nodes

probability.

Objective

The DBS algorithm has been implemented through WSNs

simulator. The performance results of the proposed solution

are compared to reference work. We analyzed the performance

with the following inputs:

Total number of nodes N

Sensing range of node Rs

Network height

Network width

It is worthy to state that we used a random deployment

scenario to scatter nodes in the network. It estimated the target

location, velocity and trajectory in a distributed and

asynchronous manner. The accuracy of the algorithm is

analytically derived under ideal binary sensing model and

extensive simulations of ideal, imperfect and faulty sensing

models show that the algorithm achieves good performance.

Log Shadowing Sensing Model

Log shadowing sensing model is implemented in this article

for maximizing number of barriers. In this implemented fading

model, receive power enhanced using gamma function. The

proposed algorithm will make use of a round-robin approach


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where end nodes are relaying a keep-alive message to other

end nodes, in order to minimize the number of messages

required to keep a continuously consistent view of safety-

critical nodes and links.

Figure 2 General Flowchart for deploying log shadowing

model

Figure 3 Monitoring Phase

Shadowing gives a path loss exponent factor to describe the

effect of micro environment, and a random factor to describe

the shadowing effect. The dependencies of all the factors

(obstacles such as building, foliage) have been taken into

account in this sensing model. Here, the sensing ability of a

node is not uniform in all the directions. This is similar to

shadowing in radio wave propagation. Assuming log-normal

shadowing path loss model, the probability that an event at a

distance x from the node will be detected is given by

𝑃𝐷 𝑦 = 𝑄 10𝑛𝑙𝑜𝑔 𝑦 𝑟𝑠

𝜕

Where n denotes path loss exponent (2 ⩽ 𝑛 ≤ 4), 𝑟𝑠 denotes

sensing radius without fading.

IV. RESULT AND DISCUSSION

SOFTWARE: It is powerful software that provides an

environment for numerical computation as well as graphical

display of outputs. In Matlab the data input is in the ASCII

format as well as binary format. It is high-performance

language for technical computing integrates computation,

visualization, and programming in a simple way where

problems and solutions are expressed in familiar mathematical

notation.

Table 1 Various Simulation Parameters used in NS2

Network Animator Simulation Result

Figure 4 NS 2 network animation file for deploying 10 sensor

nodes


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Figure 5 NS 2 network animation file showing packet loss in a

cluster of 10 nodes

Figure 6 Base and proposed work comparative analysis for

number of barriers with network height 20


network width 20 meter

Figure 8 Number of base barrier and number of proposed

barrier comparative analysis for diverse sensing range with

100 nodes


different network size and R=40 m


different network size


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V. CONCLUSION

Border surveillance is one of the high priorities in the security

of countries around the world. Border surveillance must be so

tight otherwise it leads to heinous crime. Border monitoring

systems are peculiar province of the intelligent technologies

by the implementation of WSNs. Traditional border

observations unable to provide complete surveillance at

borders. Therefore need intelligent system like various types

of advanced sensors, laser wall, smart fencing. In our

dissertation we implemented fully distributed approach using

log sensing shadowing model to enhance network overall

performance by locating BPs. We implemented an efficient

approach for maintaining the BPs in the network, which

updates their structure in a stochastic way. By implementing

log shadowing sensing model technique number of barriers

depicted the efficiency of proposed work better than exist one

for various parameters like network height, width, and range.

In order to implement WSN for border surveillance, it is

compulsory to have a secure WSN with appropriate protocols

because there are possibilities of diverse attacks in WSN.

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border surveillance in wireless sensor network system ... · border surveillance as it differs from...

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