International Journal of Engineering Trends and Technology (IJETT) – Volume 4 Issue 9- Sep 2013
1
1
M.Tech Scholar ,
2
2
3
Assoc. Professor,
3
Asst.Professor
1,2
Dept of CSE, Aditya Institute of Technology And Management ,Tekkali
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Dept of MCA, Sree Vidyanikethan Institute of Management,Tirupathi.
Abstract: EEC enables the receiver of the packet to estimate rate. Some of the traditional process is presented in section the packet’s bit error rate which is perhaps the most important meta-information of a partially correct packet.In
II, and our proposed method presented in section III. present days these are playing crucial role for finding the packets bits error rate at receiver side. In traditional and existing algorithms the accuracy of the bit error rate slightly difficult. Because of this receiver couldn’t find the data correctly or not. So we introduced new framework containing the randomization of bits that accurately finds the bit error rate and works on each and every bit in the packet. It works on theoretical analysis also. If the BER in packets can be accurately estimated, important operations in wireless networks such as packet re-scheduling, routing, and carrier selection can be performed with greater efficiency.
The main disadvantages of the traditional works are that the main constraint of the calculation of the bit error rate is parity bits. Based on the parity bits the whole functionality depends. The parity bit adds a single bit that indicates whether the number of 1 bits in the preceding data was even or odd. If an odd number of bits is changed in transmission, the message will change parity and the error can be detected at this point. (Note that the bit that changed may have been the parity bit itself!) The most common convention is that a parity value of 1indicates that there is an odd number of ones in the data, and a parity
value of 0 indicates that there is an even number of ones. If the number of bits changed is even, the check bit will be valid and the error will not be detected.
In present days data exchanging is more scalable.
The data we are exchanging is in the form of packets and so called as data packets. There is a chance to get attacks in the communication channel that leads to loss of data. So there is a need to check that the data packet is securely received or not without losing the data. If the data corrupted there is a need to check how much percentage of data corrupted.
Moreover, parity does not indicate which bit contained the error, even when it can detect it. The data must be discarded entirely and re-transmitted from scratch.
On a noisy transmission medium, a successful transmission could take a long time or may never occur. However, while the quality of parity checking is poor, since it uses only a single bit, this method results in the least overhead.
Furthermore, parity checking does allow for the restoration of an erroneous bit when its position is known.
The data packets are checked in the bits range.
Checking can perform on the data in the range of bits because there are so many ways to corrupt. So we have to check the data in many ways considering major problems such as corrupter replaces a word which is equal to the original word, or completely changes the data etc. So the receiver which is relieved the data packet have to perform all considering ways.
The process of checking the data bits is Error
Estimation Coding. The rate which is calculated in the estimation process is called Bit Error Rate. In the Initial
Stage of the Data exchanging the Estimation Coding follows hamming distance. This hamming distance is mainly compares the bits which are received with the original bits. In this process the receiver have to know some part of the information in the original data packet.
So the researchers studied this problem very deeply and introduced so many methods to find bit error
In the traditional of error estimation coding the there are so many methods and they used parity bits but follows some other process to complete the process. The traditional method of error estimation coding is shown below:
First take the data packet and convert into binary form which is called as bit vector or binary vector. In the binary format take alternative bits from the starting position of the binary vector. Then replace the bits for 1 take +1 and for 0 take -1. All chosen bits are replaced by this way only. Then find sum of the bit vector after replacing of the bits. Then send the positions and the replaced values of the bit vector.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 4 Issue 9- Sep 2013
Then the receiver side the received bit vector and the positions are again replaced with the received replaced values and then find the sum of the bit vector. So the received total and the resultant sum of the bit vector is same then the received bits are not corrupted.
Then researchers introduced dot product on the bit vector. So that the process is explained below.
As same as the above explain process, Take data in the form of bits that is called as bit vector, Then that convert that bits into transformation vector. That vector also uses for bit 1 take +1 and for 0 take -1.
Then product bit vector and respective transformation bit in the transformation bit vector. The resultant bits are in the form of bits which is in the form of
1, +1, 0,-1 ..Etc. and divide by 2 for each bit in the resultant vector. Then we get X=x
1
, x2…..x
n
.
In the Estimation process received bit vector and the resultant X used to calculate the Error Estimation Rate.
For calculating we convert the received bit vector into transformation vector. Then we calculate the differences and average of their total then if we get the rate within the range 0 to 0.001 the data packet corrupted but not serious.
If we get 0 there is no error, else if get 0.001 to 1 range there is huge amount of data is corrupted.
The sketch
Here, we briefly describe and analyze the plain in the context of error estimating coding, under the assumption that the sketch per se is not subject to bit errors during transmission. The sketch of a bit array is comprised of a constant number c of counters that are maintained using the same update algorithm (with possibly different update values) and is sent to the receiver alongside with bit array. After the execution of these update algorithms, each counter contains the inner product of the bit array with a pre-defined pseudorandom vector {-1,1}.
The receipt of the transmitted bit array and the sketch (no bit error during transmission), the receiver computes the inner products using the received packet
(possibly with bit errors), takes the difference between them and the counters in the sketch sent along the packet, and squares the result. Each of these results is now an unbiased estimate the Hamming distance between the original and the transmitted packets, and can be averaged to give an accurate estimate of the Hamming distance.
This is needed for us to compare it with our enhanced framework, to be described in the next section.
To make comparison, here we no longer assume the sketch is immune from bit errors during transmissions. The total size of the sketch is determined by three factors: the number of counters, the size of each counter, and the number of extra bits needed to protect the sketch. Since our enhanced sketch uses the same number of counters.
In our proposed approach we consider only some range of bit levels which is suggested in [2]. So that we reduce the processing time of the reading bits from the packet. For given data first we convert into binary format.
We consider as value such as constant that is used to divide the binary data packet into equal parts, generally consider some n=5. For each part we main a counter value for representing unique part. So that after dividing the every counter we have to take care of the truncation bits which is come from the parity bits or overflow bits. This parameter is mainly introduced to gain maximum accuracy.
Finally the part of the binary vector is protected by the parity and the truncation bits. This is because considering the example supposes that a sender sent 5 bits of data packet to receiver. The data bits are corrupted in the communication channel, but the data bits are same as the original bits. In normal case we didn’t check for the content but they are visually same. So by performing the parity and truncation bits this problem will solve. If the above case is considered when the parity bits and the truncation bits are same as the original then only the received data packet is secure otherwise its corrupted.
The detailed algorithm is shown below:
Algorithm
Enhanced framework with parameters (c, l, k, r).
Input b’: original data bits vector.
Output z: the sketch of b’. pre-compute l-bit-long vectors s j

,1 ≤j≤c
: [n]  {-1,1}
For j = 1 to c do l-bits-long vector b
 j
: sampled with replacement from b 
Random projection: z’ j
:= (b’ j
. s’ j
)/2 k-bits-long truncated projection: z j
:= trunck( z  j
) r-bits-long parities q j
:= parityr(z j
) return c(k+r)-bits long sketch z = (z
1
……z c
) (q
1…… q c
)
DISTANCE–ESTIMATION(b  ’,z’)
Input b

’: received data bits vector, z’: received sketch.
Output p’: The estimate of the error rate p. pre-compute l-bit-long vectors s j

,1 ≤j≤c
: [l]  {-1,1} for j = 1 to c do l-bits-long vector b j

’: sampled with replacement from b
 ’
(with the same hash seed pre-configured.)
Random projection: z  ’
= z j
:= (b j
 .s
j
 )/2
Estimation Yj := trunck( z’ j
- z j
) ,X j
= Y j
2
Check parities V j
:= 1 {q j
=parityr(trunck( z’ j
} return p’ = Σ c j=1 v j x j
/ Σ c j=1 v j
as the estimation of error rate .
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International Journal of Engineering Trends and Technology (IJETT) – Volume 4 Issue 9- Sep 2013
According to the proposed system, the following experimental analysis we took encoding bit vector,
Truncation bits, parity bits and these parameters are send to receiver.
In receiver side after receiving, the bit vector and calculates pre-compute vector and random projection , if any bits are changed then the bit error rate is calculated.
If data is changed then the error rate is calculated. As shown below.
In this paper introduced new framework that reduces the bit error rate and optimal solution for two party computation problems. This is more better than traditional bit error rate algorithms according to delivery performance.
The proposed framework is fully analyzable and provable estimation quality, with rather low redundancy. Our realworld experiments have demonstrated that more applications can significantly benefit from EEC.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 4 Issue 9- Sep 2013
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BIOGRAPHIES
V . Ashok Gajapathi Raju stydying,
M .Tech Scholar(CSE) in Aditya Institute of Technology and Management, Tekkali.
Completed MCA from Aditya Institute of
Technology and Management, Tekkali.
T.NARESH has 4 years and 6 months of teaching experience in reputed colleges.
Presently he working as Assistant
Professor in Department of MCA , Sree
Vidyanikethan Institute of Management.
He completed M.Tech in 2012 at Pydah
College of Engineering and completed
MCA in 2009 at Aditya Institute of technology and Management.
His area of Interests are Computer organization, operating system,
Unix programming, and programming languages (C,C++,java),
DBMS, Multimedia application development and Software
Engineering .Currently he was published 4 papers in areas like text mining and network security in issues of IJERA-2012,
IJCTT-2013 . He was member of IAENG.
Mr. YEGIREDDI RAMESH is MCA
(Computer Applications) from Osmania
University and M.Tech(CSE) from
JNTUH Hyderabad, Andhra Pradesh,
India. He is working as Associate professor in Computer Science &
Engineering department in Aditya
Institute of Technology and Management,
Tekkali, Andhra Pradesh, India. He has
12 years of experience in teaching Computer Science and
Engineering related subjects. He is a research scholar in JNTU
Kakinada and his area of interest and research include Computer
Networks, Wireless LANs & Ad-Hoc Networks and Cloud
Computing. He has published several Research papers in national and international journals/conferences. He has guided more than
80 students of Bachelor degree, 25 Students of Master degree in
Computer Science and Engineering in their major projects. He is a member of ISTE and CSI.
ISSN: 2231-5381 http://www.ijettjournal.org
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