Six Myths about Ontologies: The Basics of Formal Ontology
Ijess complimentary copy vol1issue3
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Sr. TITLE & NAME OF THE AUTHOR(S) Page
No. No.
1 MEASURING SOFTWARE QUALITY FACTORS USING CK METRICS 1
Rashmi Goyal, Sona Malhotra
2 INDIAN REAL ESTATE‐ A BOON TO THE ECONOMY 10
Dr. V. Santhi, Benon.S, Arun Kumar.J
3 WIRELESS SIGNAL STRENGTH ENHANCEMENT IN LOCAL AREA NETWORK (WLAN) 28
M. Umair Saleem, Tasleem Mustafa, Ahsan Raza Sattar, Dr. Muhammad Saleem, Dr. Shaukat Ali
4 SECURITY IN VEHICULAR AD‐HOC NETWORKS ‐ CHALLENGES AND COUNTER MEASURES 45
Ann Baby, .Dr.Sreekumar
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MEASURING SOFTWARE QUALITY FACTORS USING CK METRICS
Rashmi Goyal*
Sona Malhotra**
ABSTRACT
This paper gives an approach to evaluate software testability. The process of Software
Engineering evolves with a unique issue of testability. It is an external software attribute that
assesses the complexity and effort required for testing software. The insight provided by
testability is valuable during design, coding, testing and quality assurance. To capture
testability of classes, we used different metrics to measure its characteristics. Testability
Keywords: Software Testability, CK metrics, quality.
*CSE Deptt., University Institute of Engineering & Technology, Kurukshetra
** Assistant Professor, CSE Deptt., University Institute of Engineering & Technology,
Kurukshetra
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1. INTRODUCTION
Software engineering is a profession dedicated to analysis, designing, implementing and
modifying software so that we develop software of high quality and fast to build. Testing has
always been a broad concept to measure and evaluate software accurately. Software quality is the
attribute to measure the software characteristics. To measure software quality, a no. of software
metrics is used. Metric are the quantitative measure of the degree to which a system, component,
or process possesses a given attribute. Software metrics can be used to measure different
characteristics of a software system or software development process. Metrics for object oriented
development is a relatively new field of study. The metrics focus on internal object structures
that reflect the complexity of each individual entity, such as methods and classes, and on external
complexity that measures the interactions among entities, such as coupling and inheritance.
Chidamber and Kemerer’s metrics suite for object-oriented design is the deepest research in OO
metrics investigation. They have defined six metrics for OO design.
2. CK METRICS
Weighted methods per class (WMC):
It is the sum of the complexities of all methods of a class. According to this metric if a Class C,
has n methods and c1, c2 …cn be the complexity of the methods, then WMC(C)= c1 + c2 +… +
cn. Mc Cabe’s complexity metric is chosen for calculating the complexity values of the methods
of a class. The value is normalized so that nominal complexity for a method takes on a value of
1.0. If all method complexities are considered to be unity, then WMC = n i.e. the number of
methods existing in that class.
Depth of the inheritance tree (DIT):
Depth of inheritance of a class is “the maximum length from the node to the root of the tree".
More is the depth of the inheritance tree greater the reusability of the class corresponding to the
root of that tree as the class properties are shared by more derived classes under that class. So
there too much depth dilutes the abstraction. So there is a need to set the minimum & maximum
DIT value for a class as a contribution towards the reusability.
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The definition of DIT is ambiguous when multiple inheritance and multiple roots are present as
the alternative length of the path is not being considered in case of multiple inheritance. If we
add all the ancestor classes coming in common path to the ancestor classes coming in alternative
paths then that will be the true representation of the theoretical basis of the DIT metric.
Number of Children (NOC):
According to this metric Number of children (NOC) of a class is the number of immediate sub-
classes subordinated to a class in the class hierarchy. So greater is the value of NOC greater will
be the reusability of the parent class. Hence there should be some minimum value of NOC for a
parent class for its reusability. Theoretical basis of NOC metric relates to the notion of scope of
properties. It is a measure of how many sub-classes are going to inherit the methods of the parent
class. The definition of NOC metric gives the distorted view of the system as it counts only the
immediate sub-classes instead of all the descendants of the class. NOC value of a class, say class
i, should reflect all the subclasses that share the properties of that class.
NOC(i) =N+ΣiAll subclasses NOC(i)
Where N is the total number of immediate subclasses of class i.
Coupling between object classes (CBO):
Coupling between Object Classes (CBO) is a count of the number of other classes to which a
class is coupled. Excessive coupling is detrimental to modular design and prevents reuse. The
more independent a class is, the easier it is reuse in another application. The larger the number of
couples, the higher the sensitivity to changes in other parts of the design and therefore
maintenance is more difficult. Strong coupling complicates a system since a class is harder to
understand, change or correct by itself if it is interrelated with other classes.
Response for a class (RFC):
According to this metric “Coupling between Object Classes” (CBO) for a class is a count of the
number of other classes to which it is coupled. Theoretical basis of CBO relates to the notion that
an object is coupled to another object if one of them acts on the other, i.e. methods of one object
use methods or instance variables of another. Here we are restricting the unidirectional use of
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methods or instance variables of another object by the object of the class whose reusability is to
be measured. As Coupling between Object classes increases, reusability decreases and it becomes
harder to modify and test the software system. So there is the need to set some maximum value
of coupling level for its reusability. If the value of CBO for a class is beyond that maximum
value then the class is said to be non-reusable. It is the number of methods that can be triggered
by a message sent to an object.
Software Testability:
Software testability is affected by many different factors, including the required validity, the
process and tools used and the representation of the requirements. Voas et. al. [27] defines
software testability as the probability that a piece of software will fail on its next execution
during testing, provided it contains a fault. This fault sensitivity is obtained by multiplying the
probabilities that
(1) the location containing the fault is executed;
(2) the fault corrupts the program’s state; and
(3) the corrupted state gets propagated to the output.
High fault sensitivity indicates high testability and vice versa. The effort required to test a
program to ensure that it performs its intended function. Thus testability is also measured in form
of testability effort. The effect of values of CK metrics on testability is defined in the principles
below:
Principles for measuring Testability are:
1. LOC, the larger the size of a class, more effort is required to test a class.
2. WMC, more the methods in a class, more difficult it is to test the class.
3. DIT, greater is the inheritance tree, more testing effort is required.
4. NOC, more no. of children more will be the testing effort.
5. CA, increased complexity will increase testability of the software.
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Based upon these principles (1 – 5), equations for measuring testability are following:
Testability of a class = a*(LOC) + b*(WMC) + c*(DIT) +d*(NOC) +e*(CA)
where a, b, c, d, e are regression coefficients.
a =b =c = d =e = 1
Testability of OO program = sum (testability (class)i)
where i = 1 to n, n is number of classes.
3. COLLECTION OF METRIC DATA
To collect metric data, we have used Eclipse platform. Source code is given as input to the
Metrics tool. We analyzed software testability on metric.java and calculate ck metrics. Eclipse
Metrics tool is an open source tool which is available on internet.
Fig 1: Metric.java
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Fig 2: QualityFactorGenerator.java
4. METRIC VIEW:
To view metrics of source program, we have to enable metrics view from the menu list. It will
display the object oriented metrics for the code.
Fig 3:Metric view
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Metric Metric.java QualityFactorGenerator.java
NOC 0 0
CA 1 1
TLOC 108 40
LCOM 1 0
WMC 27 3
Table 1: CK metrics
120
metric.java
100
80
QualityFactorGener
60 ator.java
40
20
0
NOC CA TLOC LCOM WMC
Fig 4: Metric graph
These metrics are saved as a text file and given as input to the QualityFactorGenerator which
further calculates software testability.
Fig 5: Input File
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Fig 6: Software Testability
5. CONCLUSION:
The framework proposed in the paper will address testability during software development life
cycle. It may help putting testability benchmarking of software projects. The framework is
generic in nature, and may be used by industry practitioners to quantify testability in order to
make design decisions early in the development life cycle. In future, we have to emphasize on
more testability characteristics. We will introduce more software metrics too calculate testability
accurately.
6. REFERENCES:
[1]R. A. Khan, K. Mustafa, I Ahson, “An Empirical Validation of Object Oriented Design
Quality Metrics, Journal King Saud University, Computer & Information Science, Vol. 19, pp.
1-16, Riyadh (1427H/2007).
[2] Jungmayr, S. Testability Measurement and Software Dependencies. In Proceedings of the
12th International
Workshop on Software Measurement, pp. 179–202, October 2002.
[3]Bertolino, A., and Strigini, L., “On the Use of Testability Measures for Dependability
Assessment”, IEEE Transactions on Software Engineering, VOL. 22, NO. 2, February 1996.
[4] McCall, J. A., Richards, P. K., and Walters, G. F., “Factors in Software Quality”, Nat’l Tech.
Information Service, no. Vol. 1, 2 and 3, 1977.
[5]Booch, G., Object Oriented Design with Applications. Redwood City, CA: Benjamin/
Cummings, 1991.
[6]P. Coad and E. Yourdon, Object-Oriented Design. Englewood Cliffs, NJ: Prentice-Hall, 1991.
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[7]Magiel Bruntink, Arie van Deursen, “Predicting Class Testability using Object-Oriented
Metrics” Proceedings of the Fourth IEEE International Workshop on Source Code Analysis and
Manipulation (SCAM’04), pp 1-10, 2004
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INDIAN REAL ESTATE- A BOON TO THE ECONOMY
Dr. V. Santhi*
Benon.S**
Arun Kumar.J**
ABSTRACT
The prospects for real estate industry in India goes buoyant. All the factors that contributed to the
growth of real estate sector- high disposable incomes, sharp increase in global liquidity, selective
capital account liberalization, looser credit policies, a greater availability for the leverage due to
financial liberalization and the consequent increase in shortage lending and price increase.
*Asst.prof(S.G), Dept of Humanities, PSG College of technology, Coimbatore-641004
** III B.E (SW) EEE , PSG College of technology, Coimbatore-641004
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INTRODUCTION
Real estate sector in India is witnessing tremendous boom and is presently worth $12 billion and is
growing at the rate of 30 per cent per annum.It is the second largest employer next to
agriculture.India is fast evolving in the real estate market witnessing a growth in construction
activities both in residential as well as commercial and retail segments. It has observed that the real
estate action is no longer limited to the large metropolises of India but has now permeated to the
burgeoning smaller towns and cities. These emerging centers of growth are lending sparkle to India's
booming economy. It has emerged as the most profitable business venture to invest US $ 90 billion
by 2015 also witnessing huge FDI (Foreign Direct Investment), not only due to the 100 per cent
Government allowance with fast track approvals but also due to high potential investment returns of
more than 25-30 per cent. Eighty per cent share of the real estate market is garnered by residential
sector and the rest is comprised of offices, shopping malls, hotels and hospitals.One Rupee invested
in real estate sector results in 78 paise being added to the GDP of the country.With the urban
population of India is likely to grow from 285.3 million in 2001 to 360 million in 2010, 410 million
in 2015, 468 million in 2020 and 533 million in 2025 gives a huge potential simultaneously demand
for affordable residents which is considered as the basic need of human being of food, water and
shelter. The current size of real estate construction industry in India is estimated to be approximately
US$44 billion. The boom in retail industry has also spurred the growth in real estate sector. India at
the moment is witnessing a spurt in extremely large retail spaces.The industry is highly fragmented.
The top 10 players account for approximately 10 per cent of the total revenue of the industry, while a
major part is attributed to unorganized real estate contractors.The industry is expected to witness an
annual average growth rate of approximately 26 per cent till 2014. The main focus area of almost all
real estate companies is the ‘affordable housing,’ which controls more than 50 per cent of residential
sales in key residential areas such as Chennai, Gurgaon and Mumbai.The prevailing stature of the real
estate market in India and it growth statistics motivated us to carry this introspective study. Real
estate construction industry is also getting benefited from government initiatives. The Government of
India, in order to attract foreign direct investment in the industry, is working out on easier rules for
overseas investors to invest in smaller real estate projects.
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NEED FOR THE STUDY
Low interest rates, modern attitudes to home ownership (the average age of a new homeowner is now
32 years compared with 45 years a decade ago), economic prosperity along with a change of attitude
amongst the young working population from that of ‘save and buy’ to ‘buy and repay’ and liberalized
FDI regime have all contributed to sector in this boom. The above stated definition has created a need
for framing the below mentioned objective of the study to analyse the consumers preference for
towards the modern town ship development, their simultaneous perception and motivating factors at
micro level.
OBJECTIVES OF THE STUDY
To analyze the level of perception of consumers towards the Township Project.
To state the factors influencing the purchase of Villas in Township project.
To offer suggestion for Taamaesek Engineering Consortium India and S.P.Apparels in
promoting the Township.
SCOPE FOR THE STUDY
This study provides scope to review the pattern of consumer’s attitude towards the modern township
development proposal at Tirupur and Coimbatore Districts and also draw an introspective view of the
property promoters’ perception about the same. Thus it supposed that the current study to
demonstrate functional issues of real estate business development to research scholars, academician,
economic planners and the marketers as a whole.
INTRODUCTION TO THE COMPANY
The current study is based on the real-time project proposal joint-venture signed between the
Taamaesek Engineering Consortium India and SP Apparels to develop a modern town-ship.
Taamaesek Engineering Consortium India established in the year 2000,having worked on many
prestigious projects in Singapore, viz Fullerton Hotels, Ritz Carlton, Hazel Park & Flora Vale
condominiums, Millennia towers & Centennial towers etc., is ably assisted by a core team of 20
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engineers with various levels of International work execution and project management expertise and
100 engineering professionals from all streams of engineering contributing to a value engineered
design. Drawing on the multi - disciplinary expertise, generates a value engineered design to create
maximum value and enhance quality of life is the MISSION and VISION of the organization.
Taamaesek Engineering Consortium India’s total involvement and comprehensive value engineering,
in every project cutting across all services such as civil, structure, trades, electrical, air conditioning,
plumbing, fire detection and suppression, networking, water treatment, interiors. The Major
competitors for the concern are; JLL, CBRE and CUSMAN.
SPAL, well known Knitwear Garment manufacturer is in the business for nearly two decades. SPAL
is one of the largest Knitwear Exporter in India and is ranked second among 5000 Exporters in
Knitwear town of Tirupur, South India. SPAL is focused on producing extensive range of Knit
Garments viz. Kids wear – 50per cent, Ladies Garments -35per cent & Men’s wear-15per cent. SPAL
is catering to major global brands and chain stores. The unit has set up globally acceptable standards
and quality norms. With this expertise gained in the manufacturing,SPAL plans to build domestic
brand in order cash in vibrant and expending domestic garment market. SPAL holds 70 per cent
equity stake in Crocodile Products Private Limited in. The Joint Venture Partner being Crocodile
International Private Limited, Singapore. Further it is proposed to commence more stores all over the
country. The Company has vertically integrated manufacturing set up starting from Spinning,
Knitting, Processing (Dyeing), Printing & Embroidery, Sewing Facility and Retail in domestic
market.To be the best clothing supplier in the world aggressively work into US, & other EU
Countries and increase the customer base by 25 per cent a year, to grow into a 2000 cr. Company by
2015 and to create a retail presence pan India within one year is the MISSION and VISION of the
organization.
RESEARCH METHODOLOGY
Real estate property development joint venture named “OPULENCE” has been signed between
Taamaesek Engineering Consortium India and SP apparels to build a modern town ship. A marketing
research has been conducted on their request to know the feasibility of developing a town ship
connected directly by the NH 49 National High Way Road Line. The data was collected through a
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well structured interview schedule. The chi-square test is an important test amongst the several tests
of significance.It is a statistical measure used in the context of sampling analysis for comparing a
variable to a theoretical variance. As a non-parametric test, it can be used to determine if categorical
data shows dependency or the two classifications are independent. The entire hypothesis test in this
study was carried out at 5 per cent level of significance.An attempt was made to analyze the main
factors influencing the level of buyer preference with the evident of the selected sample respondents
in the study area. For the purpose of the detailed analysis, variable are classified in two important
strata which are termed as dependent variables and independent variables. The buyer preference
interms of opinion towards likeliness, opinion towards uniqueness and opinion towards willingness
by the sample respondent was taken as dependent variables and the independent variables used in
this study are age, location, annual family income. The instrument used in collecting the primary data
was Structured Questionnaire. The questionnaire consisted of both closed and open ended questions.
The sample size taken for my study is about 200 respondents. Area sampling was done. If cluster
happen to be some geographic subdivisions, cluster sampling is better known as area sampling. In
other words, cluster designs, where the primary sampling unit represents a cluster of unit based on
geographic area, are distinguished as area samplings. The frequency distribution of the variables were
calculated with help of simple percentage, by writing the formula FD = F/N x 100. Where F denotes
the number of respondents, and N denotes the total number of sample population.
(O E ) 2
Chi–square test ( ) = 2
E
Degrees of freedom = (R-1) (C-1)
Where O = observed frequency
E = expected frequency
R = number of rows
C = number of columns
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The 2 values obtained as such should be compared with relevant table value of 2 and the inference
can be drawn. If the calculated value is greater than the table value the hypothesis framed will be
rejected, otherwise accepted.
TABLE-I
FACTORS INFLUENCING THE BUYERS DECISION
TOTAL
S.NO FACTORS RANK
SCORE
1. Price 1640 1
2. Location 1404 2
Transport, Shops and Public
3. 1040 3
Amenities
4. Facilities & Amenities 798 4
Brand Image of builder / property
5. 530 6
developer
6. Landscape Area (Sq.Ft) 48 10
7. License of the Builder 368 7
8 Registration & Documents 240 8
9. Loans & EMI 660 5
10. Security of the Property 112 9
Source-primary data
It is found from the analysis that most of the respondents are influenced by competitive price, locality
and transport, shops and public amenities.
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FIGURE-I
AGE AND FACTOR SCORE
FIGURE-II
AGE AND FACTOR RANKING
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FIGURE-III
GENDER AND FACTOR SCORE
FIGURE-IV
GENDER AND FACTOR RANKING
FIGURE-V
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ANNUAL INCOME AND FACTOR PRICE
FIGURE-VI
ANNUAL INCOME AND FACTOR RANKING
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FACTORS INFLUENCING TO BUY TOWNSHIP
The following variables have been selected to the level of likeliness; uniqueness and willingness to
purchase the property are Age, Location, Annual family income and Profession.
TABLE-II
AGE AND OPINION ABOUT WILLINGNESS TO BUY A TOWNSHIP
Opinion towards willingness
Age Might
Probably Definitely Total
Definitely Probably or
(in yrs) would not would not
would buy would buy might
buy buy
not buy
16 6 4 0 10
20 – 30 36
(44.4) (16.7) (11.1) (0) (27.8)
16 22 20 4 4
30 – 40 66
(24.2) (33.3) (30.3) (6.1) (6.1)
8 32 8 4 14
40 – 50 66
(12.1) (48.5) (12.1) (6.1) (21.2)
4 16 4 0 8
Above 50 32
(12.5) (50) (12.5) (0) (25)
Total 44 76 36 8 36 200
SOURCE-PRIMARY DATA
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TABLE-III
CHI-SQUARE TEST
Calculated 2 Table
Factor D.F Result
Value Value
Age 28.750 21.026 12 Rejected
The above table shows that the calculated chi-square value (28.750) is greater than the table value
(21.026). So, the null hypothesis is rejected. Hence, there is a close significant relationship between
age and opinion about willingness to buy a township.
TABLE-IV
ANNUAL FAMILY INCOME AND OPINION ABOUT WILLINGNESS TO BUY A
TOWNSHIP
Opinion towards willingness
Annual Family Total
Income Might or Probably Definitely Score
Definitely Probably
Might not not not
Less than 2 2 0 2 2
8
2,00,000 (25) (25) (0) (25) (25)
2,00,001 – 2 0 4 2 2
10
4, 00, 000 (20) (0) (40) (20) (20)
4,00,001 – 4 16 2 0 0
22
6,00,000 (18.2) (72.7) (9.1) (0) (0)
6,00,001 – 10 18 8 0 0 36
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8,00,000 (27.8) (50) (22.2) (0) (0)
8,00,001 – 10 16 6 2 10
44
10,00,000 (22.7) (36.4) (13.6) (4.6) (22.7)
16 24 16 2 22
Above 10,00,000 80
(20) (30) (20) (2.5) (27.5)
Total 44 76 36 8 36 200
SOURCE-PRIMARY DATA
TABLE-V
CHI-SQUARE TEST
Calculated 2 Table
Factor D.F Result
Value Value
Annual
family 54.138 31.410 20 Rejected
income
The above table shows that the calculated chi-square value (54.138) is greater than the table value
(31.410). So, the null hypothesis is rejected. Hence, there is a close significant relationship between
annual family income and opinion about willingness to buy a township.
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TABLE-VI
LOCATION AND OPINION ABOUT WILLINGNESS TO BUY A TOWNSHIP
Opinion towards willingness
Location Might or Probably Definitely Total
Definitely Probably
Might not not not
12 46 12 6 24
Coimbatore 100
(12) (46) (12) (6) (24)
32 30 24 2 12
Tirupur 100
(32) (30) (24) (2) (12)
Total 44 76 36 8 36 200
SOURCE-PRIMARY DATA
TABLE-VII
CHI-SQUARE TEST
Calculated 2 Table
Factor D.F Result
Value Value
Location 13.368 9.488 4 Rejected
The above table shows that the calculated chi-square value (13.368) is greater than the table value
(9.488). So, the null hypothesis is rejected. Hence, there is a close significant relationship between
location and opinion about willingness to buy township
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TABLE-VIII
PROFESSION AND OPINION ABOUT WILLINGNESS
TO BUY A TOWNSHIP
Opinion towards willingness
Profession Might or Probably Definitely Total
Definitely Probably
Might not not not
Business / 18 32 16 2 12
80
Industrialist (22.5) (40) (20) (2.5) (15)
16 24 8 2 10
Self Employee 60
(26.67) (40) (13.33) (3.33) (16.67)
10 20 12 4 14
Employee 60
(16.67) (33.33) (20) (6.67) (23.33)
Total 44 76 36 8 36 200
SOURCE-PRIMARY DATA
TABLE-IX
CHI-SQUARE TEST
Calculated 2 Table
Factor D.F Result
Value Value
Profession 5.898 15.507 8 Accepted
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The above table shows that the calculated chi-square value (5.898) is less than the table value
(15.507). So, the null hypothesis is accepted. Hence, there is no significant relationship between
profession and opinion about willingness to buy a township.
TABLE-X
PROFESSION AND OPINION ABOUT WILLINGNESS
TO BUY A TOWNSHIP
Opinion towards willingness
Profession Might or Probably Definitely Total
Definitely Probably
Might not not not
Business / 18 32 16 2 12
80
Industrialist (22.5) (40) (20) (2.5) (15)
16 24 8 2 10
Self Employee 60
(26.67) (40) (13.33) (3.33) (16.67)
10 20 12 4 14
Employee 60
(16.67) (33.33) (20) (6.67) (23.33)
Total 44 76 36 8 36 200
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TABLE-XI
CHI-SQUARE TEST
Calculated 2 Table
Factor D.F Result
Value Value
Profession 5.898 15.507 8 Accepted
The above table shows that the calculated chi-square value (5.898) is less than the table value
(15.507). So, the null hypothesis is accepted. Hence, there is no significant relationship between
profession and opinion about willingness to buy a township.
FINDINGS
Price got the first rank in all categories of gender and landscape area got the tenth rank in all
categories of gender.
It brings from the analysis that majority of the respondents are very much interested to buy a
township.
Most of the respondents are influenced to buy a township by its competitive price, locality and
transport, shops and public amenities.
While in the case of Annual family income level, the respondents who earn eight lakhs to ten
lakhs opined that they are willing to purchase township. The result of chi-squared test
accepted the result at 5 per cent level of significance.
It is clear from the analysis that the respondents who are businessman and self employees are
opined that they probably would buy the township than the other group of the respondents.
RECOMMENDATION
The current study aims on the consumer’s attitude on purchase of opulence township, so as to take
informed business decisions (which would form as inputs to go ahead with the proposed township)
and through this process of study it has been found that India’s real estate market is poised for
tremendous growth potential with a wave of development and investment into these “exciting”
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assets. It is recommended that the “Opulence” has been well received by the industry stakeholders
company and they can go forward with the project. Opulence can be further added to the project
proposal green property with infrastructure, keeping tradition & technology under one roof .It is also
recommended that the concern can added amenities which can provide Yoga / meditation centers,
Gym, Clinics, Crèche, ATMs etc., Developers can look at Coimbatore - Tirupur belt for the further
business promotions.The price tag should be moderately range between 30 – 40 lakhs to attract all
categories of potential buyers.
CONCLUSION
It was observed that the main factor affecting the real estate business in Coimbatore and Tirupur
districts is due to the increased in land prices, followed by government policies / lack of infrastructure
and lastly by fluctuation in interest rate in home loans.India is emerging as one of the places to live
in with tranquility and a better social life. India now is not only a place to find greenery and an
enriched culture but also it is the place to find various opportunities in terms of jobs and money. Due
to growth in income class there has been an unprecedented rise in the real estate business in India.
. Real Estate Agents are good option as well, for those service class people who hardly have enough
time to search for place to put up their effects. There is a discernible hunger for knowledge and
interaction as developers and investors begin to penetrate the Indian real estate market. The
Opulence’s key success lies in the provision of pollution free environment, hassle free traffic,
optimum utilization of the scope of upcoming projects proposed area, existing educational
establishments (for multiplex/malls) and location proximity etc.,
References:
Books-
1. C.R.Kothari- Research methodology and techniques, second edition, new age international (p)
Limited publications, Reprinted, 2005.
2. O.R. Krishnaswamy and M.Ranganatham- Methodology of Research in social science;
Himalaya Publishing House; reprint 2006.
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28. IJESS Volume1Issue3 ISSN: 2249‐ 9482
3. Philip Kotler, “Marketing Management”, prentice hall of India private Ltd., New Delhi, 2000.
4. Pillai,R.S.N and Bagavathi, “Modern Marketing”, S.Chand and Company Ltd., 2004
Journals and Magazines-
1. Rands Joseph, Real Estate Development in India; Published 10/07/2006
2. Samuel Zell, Real estate industry- The true barometer for a country’s economy; Keynote
Address, Chairman Equity Group Investments, USA in a International Symposium; a Global
Platform where Developers & Investors Gather to Discuss Emerging Opportunities in India
Real Estate Market; 23-25 April 2007, Renaissance Mumbai Hotel & Convention Centre,
Mumbai, India.
3. Jones Lang LaSalle Meghraj (2007); Emerging Trends and Adoption of Sustainable practices
in India; New Delhi, 25 November.
Web Sites-
1. http://www.buzzle.com/articles/real-estate-developements-india.html
2. Mizra Sajid; Properties in south India; Article sphere; May 2007. :
http://www.articlesphere.com/Article /Properties-in-south-India/156562.
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WIRELESS SIGNAL STRENGTH ENHANCEMENT IN LOCAL AREA
NETWORK (WLAN)
M. Umair Saleem*
Tasleem Mustafa**
Ahsan Raza Sattar***
Dr. Muhammad Saleem****
Dr. Shaukat Ali*****
ABSTRACT
With the improvement in IEEE 802.11 standards, wireless networks are increasing in number.
With the advancement of technology, the data rates and coverage of Wi-Fi and usage for
different high bandwidth increases. The major problem in the Wireless Local Area network
(WLAN) is its coverage. In this research, different techniques were implemented to increase the
signal strength of wireless network (WLAN). Various forms of antennas (circular, parabolic etc.)
with different types of material (aluminum, steel and iron etc) were prepared locally. These
devices were used to increase the signal strength of WLAN in a minimum cost. These equipments
were attached with the AP (Access point) to enhance its efficiency and signal strength.
Furthermore comparative study among these devices with AP and existing devices were carried
out to evaluate the performance of above mentioned antennas.
*Computer Network Engineer, MIT College of Commerce and Computer, Faisalabad, Pakistan.
** Chairman, Department of Computer Science, University of Agriculture Faisalabad, Pakistan.
*** Lecturer, Department of Computer Science, University of Agriculture Faisalabad, Pakistan
**** Senior Research officer, Dept. of water management, University of agriculture Faisalabad,
Pakistan.
***** Assistant Professor, University of Agriculture Faisalabad, Pakistan
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INTRODUCTION
In the present, the industry is grown towards portability of network. Most of the phone
companies and signal based network companies launch wireless network facilities instead of
wired network. This mobility supports efficiency as well as service opportunities not achievable
with wired networks.
NEED FOR RESEARCH
In wireless network, the communication of network is based on signals. If everything is alright
then the user (who is wirelessly connected with the network) is using network by sitting at a far
distance, he must has a network coverage problem. But how the network increases its signals and
covers a long distance in a minimum cost. When the signal drops then the speed of the network
access will automatically decrease. Hence the signal must be strong and covers long distance
with networks original speed. The major problem in the Wireless Local Area Network (WLAN)
is its coverage. But it is possible to increase signals with the use different types of antennas. But
these are much costly antenna devices. Small CPW-fed T-shaped antenna for MIMO application
was presented to gain signal strength of wireless network. The size of the antenna was only 35%
of conventional CPW-fed T-shaped antenna, which had been satisfied return loss bandwidth and
Omni-directional radiation characteristics. Wi-Fi Access Points are being configured in most of
the possible areas like public parks, hotels, banks and universities.
ANTENNA CHARACTERISTICS
The D-Link Extreme Antenna was a multipurpose antenna designed to help get better
performance of wireless signals. It was an Omni-directional antenna (360o coverage) with the
range of 200 meters shown in figure (1). The dimensions of this antenna was (2.9” x 4.2” x 5.3”).
Operating Temperature of the antenna was (-3°F to 150°F (-21°C to 66°C)) and Storage
Temperature was (-21°F to 170°F (-29°C to 80°C)) it was so much expensive antenna as
compared to signal strength. The market price of this antenna was 180$.
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Figure (1): D-Link Extreme N™ 2.4GHz Antenna
WIRELESS SIGNAL RADIATION OF D-LINK EXTREME ANTENNA IN
AIR:
The above antenna spreads the wireless signals in a circular form shown in figure (2). It radiates
the signals up and down like a jumping ball.
Figure (2): Wireless signal radiation of D-Link Extreme antenna
MATERIAL USED TO BUILD D-LINK EXTREME ANTENNA:
The first step in building of wireless antenna is the collection of the material required for
building. The essential materials for the wireless antenna are as follows.
1. Low resistance aluminum wire
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2. Special plastic for coating
3. Special nut to connect with Access Point
4. Aluminum connectors
5. Ninety degree straight building of antenna
6. Fine soldering
7. Low resistance Copper wire
In this research, different techniques and types of antennas were judged-in for the investigation
to increase the signal strength and spread signals of wireless network. Various forms of antennas
(Omni-directional) with different types of material (aluminum, steel iron etc) were prepared
indigenously.
These devices were used to increase the signal strength of WLAN in a minimum cost. The total
cost of these type of antennas was approximately 3$ to 5$. These equipments were attached with
the AP (Access point) built in antenna to enhance its efficiency. The range of these antennas was
approximately above 1000 meters (1km) in outdoor use. Furthermore comparative study among
these devices with AP and existing devices was carried out to evaluate the performance of above
mentioned antennas.
PROBLEM STATEMENT:
In a wireless based network, signal range is a big problem. A user who wants to connect with a
wireless network from a far distance must have a signal problem. When the signal drops then the
speed of the network access will automatically decrease. The user cannot make a reliable
connection with the network. A 5-dbi Access Point antenna has no enough signal strength. The
maximum outdoor range of that antenna was 100 meter. In this research, we investigated new
home made antenna to increase signal strength of Wireless Network.
PROPOSED SOLUTION:
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A new home made wireless antenna was investigated to increase signal strength. This antenna
was used to increase signals up-to 1000 meters and also in a minimum cost. Following are the
specification of homemade antenna.
Wireless signal radiation of homemade wifi antenna in air:
The following figure (3) shows that the signal spread in the air horizontally. The signal strength
level was not same in all the directions. It depends on the environment and other factors i.e.
building, furniture and trees etc. It spreads signals at least 1 km.
a. Horizontal View
Figure (3): Wireless signal radiation of homemade wifi antenna
b. Vertical View
The following figure (4) shows, how the signal spread in the air. The vertically view of signals
shows that the signals are spreading like a fountain. The signal strength level is not same in all
the sides. Middle lobe is approximately 300 meter up in the air and side lobes covers 1000 meter
approximately in left and right. The signal strength depends on the environment and some other
factors i.e. building, furniture and trees etc. But with all these factors this antenna spreads signals
at least 1 kilo meter.
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Figure (4): Wireless signal radiation of homemade wifi antenna
Material to build Homemade antenna.
The first step in building the wireless home antenna is the collection of the material required for
building. The essential materials for the homemade wireless antenna are as follows
1. Local packing aluminum foil
2. Local Copper wire
3. Aluminum wire
4. Nuts and Bolts
ADVANTAGES
RANGE as compared to other antennas:
The range of any antenna depends on the material of antenna and also the environment in which
that antenna is used. This antenna was made up of a local material like aluminum, iron and steel.
The range of this antenna was more than 1000 meters (1 km).
The user can connect with the network easily while he will away from the access point up to
1000 meter. The efficiency of this antenna is very high than the other wireless antennas.
OUTDOOR Adjustment:
The antenna should be placed outdoor approximately 20 feet high from the ground.
Material used
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A local material was used to build homemade antenna. A simple rough aluminum and plane steel
was required to build this antenna.
PRICE compared to the other antennas:
The price will depended on the material which is used to manufacturing of antenna. This
research also concluded that these antennas were made up of a local aluminum and iron material.
The Total cost to build this antenna was approximately 3$-5$. It was most reasonable price
antenna.
Research Methodology
The major problem of WLAN network is the network coverage range. When the signal drops
then the speed of the network access will automatically decrease. The requirements, was to
increase the network signal strength also in a minimum cost. In this research, we were
investigated new techniques to increase signal strength of WLAN. Various forms of antennas
with different types of materials i.e Aluminum and iron etc was prepared locally. These devices
were used to increase the signal strength of WLAN and in a minimum cost. These antennas were
attached with the AP (Access point) antenna to enhance its efficiency. The signals which were
emits from the AP were reflected by these antennas and travels a long distance as compared to
the AP.
Materials and Methods
Wireless Networks are spreading day by day due to their reliability, ease and low cost. The speed
and the reliability of communication of communicating devices is depends on wireless signal.
These signals must be strong, powerful and covered long distance as possible in a minimum cost.
These are strong if the user is using network in its coverage range. The aim of this research was
investigated that how to improve the signal strength of Wireless Local Area Network (WLAN)
and new ways of improving existing standards in terms of distance covered and data rates.
There are lot of software available in the market to measure the strength once the access point
has been installed (Net Stumbler, 2007) or to even plot-out maps of signal strength (Air Magnet,
2007); however to gain this information in proceed of the installation requires a degree of
calculation. This is particularly important in business environments, where it is necessary to
know that network connection cannot be made to the network from outside the building.
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Figure 5: Wireless signals in building
Some security point of views was also a big question that It is necessary to guarantee that the
user cannot be connect to the network if he wants to connect to the network from outside of the
building. If his device full strength signals then he can easily connected to the network. Figure 5
shows an example of the results of a survey, which is color-coded to aid the explanation of the
information.
Increasing Signal Strength with Homemade Antenna
A homemade antenna was attached with the Access point to increase its efficiency. When the
user was out of range from the access point range, low speed of 5.5 Mbps shown in Figure (6). It
cannot connect a reliable connection, and have no access of network with the proper speed.
Figure 6: Wireless network out of range
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A homemade antenna was attached with the Access point, that antenna was gain the signal
strength up to double of signals original coverage of access point. A user who was received 5.5
Mbps signals with original antenna of AP, was received 54 Mbps speed with the home made
local antenna shown in the figure (7).
Watch out the speed: 5.5 Mbps
Watch out the signal strength level: 3 of 5 lights are glowed.
Signal quality was also very low. Hence the sent and receive capability would also be
decrease due to low signals.
Figure (7): Wireless network increase high range
Signal Measurement Calculator:
PdBm = Log Pmw x 10
1 Watt = 1x 1000 mW
PdBm = Log 1000 x 10 = 30 dBm
100 mW; P dBm = Log 100 x 10 = 20 dBm
For link budget calculations, the dBm convention is more convenient than the Watts convention.
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Signal Attenuation
Attenuation (fading) of an RF signal is defined as follows:
Pin : power level input at the attenuator input
Pout: power level output at the attenuator output
Attenuation is expressed in dB as follows: PdB = 10 x Log (Pout / Pin)
i.e., If, due to attenuation, 1/2 power is lost (Pout/Pin = 2),
Attenuation in dB is 10 x Log (2) = 3dB
Path Loss
Path loss is the loss of power of an RF signal travelling (propagating) through space. It is
expressed in dB. Path loss depends on:
Antenna height is a great factor of path loss.
Line of sight clearance between the receiving and transmitting antennas.
The distance between receiving and transmitting antennas.
Loss of Free Space
Attenuation of the electromagnetic wave while propagating through space. This attenuation is
Calculated using the following formula:
Loss of Free space = 20 * Log R (Km) + 20 * Log F (MHz) + 32.4
F = RF frequency expressed in MHz.
R = distance b/t the receiving and transmitting antennas.
At 2.4 Ghz, this formula is: 20 * Log R (Km) + 100
THE EXPERIMENTS
In total, three experiments were performed. The following are the experiments.
Experiment 1st Sniffing for sources of the interference
While performing all experiments, other 802.11 wireless equipments can potentially affect any
results obtained. Thus, the aim of the experiment had been identified, ' II" I I other potential
802.11 causes of the interference using a wireless sniffer. A wireless sniffer was a program that
has ability to capture and report to the user all traffic in the form of the packets (including beacon
frames) that traverses in free space. Wireless on had been a tool that allows users to monitor the
status of the wireless adapter(s) and gather information about nearby wireless access points in
real-time, it can help users to:
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The measure of the network throughput and view available data rates
Verifying the their network configuration had been correct
Experiment 2nd: The Time Variance
The correct variance over the time of the signal power and Packet mistake Rate had been
unknown. This testing aims to settle on if the signal power and ultimately the error rates alter
considerably over time. We had been chosen any measurement point relatively close to the AP
(ensure packets will be conventional by the wireless swarm) and run the program for as long as
possible.
Experiment 3rd: Signal propagation
The main aim of this experiment had been to determine the signal strength and the amount of the
loss throughout in the area. All of this area had been measured in which experiment had to be
conducted. The plan captured the emit packets from the AP side and record data to the TXT and
database files.
Uploading the data
Once the experiments had been completed during allocated slot, the collected data from all above
three experiments has been then uploaded using a wired connection to a desktop system. The
files that are uploaded include
Text files
Wireless Mon files
Signal strength files
Data Analysis
The statistically software had been needed to that analyzed the experimental results of the
experiment and proceeded to collate the recorded data within the text and database files into
meaningful and compact information set. The program outputs of this information on a single
line along with the particular area. The information set had been present in the database a file
determines. The round trip time i.e. time in which packet send and received had been to the
system at a particular distance and at a particular packet size, the average signal strength had
been the total number of the packets collected and finally the number of the packets was missed.
REUSLTS AND DISCUSSION
It was studied the motivation by the need for fundamental understanding of ultimate limits of
bandwidth efficient delivery of higher bitrates in digital wireless communications and to also
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begin to look into how these limits might be approached. He examined that exploitation of multi
element array (MEA) technology that was processing the spatial dimension (not just the time
dimension) to improve wireless signal strength and capacities in certain applications.
Measuring and Performance signal strength:
Access point was sending Normal signals, and Pc was received average signals before
implemented homemade (Locally) metallic material antenna behind Access point shown in the
figure 18.
Figure (8) signal strength
Access point was sending High signals and Pc receives high signals after implementing
homemade (Locally) antenna behind Access point shown in the figure 8.
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Figure (9): Boost signal strength
Analysis of reason of Signal loss
The requirements, is to increase the network signal strength also in a minimum cost. In this
research, we were investigated new techniques to increase signal strength of WLAN. Various
forms of antennas with different types of materials i.e. Aluminum and iron etc was prepared
locally. These devices were used to increase the signal strength of WLAN in a minimum cost.
These antennas were attached with the AP (Access point) antenna to enhance its efficiency. The
signals which were emitting from the AP were reflected by these antennas and travel a long
distance as compared to the AP.
Distance Vs Mean
200
180
160
140
Distance
120
100 Mean
80
60
40
20
0
0 50 100 150 200 250
Mean
Figure 10: Distance Vs Mean RTT
The above figure 10 shows that the distance VS mean. The distance increase and distance
decrease was affected negatively on the network. The distance of 90 feet and 110 feet was
significant effect. The distance of 170 feet has the mean of 140
Byte Vs Mean RTT
160
140
120
100
Mean
80 Mean
60
40
20
0
0 10000 20000 30000 40000 50000 60000 70000
Byte
Figure 11: Byte Vs Mean RTT
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The above figure 11 shows that the bytes vs. mean RTT. 5000 bytes have the mean of 16.95,
15000 have the mean of 41.62, 25000 have the mean of 65.45, 35000 have the mean of 74.616,
45000 have the mean of 92.977, 55000 have the mean of 120.598, 65000 have the mean of
139.697.
Effect of walls vs. Packet Loss
The above table shows the %age packet loss which shows that as we increase the number of
walls packet loss increases but there is another consideration that if the size of packet is small
there is almost no loss in case of six walls even so we conclude that if the packet size is small the
loss will be almost nil and if we want to communicate from such a location we must maneuver
packet size.
Effect of number of floors vs. RTT
We conducted experiment in university administration block to check the effect of %age packet
loss and increase in RTT in multi-Floor building. We designed a scenario in which first we
placed AP at 3rd Floor and PC on second, first and ground respectively. Than we place AP on
2nd floor and PC on first and first and ground Floor, the last part of the experiment was to place
AP at 1st floor and PC at ground floor. The analysis of variance table is below:
SUMMARY
Main aim of my research had been to look in the current technologies influencing the market like
“wireless local area networks” due to the cheap cost and efficiency, how were the Access Point
sends the signals, how were the antenna boost the signals. In wireless network, the
communication of network is based on signals. If everything is alright then the user (who is
wirelessly connected with the network) is using network by sitting at a far distance, he must has
a network coverage problem. But how the network increases its signals and covers a long
distance in a minimum cost. When the signal drops then the speed of the network access will
automatically decrease. Hence the signal must be strong and covers long distance with networks
original speed. The major problem in the Wireless Local Area Network (WLAN) is its coverage.
But it is possible to increase signals with the use different types of antennas. But these are much
costly antenna devices.
In this research, we have been investigated new techniques to increase signal strength of WLAN.
Various forms of antennas with different types of materials i.e. Aluminum and iron etc have been
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43. IJESS Volume1Issue3 ISSN: 2249‐ 9482
prepared locally. These devices were used to increase the signal strength of WLAN in a
minimum cost. This antenna was attached with the AP (Access point) antenna to enhance its
efficiency. The signals which were emitted from the AP will amplified with these antennas and
travel a long distance as compared to the original signals of AP. Furthermore comparative study
among these devices with AP and existing devices will be carried out to evaluate the
performance of above mentioned antennas.
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SECURITY IN VEHICULAR AD-HOC NETWORKS - CHALLENGES
AND COUNTERMEASURES
Ann Baby*
.Dr.Sreekumar**
ABSTRACT
Vehicular Ad-hoc Networks (VANETS) are a kind of MANETs (Mobile Ad Hoc Networks) which
operate without any predefined infrastructure. Vehicular Networks are conceived from the
Intelligent Transportation Systems. Ad hoc (or self-organizing) networks operate without
predefined infrastructure. In VANETs, vehicles equipped with Wi-Fi hardware constitute the
mobile nodes (hosts). VANETs help in inter vehicular and intra vehicular communication. The
most challenging issue in VANETs is the security aspect. This paper is an effort in discussing the
security aspects in VANETs, the challenges, requirements and a possible solution to overcome e
the security aspects in VANETs.
Keywords: VANETs, V2V, V2I, RSU, DCF, PCF, Vehicular Public Key Infrastructure, Digital
Signatures.
*
Computer Science Department, Rajagiri College of Social Sciences, Kalamassery, Kerala
**
Computer Science Departments, Cochin University of Science and Technology, Cochin, Kerala.
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1. INTRODUCTION
The innovations and improvement in the networking technologies has resulted in the
development of VANETs. VANETS (Vehicular Ad Hoc Networks) is a special kind of
MANETs (Mobile Ad Hoc Networks)) which aids in Vehicular Communication. Vehicular
Communication offers safer roads, efficient driving and easier maintenance. VANETs help in
saving time and money. The IEEE 802.11 Wireless standards are of high acceptance in today’s
academic and commercial standards. Driving cars includes two aspects: the first one being driver
assistance and car safety and the second one is infotainment for the travelers in the car (1). The
exchange of data and information between vehicles helps in the process of transferring real
time data. It also helps in communication about the road traffic and environment conditions.
VANETS also finds its applications in determining free parking slots and online help for car
maintenance. Research is also in progress for inter-vehicle communication. The field of inter-
vehicular communications (IVC), including both vehicle-to-vehicle communications (V2V) and
vehicle-to roadside communications (V2R), also known as VANET, is recognized as an
important component of ITS (Intelligent Transport Systems) in various national plans.(2) Traffic
fatalities are the leading causes of death in many countries. (3)This paper discusses the IEEE
802.11 standards for VANETS, the security problems that occurs in VANETs and the
countermeasures to overcome them.
2. VANET BASICS
Vehicular ad hoc networks are also known under a number of different terms such as inter
vehicle communication (IVC), Dedicated Short Range Communication (DSRC) or WAVE.(3) A
MANET is a self forming network which can function without the help of a centralized control.
Each node in this type of an ad-hoc network can act as both a terminal to store data and also as a
router. The nodes communicate through wireless medium in their specific radio range. VANETs
are a type of MANETs. As installing IEEE802.11 access points in all roads is expensive, it is
beneficial to go for an ad-hoc network. It also helps in quicker deployment. The greatest
challenge in creating a VANET is the rapidly changing network topology. The approximate time
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period in which two vehicles are in the same communication range is approximately one minute,
which is a greatest challenge for implementing VANETS. The error-rate in wireless networks is
also comparatively higher. Another challenge is the limited ad-hoc mode provided by the
IEEE802.11 protocols.
3. WORKING OF VANETS
VANETS can be of V2V or V2R (also known as V2I- Vehicle-to-infrastructure) approaches. In a
V2V approach which requires zero infrastructures to outside devices is purely ad-hoc. In this
approach, vehicles communicate with each other to determine the traffic situation. The number
of vehicles needed to use the system to get quality information need to be determined. In the
second approach which employs both V2V and V2R requires roadside devices or units (RSUs)
as outside infrastructure. RSUs are usually placed in the traffic lights, road dividers etc. Using
this technology, vehicles can communicate with RSUs (also known as OBUs-On-Board Units)
and with other vehicles. Thus, a VANET is an ad-hoc network with vehicles, other network
services and applications (2).
Figure 1: Conceptual Schematic of a VANET
The IEEE has completed the standards IEEE P1609.1, P1609.2, P1609.3, and P1609.4 for
vehicular networks and recently released them for trial use. (4)
4. VANET APPLICATIONS
The three major areas of applications of VANETs are safety oriented, convenience oriented and
commercial oriented. (5) Safety applications include a Slow/Stop Vehicle Advisor (SVA) which
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happens through V2V. Another safety application is Emergency Electronic Brake Light (EBBL).
Broadcast warning message about a vehicle involved in accident is done through Post Crash
Notification (PCN). Road Hazard Control Notification (RHCN) notifies other cars about road
slides, floods etc. Co-operative Collision Warning (CCW) alerts vehicles about potential crash
routes.
Convenience applications include Congested Road Notification (CRN) which alerts and notifies
congestion routes. Parking Availability Notification (PAN) helps in locating available parking
lots.
Commercial Applications include RVP/D, CMDD, RTVR and SA. Remote Vehicle
Personification/Diagnostics (RVP/D) downloads and uploads vehicle settings from/to
infrastructure. Content Map Database Download (CMDD) helps in obtaining information from
other stations. Real Time Video Relay (RTVR) helps in viewing videos for entertainment.
Service Announcements (SA) helps in giving alerts about gas stations, restaurants and restrooms
on the highway. (5) The U.S. Federal Communications Commission (FCC) recently allocated 75
MHz of Dedicated Short Range Communications (DSRC) spectrum, a one or two-way short to
medium range wireless communication channels at 5.9 GHz, to be used exclusively for V2V
and V2R communications(6).
5. MAC PROTOCOLS FOR VANETS
VANET Medium Access Control (MAC) protocols have to cater to the fast changing network
topologies and the different kinds of applications. VANET MAC protocols have to also reduce
the medium access delay for safety applications. Modifications need to be thus made to the MAC
layer to create wide scale VANETs, to share the wireless channel medium. It is the duty of the
MAC to ensure nodes from transmitting at the same time and to avoid collision. Due to the large
availability of cheap IEEE 802.11 based wireless devices, both the MAC and physical layer can
be addressed. (3)
Carrier Sense Multiple Access with Collision Detection (CSMA/CD) with acknowledgements
helps the network in avoiding collisions. Two protocols namely Distributed Co-ordinate
Function(DCF), a contention based, easy to implement access protocol where all the nodes
planning to send data compete for the channel, and Point Co-ordinate Function (PCF), a
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contention free protocol , which is not applicable to ad-hoc networks are defined by 802.11
standards. (7)
5.1 IEEE 802.11 Standards
IEEE defines a MAC sub layer, protocols and services for the WLANs and three physical (PHY)
layers. The SME (Station Management Entity) and MLME (MAC Layer Management Entity)
control the MAC sub layer.
The IEEE working group has now come out with the 802.11p, an approved amendment (2009) to
the IEEE 802.11 standard for implementing wireless access in vehicular environments (WAVE),
the next generation dedicated short-range communications (DSRC) state-of-the art technology to
support VANETs. IEEE 802.11p includes vehicular safety applications, data transfer enabled
through V2V and V2R, in the licensed ITS band of 5.9 GHz (5.85-5.925 GHz). The IEEE
802.11p also states that in the United States proposes that the information about an accident
should be communicated through VANET within half a second to all equipped vehicles in 500
meters range. (7) 802.11p will be used as the groundwork for DSRC based on the ISO CALM
architecture standard looking at vehicle-based communication networks, particularly for
applications such as toll collection, vehicle safety services, and commerce transactions via cars.
(8) CALM is an acronym for Continuous Air interface for Long and Medium distance. WAVE
uses the CSMA/CA as the basic medium access scheme for sharing links between vehicles and
stations.
6. INTER VEHICLE AND INTRA VEHICLE COMMUNICATION
Communicating vehicles can be possible by microwaves for broadcast communication and
infrared for directional communication, though microwaves are used more often (9). Bluetooth
technology is also used widely. Communication requests can be refused due to the master/slave
setup of Bluetooth. Directional MAC (DMAC) protocol, which uses only directional
transmissions (10) helps in avoiding hidden terminal and deafness problems among nodes. A
Circular Request to Send (CRTS) consisting of RTS-CTS-DATA-ACK is sent directionally. The
source transmits its data when it receives Clear to Send (CTS) message. Though DMAC should
have better performance, it is hindered by mobile portability. (10) The Adaptive Space Division
Multiplexing (ASDM) addresses the denial of Service (DoS) attacks. It is an extension of Space
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Division Multiple Access (SDMA) where time slots are assigned based on the location of
vehicles on the highway.
Communication functions inside a vehicle can be performed using the wireless technologies.
IEEE 802.15.1(Bluetooth), IEEE 802.15.3(UWB (Ultra Wide Band), high data rate) and IEEE
802.15.4 (ZigBee, low data rate) can be used for the inter vehicle communication. Bluetooth
which is a proven, cheap technology can transmit both voice and data with good security
features. The power requirement is low and security features are good. It conforms to the
Frequency Hopping Spread Spectrum (FHSS) mode and supports star topology and has error
correcting mechanisms (11).
7. SECURITY REQUIREMENTS IN VANETS
Similar to any other networks, VANETS are also vulnerable to attackers and adversaries. The
CIAN (Confidentiality, Integrity, Availability and Non-Repudiation) are of most importance to a
VANET.
Confidentiality- It ensures that information is accessible only to those nodes authorized to have
access. It prevents unauthorized access. Not all data are confidential but critical data require
confidentiality. This type of access includes printing, transmitting, displaying and other forms of
disclosure, including simply revealing the existing of a vehicle.
Integrity and Authentication – It ensures safeguarding the accuracy and completeness of
information and processing methods. Data cannot be modified.
Availability – Availability ensures that authorized users have access to information and
associated assets when required. Availability requires that vehicle details are available to
authorized parties. Availability is a requirement intended to assure that systems work promptly
and service is not denied to authorize users.
Non Repudiation – The sender of the message cannot deny having sent the message. It ensures
that a transferred message has been sent and received by the parties claiming to have sent and
received the message. It guarantees that the sender of a message cannot later deny having sent
the message and that the recipient cannot deny having received the message.
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