One of the important steps in routing is to find a feasible path based on the state information. In order to support real-time multimedia applications, the feasible path that satisfies one or more constraints has to be computed within a very short time. Therefore, the paper presents a genetic algorithm to solve the paths tree problem subject to cost constraints. The objective of the algorithm is to find the set of edges connecting all nodes such that the sum of the edge costs from the source (root) to each node is minimized. I.e. the path from the root to each node must be a minimum cost path connecting them. The algorithm has been applied on two sample networks, the first network with eight nodes, and the last one with eleven nodes to illustrate its efficiency.
A NOVEL ANT COLONY ALGORITHM FOR MULTICAST ROUTING IN WIRELESS AD HOC NETWORKS cscpconf
The Steiner tree is the underlying model for multicast communication. This paper presents a
novel ant colony algorithm guided by problem relaxation for unconstrained Steiner tree in static
wireless ad hoc networks. The framework of the proposed algorithm is based on ant colony
system (ACS). In the first step, the ants probabilistically construct the path from the source tothe terminal nodes. These paths are then merged together to generate a Steiner tree rooted at the source. The problem is relaxed to incorporate the structural information into the heuristic value for the selection of nodes. The effectiveness of the algorithm is tested on the benchmark problems of the OR-library. Simulation results show that our algorithm can find optimal Steiner tree with high success rate.
A Threshold Enhancement Technique for Chaotic On-Off Keying SchemeCSCJournals
In this paper, an improvement for Chaotic ON-OFF (COOK) Keying scheme is proposed. The scheme enhances Bit Error Rate (BER) performance of standard COOK by keeping the signal elements at fixed distance from the threshold irrespective of noise power. Each transmitted chaotic segment is added to its flipped version before transmission. This reduces the effect of noise contribution at correlator of the receiver. The proposed system is tested in Additive White Gaussian Noise (AWGN) channel and compared with the standard COOK under different Eb/No levels. A theoretical estimate of BER is derived and compared with the simulation results. Effect of spreading factor increment in the proposed system is studied. Results show that the proposed scheme has a considerable advantage over the standard COOK at similar average bit energy and with higher values of spreading factors.
Route Optimization to make Energy Efficient MANET using Vishal Fuzzy Genetic ...ijsrd.com
In any network QOS is one the basic requirement and when we talk about the MANET(mobile AD-HOC network) this is the highly constraint requirement of a user. To improve the quality of service we use different changes in MANET protocols, its parameter, routing algorithm etc. In this proposed work we are also improving the QOS by modifying the routing algorithm. The proposed routing algorithm is inspired from the genetic approach. The proposed algorithm will follow all the basic steps of routing algorithm in the sequence. As in initializing phase we will select the shortest path and one alternative aggregative path. The shortest path selection always returns the congestion over the network. Instead of using the shortest path we will select a genetic inspired path. In this work, the selection of the next cross over child path will be identified based on cyclic fuzzy logic. The whole process will optimize the routing algorithm to improve the QOS. In this work, the fuzzy-improved Genetic algorithm will be implemented on MATLAB 7.1 for the route generation.
Behavior study of entropy in a digital image through an iterative algorithmijscmcj
Image segmentation is a critical step in computer vision tasks constituting an essential issue for pattern recognition and visual interpretation. In this paper, we study the behavior of entropy in digital images through an iterative algorithm of mean shift filtering. The order of a digital image in gray levels is defined. The behavior of Shannon entropy is analyzed and then compared, taking into account the number of iterations of our algorithm, with the maximum entropy that could be achieved under the same order. The use of equivalence classes it induced, which allow us to interpret entropy as a hyper-surface in real m dimensional space. The difference of the maximum entropy of order n and the entropy of the image is used to group the the iterations, in order to caractrizes the performance of the algorithm.
Buffer Allocation Problem is an important research issue in manufacturing system design.
Objective of this paper is to find optimum buffer allocation for closed queuing network with
multi servers at each node. Sum of buffers in closed queuing network is constant. Attempt is
made to find optimum number of pallets required to maximize throughput of manufacturing
system which has pre specified space for allocating pallets. Expanded Mean Value Analysis is
used to evaluate the performance of closed queuing network. Particle Swarm Optimization is
used as generative technique to optimize the buffer allocation. Numerical experiments are
shown to explain effectiveness of procedure
On the performance of code word diversity based quasi orthogonal space time b...IJECEIAES
In the recent past, a lot of researches have been put into designing a MultipleInput-Multiple-Output (MIMO) system to provide multimedia services with higher quality and at higher data rate. On par with these requirements, a novel Quasi Orthogonal Space Time Block Code (QOSTBC) scheme based on code word diversity is proposed, which is a multi-dimensional approach, in this paper. The term code word diversity is coined, since the information symbols were spread across many code words in addition to traditional time and spatial spreading, without increasing transmission power and bandwidth. The receiver with perfect channel state information estimates the transmitted symbols with less probability of error, as more number of samples is available to estimate given number of symbols due to the extra diversity due to code words. The simulation results show a significant improvement in the Bit Error Rate (BER) performance of the proposed scheme when compared with the conventional schemes.
A NOVEL ANT COLONY ALGORITHM FOR MULTICAST ROUTING IN WIRELESS AD HOC NETWORKS cscpconf
The Steiner tree is the underlying model for multicast communication. This paper presents a
novel ant colony algorithm guided by problem relaxation for unconstrained Steiner tree in static
wireless ad hoc networks. The framework of the proposed algorithm is based on ant colony
system (ACS). In the first step, the ants probabilistically construct the path from the source tothe terminal nodes. These paths are then merged together to generate a Steiner tree rooted at the source. The problem is relaxed to incorporate the structural information into the heuristic value for the selection of nodes. The effectiveness of the algorithm is tested on the benchmark problems of the OR-library. Simulation results show that our algorithm can find optimal Steiner tree with high success rate.
A Threshold Enhancement Technique for Chaotic On-Off Keying SchemeCSCJournals
In this paper, an improvement for Chaotic ON-OFF (COOK) Keying scheme is proposed. The scheme enhances Bit Error Rate (BER) performance of standard COOK by keeping the signal elements at fixed distance from the threshold irrespective of noise power. Each transmitted chaotic segment is added to its flipped version before transmission. This reduces the effect of noise contribution at correlator of the receiver. The proposed system is tested in Additive White Gaussian Noise (AWGN) channel and compared with the standard COOK under different Eb/No levels. A theoretical estimate of BER is derived and compared with the simulation results. Effect of spreading factor increment in the proposed system is studied. Results show that the proposed scheme has a considerable advantage over the standard COOK at similar average bit energy and with higher values of spreading factors.
Route Optimization to make Energy Efficient MANET using Vishal Fuzzy Genetic ...ijsrd.com
In any network QOS is one the basic requirement and when we talk about the MANET(mobile AD-HOC network) this is the highly constraint requirement of a user. To improve the quality of service we use different changes in MANET protocols, its parameter, routing algorithm etc. In this proposed work we are also improving the QOS by modifying the routing algorithm. The proposed routing algorithm is inspired from the genetic approach. The proposed algorithm will follow all the basic steps of routing algorithm in the sequence. As in initializing phase we will select the shortest path and one alternative aggregative path. The shortest path selection always returns the congestion over the network. Instead of using the shortest path we will select a genetic inspired path. In this work, the selection of the next cross over child path will be identified based on cyclic fuzzy logic. The whole process will optimize the routing algorithm to improve the QOS. In this work, the fuzzy-improved Genetic algorithm will be implemented on MATLAB 7.1 for the route generation.
Behavior study of entropy in a digital image through an iterative algorithmijscmcj
Image segmentation is a critical step in computer vision tasks constituting an essential issue for pattern recognition and visual interpretation. In this paper, we study the behavior of entropy in digital images through an iterative algorithm of mean shift filtering. The order of a digital image in gray levels is defined. The behavior of Shannon entropy is analyzed and then compared, taking into account the number of iterations of our algorithm, with the maximum entropy that could be achieved under the same order. The use of equivalence classes it induced, which allow us to interpret entropy as a hyper-surface in real m dimensional space. The difference of the maximum entropy of order n and the entropy of the image is used to group the the iterations, in order to caractrizes the performance of the algorithm.
Buffer Allocation Problem is an important research issue in manufacturing system design.
Objective of this paper is to find optimum buffer allocation for closed queuing network with
multi servers at each node. Sum of buffers in closed queuing network is constant. Attempt is
made to find optimum number of pallets required to maximize throughput of manufacturing
system which has pre specified space for allocating pallets. Expanded Mean Value Analysis is
used to evaluate the performance of closed queuing network. Particle Swarm Optimization is
used as generative technique to optimize the buffer allocation. Numerical experiments are
shown to explain effectiveness of procedure
On the performance of code word diversity based quasi orthogonal space time b...IJECEIAES
In the recent past, a lot of researches have been put into designing a MultipleInput-Multiple-Output (MIMO) system to provide multimedia services with higher quality and at higher data rate. On par with these requirements, a novel Quasi Orthogonal Space Time Block Code (QOSTBC) scheme based on code word diversity is proposed, which is a multi-dimensional approach, in this paper. The term code word diversity is coined, since the information symbols were spread across many code words in addition to traditional time and spatial spreading, without increasing transmission power and bandwidth. The receiver with perfect channel state information estimates the transmitted symbols with less probability of error, as more number of samples is available to estimate given number of symbols due to the extra diversity due to code words. The simulation results show a significant improvement in the Bit Error Rate (BER) performance of the proposed scheme when compared with the conventional schemes.
MULTI-OBJECTIVE ENERGY EFFICIENT OPTIMIZATION ALGORITHM FOR COVERAGE CONTROL ...ijcseit
Many studies have been done in the area of Wireless Sensor Networks (WSNs) in recent years. In this kind of networks, some of the key objectives that need to be satisfied are area coverage, number of active sensors and energy consumed by nodes. In this paper, we propose a NSGA-II based multi-objective algorithm for optimizing all of these objectives simultaneously. The efficiency of our algorithm is demonstrated in the simulation results. This efficiency can be shown as finding the optimal balance point among the maximum coverage rate, the least energy consumption, and the minimum number of active nodes while maintaining the connectivity of the network
A C OMPARATIVE A NALYSIS A ND A PPLICATIONS O F M ULTI W AVELET T RANS...IJCI JOURNAL
In the era of telemedicine a large amount of medica
l information is exchanged via electronic media mos
tly
in the form of medical images, to improve the accur
acy and speed of diagnosis process. Medical Image
denoising has the basic importance in image analysi
s as these algorithm and procedures affects the eff
icacy
of medical diagnostic. In this paper focus is on Mu
lti wavelets based Image denoising techniques, beca
use
they provide the possibility of designing wavelets
systems which are orthogonal, symmetric and compact
ly
supported, simultaneously. Performance of Discrete
Multi Wavelet Transform and Discrete Wavelet
Transform based denoising methods are compared on t
he basis of PSNR
Design of an Adaptive Hearing Aid Algorithm using Booth-Wallace Tree MultiplierWaqas Tariq
The paper presents FPGA implementation of a spectral sharpening process suitable for speech enhancement and noise reduction algorithms for digital hearing aids. Booth and Booth Wallace multiplier is used for implementing digital signal processing algorithms in hearing aids. VHDL simulation results confirm that Booth Wallace multiplier is hardware efficient and performs faster than Booth’s multiplier. Booth Wallace multiplier consumes 40% less power compared to Booth multiplier. A novel digital hearing aid using spectral sharpening filter employing booth Wallace multiplier is proposed. The results reveal that the hardware requirement for implementing hearing aid using Booth Wallace multiplier is less when compared with that of a booth multiplier. Furthermore it is also demonstrated that digital hearing aid using Booth Wallace multiplier consumes less power and performs better in terms of speed.
Compressive Sensing in Speech from LPC using Gradient Projection for Sparse R...IJERA Editor
This paper presents compressive sensing technique used for speech reconstruction using linear predictive coding because the
speech is more sparse in LPC. DCT of a speech is taken and the DCT points of sparse speech are thrown away arbitrarily.
This is achieved by making some point in DCT domain to be zero by multiplying with mask functions. From the incomplete
points in DCT domain, the original speech is reconstructed using compressive sensing and the tool used is Gradient
Projection for Sparse Reconstruction. The performance of the result is compared with direct IDCT subjectively. The
experiment is done and it is observed that the performance is better for compressive sensing than the DCT.
A Text-Independent Speaker Identification System based on The Zak TransformCSCJournals
A novel text-independent speaker identification system based on the Zak transform is implemented. The data used in this paper are drawn from the ELSDSR database. The efficiency of identification approaches 91.3% using single test file and 100% using two test files. The method shows comparable efficiency results with the well known MFCC method with an advantage of being faster in both modeling and identification.
PERFORMANCE AND COMPLEXITY ANALYSIS OF A REDUCED ITERATIONS LLL ALGORITHMIJCNCJournal
Multiple-input multiple-output (MIMO) systems are playing an increasing and interesting role in the recent
wireless communication. The complexity and the performance of the systems are driving the different
studies and researches. Lattices Reduction techniques bring more resources to investigate the complexity
and performances of such systems.
In this paper, we look to modify a fixed complexity verity of the LLL algorithm to reduce the computation
operations by reducing the number of iterations without important performance degradation. Our proposal
shows that we can achieve a good performance results while avoiding extra iteration that doesn’t bring
much performance.
A detection technique of signal in mimo systemeSAT Journals
Abstract MIMO techniques are based on multiple antennae in receiving and transmitting signals and also used in multipath propagation for the transformation of entire channel into many independent virtual channels. In MIMO system multiple antennae can increase the spectral efficiency/ reliability of radio channel without increasing bandwidth or transmit power. Commercially, it is not feasible in case of MIMO systems. So, simple and efficient receiver that can harness MIMO architecture benefits without draining mobile receiver battery power or long time to decode transmitted symbols was required. In this paper problem of receiver design for MIMO system in spatial multiplexing scheme that is Maximum likelihood detection problem also known as NP hard combinatorial optimization problem, which need an exponential search over the space of all possible transmitted symbols in order to find closest point in Euclidean sense to received symbols, has been considered. A metaheuristic algorithm for detection of MIMO wireless system based on the Ant colony optimization (ACO) technique using MATLAB give the best solution to the problem and find the optimal path for the receivers. Keywords: ACO, CO- combinatorial optimization, MATLAB, Metaheuristic, MIMO, NP Hard-non deterministic polynomial time hard, QAM- quadratic amplitude modulation
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
In this project, we consider the deep learning-based approaches to performing Neural Style Transfer (NST) on images. In particular, we intend to assess the Real-Time performance of this approach, since it has become a trending topic both in academia and in industrial applications.
For this purpose, after exploring the perceptual loss concept, which is used by the majority of models when performing NST, we conducted a review on a range of existing methods for this practical problem. We found that the feedforward based methods allow to achieve real time performance as opposed to the framework of iterative optimization proposed in the original Neural Style Transfer algorithm introduced by Gatys et al. Which is why we mainly focused on two feed-forward methods proposed in the literature: one that focuses on Single-Style transfer, TransformNet, and one that tackles the more generic problem of Multiple Style Transfer, MSG-Net.
Enriched Firefly Algorithm for Solving Reactive Power Problemijeei-iaes
In this paper, Enriched Firefly Algorithm (EFA) is planned to solve optimal reactive power dispatch problem. This algorithm is a kind of swarm intelligence algorithm based on the response of a firefly to the light of other fireflies. In this paper, we plan an augmentation on the original firefly algorithm. The proposed algorithm extends the single population FA to the interacting multi-swarms by cooperative Models. The proposed EFA has been tested on standard IEEE 30 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss.
Improving Performance of Back propagation Learning Algorithmijsrd.com
The standard back-propagation algorithm is one of the most widely used algorithm for training feed-forward neural networks. One major drawback of this algorithm is it might fall into local minima and slow convergence rate. Natural gradient descent is principal method for solving nonlinear function is presented and is combined with the modified back-propagation algorithm yielding a new fast training multilayer algorithm. This paper describes new approach to natural gradient learning in which the number of parameters necessary is much smaller than the natural gradient algorithm. This new method exploits the algebraic structure of the parameter space to reduce the space and time complexity of algorithm and improve its performance.
A new efficient way based on special stabilizer multiplier permutations to at...IJECEIAES
BCH codes represent an important class of cyclic error-correcting codes; their minimum distances are known only for some cases and remains an open NP-Hard problem in coding theory especially for large lengths. This paper presents an efficient scheme ZSSMP (Zimmermann Special Stabilizer Multiplier Permutation) to find the true value of the minimum distance for many large BCH codes. The proposed method consists in searching a codeword having the minimum weight by Zimmermann algorithm in the sub codes fixed by special stabilizer multiplier permutations. These few sub codes had very small dimensions compared to the dimension of the considered code itself and therefore the search of a codeword of global minimum weight is simplified in terms of run time complexity. ZSSMP is validated on all BCH codes of length 255 for which it gives the exact value of the minimum distance. For BCH codes of length 511, the proposed technique passes considerably the famous known powerful scheme of Canteaut and Chabaud used to attack the public-key cryptosystems based on codes. ZSSMP is very rapid and allows catching the smallest weight codewords in few seconds. By exploiting the efficiency and the quickness of ZSSMP, the true minimum distances and consequently the error correcting capability of all the set of 165 BCH codes of length up to 1023 are determined except the two cases of the BCH(511,148) and BCH(511,259) codes. The comparison of ZSSMP with other powerful methods proves its quality for attacking the hardness of minimum weight search problem at least for the codes studied in this paper.
Bounds on the Achievable Rates of Faded Dirty Paper Channel IJCNCJournal
Bounds on the achievable rate of a Gaussian channel in the case that the transmitter knows the
interference signal but not its fading coefficients are given. We generalize the analysis which were studied
in [1] and [4] so that their results are special cases of our analysis. We enforce our bounds by simulations
in which many numerical examples are drawn and investigated under different cases.
Architecture neural network deep optimizing based on self organizing feature ...journalBEEI
Forward neural network (FNN) execution relying on the algorithm of training and architecture selection. Different parameters using for nip out the architecture of FNN such as the connections number among strata, neurons hidden number in each strata hidden and hidden strata number. Feature architectural combinations exponential could be uncontrollable manually so specific architecture can be design automatically by using special algorithm which build system with ability generalization better. Determination of architecture FNN can be done by using the algorithm of optimization numerous. In this paper methodology new proposes achievement where FNN neurons respective with hidden layers estimation work where in this work collect algorithm training self organizing feature map (SOFM) with advantages to explain how the best architectural selected automatically by SOFM from criteria error testing based on architecture populated. Different size of dataset benchmark of 4 classifications tested for approach proposed.
P REDICTION F OR S HORT -T ERM T RAFFIC F LOW B ASED O N O PTIMIZED W...ijcsit
Short term traffic forecasting has been a very impo
rtant consideration in many areas of transportation
research for more than 3 decades. Short-term traffi
c forecasting based on data driven methods is one o
f the
most dynamic and developing research arenas with en
ormous published literature. In order to improve
forecasting model accuracy of wavelet neural networ
k, an adaptive particle swarm optimization algorith
m
based on cloud theory was proposed, not only to hel
p improve search performance, but also speed up
individual optimizing ability. And the inertia weig
ht adaptively changes depending on X-conditional cl
oud
generator which has the stable tendency and randomn
ess property .Then the adaptive particle swarm
optimization algorithm based on cloud theory was us
ed to optimize the weights and thresholds of wavele
t
BP neural network, Instead of traditional gradient
descent method . At last, wavelet BP neural network
was
trained to search for the optimal solution. Based o
n above theory, an improved wavelet neural network
model based on modified particle swarm optimization
algorithm was proposed and the availability of the
modified prediction method was proved by predicting
the time series of real traffic flow. At last, the
computer simulations have shown that the nonlinear
fitting and accuracy of the modified prediction
methods are better than other prediction methods.
Macromodel of High Speed Interconnect using Vector Fitting Algorithmijsrd.com
At high frequency efficient macromodeling of high speed interconnects is all time challenging task. We have presented systematic methodologies to generate rational function approximations of high-speed interconnects using vector fitting technique for any type of termination conditions and construct efficient multiport model, which is easily and directly compatible with circuit simulators.
PAPR analysis of OFDM system using AI based multiple signal representation me...TELKOMNIKA JOURNAL
OFDM (orthogonal frequency division multiplexing) is widely used in 4th generation applications owing to its robustness in fading environments. The major issues with OFDM systems is the high PAPR (peak-to-average power ratio) of the transmitted signals, it leads to in and out of band distortion. SLM (selective mapping) and PTS (partial transmit sequence) are two key methods for PAPR reduction. Both the methods require exhaustive searching of phase factors to optimize the PAPR, these searches lead to high computational complexity. This paper discusses using optimization based PAPR reduction methods which an be used with PTS for the reduction of computational complexity and search space. In this paper we have analyzed PTS and SLM with particle swarm optimization (PSO), Artificial Bee Colony (ABC) and differential evolution (DE). PAPR and BER (bit error rate) comparison is done for both the cases.
A distributed ip based telecommunication system using sipIJCNCJournal
Voice over Internet Protocol (VoIP) technologies are integral to modern telecommunications because of
their advanced features, flexibility, and economic benefits. Internet Service Providers initially promoted
these technologies by providing low cost local and international calling. At present, there is also a great
deal of interest in using IP-based technologies to replace traditional small and large office telephone
systems that use traditional PBX’s (Private Branch eXchange). Unfortunately, the large majority of the
emerging VoIP based office telephone systems have followed the centralized design of traditional public
and private telephone systems in which all the intelligence in the system is at the core, with quite expensive
hardware and software components and appropriate redundancy for adequate levels of reliability. In this
paper, it is argued that a centralized model for an IP-based telecommunications system fails to exploit the
full capabilities of Internet-inspired communications and that, very simple, inexpensive, elegant and
flexible solutions are possible by deliberately avoiding the centralized approach. This paper describes the
design, philosophy and implementation of a prototype for a fully distributed IP-based Telecommunication
System (IPTS) that provides the essential feature set for office and home telecommunications, including IPbased
long-distance and local calling, and with the support for video as well as data and text. The
prototype system was implemented with an Internet-inspired distributed design using open source software,
with appropriate customizations and configurations.
MULTI-OBJECTIVE ENERGY EFFICIENT OPTIMIZATION ALGORITHM FOR COVERAGE CONTROL ...ijcseit
Many studies have been done in the area of Wireless Sensor Networks (WSNs) in recent years. In this kind of networks, some of the key objectives that need to be satisfied are area coverage, number of active sensors and energy consumed by nodes. In this paper, we propose a NSGA-II based multi-objective algorithm for optimizing all of these objectives simultaneously. The efficiency of our algorithm is demonstrated in the simulation results. This efficiency can be shown as finding the optimal balance point among the maximum coverage rate, the least energy consumption, and the minimum number of active nodes while maintaining the connectivity of the network
A C OMPARATIVE A NALYSIS A ND A PPLICATIONS O F M ULTI W AVELET T RANS...IJCI JOURNAL
In the era of telemedicine a large amount of medica
l information is exchanged via electronic media mos
tly
in the form of medical images, to improve the accur
acy and speed of diagnosis process. Medical Image
denoising has the basic importance in image analysi
s as these algorithm and procedures affects the eff
icacy
of medical diagnostic. In this paper focus is on Mu
lti wavelets based Image denoising techniques, beca
use
they provide the possibility of designing wavelets
systems which are orthogonal, symmetric and compact
ly
supported, simultaneously. Performance of Discrete
Multi Wavelet Transform and Discrete Wavelet
Transform based denoising methods are compared on t
he basis of PSNR
Design of an Adaptive Hearing Aid Algorithm using Booth-Wallace Tree MultiplierWaqas Tariq
The paper presents FPGA implementation of a spectral sharpening process suitable for speech enhancement and noise reduction algorithms for digital hearing aids. Booth and Booth Wallace multiplier is used for implementing digital signal processing algorithms in hearing aids. VHDL simulation results confirm that Booth Wallace multiplier is hardware efficient and performs faster than Booth’s multiplier. Booth Wallace multiplier consumes 40% less power compared to Booth multiplier. A novel digital hearing aid using spectral sharpening filter employing booth Wallace multiplier is proposed. The results reveal that the hardware requirement for implementing hearing aid using Booth Wallace multiplier is less when compared with that of a booth multiplier. Furthermore it is also demonstrated that digital hearing aid using Booth Wallace multiplier consumes less power and performs better in terms of speed.
Compressive Sensing in Speech from LPC using Gradient Projection for Sparse R...IJERA Editor
This paper presents compressive sensing technique used for speech reconstruction using linear predictive coding because the
speech is more sparse in LPC. DCT of a speech is taken and the DCT points of sparse speech are thrown away arbitrarily.
This is achieved by making some point in DCT domain to be zero by multiplying with mask functions. From the incomplete
points in DCT domain, the original speech is reconstructed using compressive sensing and the tool used is Gradient
Projection for Sparse Reconstruction. The performance of the result is compared with direct IDCT subjectively. The
experiment is done and it is observed that the performance is better for compressive sensing than the DCT.
A Text-Independent Speaker Identification System based on The Zak TransformCSCJournals
A novel text-independent speaker identification system based on the Zak transform is implemented. The data used in this paper are drawn from the ELSDSR database. The efficiency of identification approaches 91.3% using single test file and 100% using two test files. The method shows comparable efficiency results with the well known MFCC method with an advantage of being faster in both modeling and identification.
PERFORMANCE AND COMPLEXITY ANALYSIS OF A REDUCED ITERATIONS LLL ALGORITHMIJCNCJournal
Multiple-input multiple-output (MIMO) systems are playing an increasing and interesting role in the recent
wireless communication. The complexity and the performance of the systems are driving the different
studies and researches. Lattices Reduction techniques bring more resources to investigate the complexity
and performances of such systems.
In this paper, we look to modify a fixed complexity verity of the LLL algorithm to reduce the computation
operations by reducing the number of iterations without important performance degradation. Our proposal
shows that we can achieve a good performance results while avoiding extra iteration that doesn’t bring
much performance.
A detection technique of signal in mimo systemeSAT Journals
Abstract MIMO techniques are based on multiple antennae in receiving and transmitting signals and also used in multipath propagation for the transformation of entire channel into many independent virtual channels. In MIMO system multiple antennae can increase the spectral efficiency/ reliability of radio channel without increasing bandwidth or transmit power. Commercially, it is not feasible in case of MIMO systems. So, simple and efficient receiver that can harness MIMO architecture benefits without draining mobile receiver battery power or long time to decode transmitted symbols was required. In this paper problem of receiver design for MIMO system in spatial multiplexing scheme that is Maximum likelihood detection problem also known as NP hard combinatorial optimization problem, which need an exponential search over the space of all possible transmitted symbols in order to find closest point in Euclidean sense to received symbols, has been considered. A metaheuristic algorithm for detection of MIMO wireless system based on the Ant colony optimization (ACO) technique using MATLAB give the best solution to the problem and find the optimal path for the receivers. Keywords: ACO, CO- combinatorial optimization, MATLAB, Metaheuristic, MIMO, NP Hard-non deterministic polynomial time hard, QAM- quadratic amplitude modulation
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
In this project, we consider the deep learning-based approaches to performing Neural Style Transfer (NST) on images. In particular, we intend to assess the Real-Time performance of this approach, since it has become a trending topic both in academia and in industrial applications.
For this purpose, after exploring the perceptual loss concept, which is used by the majority of models when performing NST, we conducted a review on a range of existing methods for this practical problem. We found that the feedforward based methods allow to achieve real time performance as opposed to the framework of iterative optimization proposed in the original Neural Style Transfer algorithm introduced by Gatys et al. Which is why we mainly focused on two feed-forward methods proposed in the literature: one that focuses on Single-Style transfer, TransformNet, and one that tackles the more generic problem of Multiple Style Transfer, MSG-Net.
Enriched Firefly Algorithm for Solving Reactive Power Problemijeei-iaes
In this paper, Enriched Firefly Algorithm (EFA) is planned to solve optimal reactive power dispatch problem. This algorithm is a kind of swarm intelligence algorithm based on the response of a firefly to the light of other fireflies. In this paper, we plan an augmentation on the original firefly algorithm. The proposed algorithm extends the single population FA to the interacting multi-swarms by cooperative Models. The proposed EFA has been tested on standard IEEE 30 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss.
Improving Performance of Back propagation Learning Algorithmijsrd.com
The standard back-propagation algorithm is one of the most widely used algorithm for training feed-forward neural networks. One major drawback of this algorithm is it might fall into local minima and slow convergence rate. Natural gradient descent is principal method for solving nonlinear function is presented and is combined with the modified back-propagation algorithm yielding a new fast training multilayer algorithm. This paper describes new approach to natural gradient learning in which the number of parameters necessary is much smaller than the natural gradient algorithm. This new method exploits the algebraic structure of the parameter space to reduce the space and time complexity of algorithm and improve its performance.
A new efficient way based on special stabilizer multiplier permutations to at...IJECEIAES
BCH codes represent an important class of cyclic error-correcting codes; their minimum distances are known only for some cases and remains an open NP-Hard problem in coding theory especially for large lengths. This paper presents an efficient scheme ZSSMP (Zimmermann Special Stabilizer Multiplier Permutation) to find the true value of the minimum distance for many large BCH codes. The proposed method consists in searching a codeword having the minimum weight by Zimmermann algorithm in the sub codes fixed by special stabilizer multiplier permutations. These few sub codes had very small dimensions compared to the dimension of the considered code itself and therefore the search of a codeword of global minimum weight is simplified in terms of run time complexity. ZSSMP is validated on all BCH codes of length 255 for which it gives the exact value of the minimum distance. For BCH codes of length 511, the proposed technique passes considerably the famous known powerful scheme of Canteaut and Chabaud used to attack the public-key cryptosystems based on codes. ZSSMP is very rapid and allows catching the smallest weight codewords in few seconds. By exploiting the efficiency and the quickness of ZSSMP, the true minimum distances and consequently the error correcting capability of all the set of 165 BCH codes of length up to 1023 are determined except the two cases of the BCH(511,148) and BCH(511,259) codes. The comparison of ZSSMP with other powerful methods proves its quality for attacking the hardness of minimum weight search problem at least for the codes studied in this paper.
Bounds on the Achievable Rates of Faded Dirty Paper Channel IJCNCJournal
Bounds on the achievable rate of a Gaussian channel in the case that the transmitter knows the
interference signal but not its fading coefficients are given. We generalize the analysis which were studied
in [1] and [4] so that their results are special cases of our analysis. We enforce our bounds by simulations
in which many numerical examples are drawn and investigated under different cases.
Architecture neural network deep optimizing based on self organizing feature ...journalBEEI
Forward neural network (FNN) execution relying on the algorithm of training and architecture selection. Different parameters using for nip out the architecture of FNN such as the connections number among strata, neurons hidden number in each strata hidden and hidden strata number. Feature architectural combinations exponential could be uncontrollable manually so specific architecture can be design automatically by using special algorithm which build system with ability generalization better. Determination of architecture FNN can be done by using the algorithm of optimization numerous. In this paper methodology new proposes achievement where FNN neurons respective with hidden layers estimation work where in this work collect algorithm training self organizing feature map (SOFM) with advantages to explain how the best architectural selected automatically by SOFM from criteria error testing based on architecture populated. Different size of dataset benchmark of 4 classifications tested for approach proposed.
P REDICTION F OR S HORT -T ERM T RAFFIC F LOW B ASED O N O PTIMIZED W...ijcsit
Short term traffic forecasting has been a very impo
rtant consideration in many areas of transportation
research for more than 3 decades. Short-term traffi
c forecasting based on data driven methods is one o
f the
most dynamic and developing research arenas with en
ormous published literature. In order to improve
forecasting model accuracy of wavelet neural networ
k, an adaptive particle swarm optimization algorith
m
based on cloud theory was proposed, not only to hel
p improve search performance, but also speed up
individual optimizing ability. And the inertia weig
ht adaptively changes depending on X-conditional cl
oud
generator which has the stable tendency and randomn
ess property .Then the adaptive particle swarm
optimization algorithm based on cloud theory was us
ed to optimize the weights and thresholds of wavele
t
BP neural network, Instead of traditional gradient
descent method . At last, wavelet BP neural network
was
trained to search for the optimal solution. Based o
n above theory, an improved wavelet neural network
model based on modified particle swarm optimization
algorithm was proposed and the availability of the
modified prediction method was proved by predicting
the time series of real traffic flow. At last, the
computer simulations have shown that the nonlinear
fitting and accuracy of the modified prediction
methods are better than other prediction methods.
Macromodel of High Speed Interconnect using Vector Fitting Algorithmijsrd.com
At high frequency efficient macromodeling of high speed interconnects is all time challenging task. We have presented systematic methodologies to generate rational function approximations of high-speed interconnects using vector fitting technique for any type of termination conditions and construct efficient multiport model, which is easily and directly compatible with circuit simulators.
PAPR analysis of OFDM system using AI based multiple signal representation me...TELKOMNIKA JOURNAL
OFDM (orthogonal frequency division multiplexing) is widely used in 4th generation applications owing to its robustness in fading environments. The major issues with OFDM systems is the high PAPR (peak-to-average power ratio) of the transmitted signals, it leads to in and out of band distortion. SLM (selective mapping) and PTS (partial transmit sequence) are two key methods for PAPR reduction. Both the methods require exhaustive searching of phase factors to optimize the PAPR, these searches lead to high computational complexity. This paper discusses using optimization based PAPR reduction methods which an be used with PTS for the reduction of computational complexity and search space. In this paper we have analyzed PTS and SLM with particle swarm optimization (PSO), Artificial Bee Colony (ABC) and differential evolution (DE). PAPR and BER (bit error rate) comparison is done for both the cases.
A distributed ip based telecommunication system using sipIJCNCJournal
Voice over Internet Protocol (VoIP) technologies are integral to modern telecommunications because of
their advanced features, flexibility, and economic benefits. Internet Service Providers initially promoted
these technologies by providing low cost local and international calling. At present, there is also a great
deal of interest in using IP-based technologies to replace traditional small and large office telephone
systems that use traditional PBX’s (Private Branch eXchange). Unfortunately, the large majority of the
emerging VoIP based office telephone systems have followed the centralized design of traditional public
and private telephone systems in which all the intelligence in the system is at the core, with quite expensive
hardware and software components and appropriate redundancy for adequate levels of reliability. In this
paper, it is argued that a centralized model for an IP-based telecommunications system fails to exploit the
full capabilities of Internet-inspired communications and that, very simple, inexpensive, elegant and
flexible solutions are possible by deliberately avoiding the centralized approach. This paper describes the
design, philosophy and implementation of a prototype for a fully distributed IP-based Telecommunication
System (IPTS) that provides the essential feature set for office and home telecommunications, including IPbased
long-distance and local calling, and with the support for video as well as data and text. The
prototype system was implemented with an Internet-inspired distributed design using open source software,
with appropriate customizations and configurations.
An Optimal Software Framework for Parallel Computation of CRCIJCNCJournal
CRC is a common error detection method used in different areas such as information storage and data
communication. CRC depends on modulo-2 division by a predetermined divisor called the generator. In
this method, the transmitter divides the message by the generator and concatenates the calculated residue
to the message. CRC is not able to detect every kind of errors. The properties of the generator determine
the range of errors which are detectable in the receiver side. The division operation is currently performed
sequentially, so developing methods for parallel computation of the residue makes CRC suitable for
network protocols and software applications. This paper presents a novel software framework for parallel
computation of CRC using ODP polynomials.
Minimizing mobiles communication time using modified binary exponential backo...IJCNCJournal
The domain of wireless Local Area Networks (WLANs) is growing speedily as a consequence of
developments in digital communications technology. The early adopters of this technology have mainly
been vertical application that places a premium on the mobility offered by such systems. Examples of these
types of applications consist of stocking control in depot environments, point of sale terminals, and rental
car check-in. Furthermore to the mobility that becomes possible with wireless LANs; these systems have
also been used in environments where cable installation is expensive or impractical. Such environments
include manufacturing floors, trading floors on stock exchanges, conventions and trade shows, and historic
buildings. With the increasing propagation of wireless LANs comes the need for standardization so as to
allow interoperability for an increasingly mobile workforce. Despite all the advantages and facilities that
Wi-FI offers, there is still the delay problem that is due to many reasons that are introduced in details in
our case study which also presents the solutions and simulation that can reduce this delay for better
performance of the wireless networks
In this paper, three novel designs of broadband patch antenna are proposed. The first design propose
broadband slotted equilateral triangular patch antenna (ETPA) operating on frequency around 1800 MHz.
The second design propose broadband slotted right angle isosceles triangular patch antenna RAITPA operating on frequency around 2400 MHz. The third design proposes wideband V-Slotted and shorted edge ETPA antenna operating on frequency around 2400 MHz. The two powerful software HFSS and IE3D are used to simulate the proposed designs. Very good agreement between HFSS and IE3D software is obtained. The designs were chosen to fit modern wireless communication applications operate at Industrial Scientific Medical (ISM) bands such as Wireless local area networks (WLAN). Moreover, mounting the patch on thick substrate with loaded slot technique and loading the patch with a notch technique were used to enhance the bandwidth of those designs. Hence, large fractional bandwidth is obtained.
EFFECT OF OPERATING WAVELENGTHS AND DIFFERENT WEATHER CONDITIONS ON PERFORMAN...IJCNCJournal
Free Space Optical (FSO) communication is a very recent and emerging technology to establish broadband
wireless data transmission system using modulated optical beams. The adoption of FSO system is mainly
needed when any physical connection between the transmitter and receiver is practically impossible and
where high bandwidth data transmission is expected. The performance of FSO communication technology
is highly dependent on atmospheric attenuation which is related to the visibility of the different weather
conditions as well as operating wavelengths. This paper presents our study about the effect of visibility as
well as operating wavelengths on atmospheric attenuation in different weather conditions for point-to-point
free space optical link. Moreover, it also discusses the methodology to find out the optimum link distance
for point-to-point FSO link which will be operated in different weather conditions. It is found that,
atmospheric attenuation is changed with the change in weather condition as well as operating wavelengths.
An Ant Algorithm for Solving QoS Multicast Routing ProblemCSCJournals
Abstract: Many applications require send information from a source to multiple destinations through a communication network. To support these applications, it is necessary to determine a multicast tree of minimal cost to connect the source node to the destination nodes subject to delay constraints. Based on the Ant System algorithm, we present an ant algorithm to find the multicast tree that minimizes the total cost. In the proposed algorithm, the k shortest paths from the source node to the destination nodes are used for genotype representation. The expermintal results show that the algorithm can find optimal solution quickly and has a good scalability.
A Genetic Algorithm for Reliability Evaluation of a Stochastic-Flow Network w...CSCJournals
The paper presents a genetic algorithm to compute the reliability of a stochastic- flow network in which each arc or node has several capacitis and may fail. I.e. Calculate the system reliability such that the maximum flow is not less than a given demand. The algorithm is based on generating all lower boundary points for the given demand and than the system reliability can be calculated in terms of such points. The proposed algorithm can be used for a network with large number of nodes and links. Also, the paper investigates the problems that are found in the solutions that obtained by using other previous methods.
A genetic algorithm for constructing broadcast trees with cost and delay cons...IJCNCJournal
We refer to the problem of constructing broadcast trees with cost and delay constraints in the networks as a delay-constrained minimum spanning tree problem in directed networks. Hence it is necessary determining a spanning tree of minimal cost to connect the source node to all nodes subject to delay constraints on broadcast routing. In this paper, we proposed a genetic algorithm for solving broadcast routing by finding the low-cost broadcast tree with minimum cost and delay constraints. In this research we present a genetic algorithm to find the broadcast routing tree of a given network in terms of its links. The algorithm uses the connection matrix of the given network to find the spanning trees and considers the weights of the links to obtain the minimum spanning tree. Our proposed algorithm is able to find a better solution, fast convergence speed and high reliability. The scalability and the performance of the algorithm with increasing number of network nodes are also encouraging.
With the widespread of smart mobile devices and the
availability of many applications that provide maps, many programs
have spread to find the closest and fastest routes between
two points on the map. While the exactness and effectiveness of
best path depend on the traffic circumstances, the system needs to
add more parameters such as real traffic density and velocity in
road. In addition, because of the restricted resources of phone devices,
it is not reasonable to be used to calculate the exact optimal
solutions by some familiar deterministic algorithms, which are
usually used to find the shortest path with a map of reasonable
node number. To resolve this issue, this paper put forward to use
the genetic algorithm to reduce the computational time. The proposed
system use the genetic algorithm to find the shortest path
time with miscellaneous situations of real traffic conditions. The
genetic algorithm is clearly demonstrate excellent result when applied
on many types of map, especially when the number of nodes
increased.
SOLVING OPTIMAL COMPONENTS ASSIGNMENT PROBLEM FOR A MULTISTATE NETWORK USING ...ijmnct
Optimal components assignment problem subject to system reliability, total lead-time, and total cost constraints is studied in this paper. The problem is formulated as fuzzy linear problem using fuzzy membership functions. An approach based on genetic algorithm with fuzzy optimization to sole the presented problem. The optimal solution found by the proposed approach is characterized by maximum reliability, minimum total cost and minimum total lead-time. The proposed approach is tested on different examples taken from the literature to illustrate its efficiency in comparison with other previous methods.
SOLVING OPTIMAL COMPONENTS ASSIGNMENT PROBLEM FOR A MULTISTATE NETWORK USING ...ijmnct
Optimal components assignment problem subject to system reliability, total lead-time, and total cost
constraints is studied in this paper. The problem is formulated as fuzzy linear problem using fuzzy
membership functions. An approach based on genetic algorithm with fuzzy optimization to sole the
presented problem. The optimal solution found by the proposed approach is characterized by maximum
reliability, minimum total cost and minimum total lead-time. The proposed approach is tested on different
examples taken from the literature to illustrate its efficiency in comparison with other previous methods
Improving The Performance of Viterbi Decoder using Window System IJECEIAES
An efficient Viterbi decoder is introduced in this paper; it is called Viterbi decoder with window system. The simulation results, over Gaussian channels, are performed from rate 1/2, 1/3 and 2/3 joined to TCM encoder with memory in order of 2, 3. These results show that the proposed scheme outperforms the classical Viterbi by a gain of 1 dB. On the other hand, we propose a function called RSCPOLY2TRELLIS, for recursive systematic convolutional (RSC) encoder which creates the trellis structure of a recursive systematic convolutional encoder from the matrix “H”. Moreover, we present a comparison between the decoding algorithms of the TCM encoder like Viterbi soft and hard, and the variants of the MAP decoder known as BCJR or forward-backward algorithm which is very performant in decoding TCM, but depends on the size of the code, the memory, and the CPU requirements of the application.
Design and Performance Analysis of Convolutional Encoder and Viterbi Decoder ...IJERA Editor
In digital communication forward error correction methods have a great practical importance when channel is
noisy. Convolutional error correction code can correct both type of errors random and burst. Convolution
encoding has been used in digital communication systems including deep space communication and wireless
communication. The error correction capability of convolutional code depends on code rate and constraint
length. The low code rate and high constraint length has more error correction capabilities but that also
introduce large overhead. This paper introduces convolutional encoders for various constraint lengths. By
increasing the constraint length the error correction capability can be increased. The performance and error
correction also depends on the selection of generator polynomial. This paper also introduces a good generator
polynomial which has high performance and error correction capabilities.
Investigation on the Pattern Synthesis of Subarray Weights for Low EMI Applic...IOSRJECE
In modern radar applications, it is frequently required to produce sum and difference patterns sequentially. The sum pattern amplitude coefficients are obtained by using Dolph-Chebyshev synthesis method where as the difference pattern excitation coefficients will be optimized in this present work. For this purpose optimal group weights will be introduced to the different array elements to obtain any type of beam depending on the application. Optimization of excitation to the array elements is the main objective so in this process a subarray configuration is adopted. However, Differential Evolution Algorithm is applied for optimization method. The proposed method is reliable and accurate. It is superior to other methods in terms of convergence speed and robustness. Numerical and simulation results are presented.
An Algorithm for Computing Average Packet DelayCSCJournals
Average Packet delay is considered as a vital performance measure for a computer-communication network especially in the network designing problem. Average Packet delay evaluation depends on two main parts: the first part is the capacity of each link in the network, the last one is the flow of each link. The capacity of each link is assumed to be fixed but the flow of each link is computed by using routing algorithms and the traffic requirement matrix. The paper presents an algorithm based on FLOYD’s routing algorithm to calculate the flow of each link and then we can compute the average packet delay.
Routing in Wireless Mesh Networks: Two Soft Computing Based Approachesijmnct
Due to dynamic network conditions, routing is the most critical part in WMNs and needs to be optimised.
The routing strategies developed for WMNs must be efficient to make it an operationally self configurable
network. Thus we need to resort to near shortest path evaluation. This lays down the requirement of some
soft computing approaches such that a near shortest path is available in an affordable computing time. This
paper proposes a Fuzzy Logic based integrated cost measure in terms of delay, throughput and jitter.
Based upon this distance (cost) between two adjacent nodes we evaluate minimal shortest path that updates
routing tables. We apply two recent soft computing approaches namely Big Bang Big Crunch (BB-BC) and
Biogeography Based Optimization (BBO) approaches to enumerate shortest or near short paths. BB-BC
theory is related with the evolution of the universe whereas BBO is inspired by dynamical equilibrium in
the number of species on an island. Both the algorithms have low computational time and high convergence
speed. Simulation results show that the proposed routing algorithms find the optimal shortest path taking
into account three most important parameters of network dynamics. It has been further observed that for
the shortest path problem BB-BC outperforms BBO in terms of speed and percent error between the
evaluated minimal path and the actual shortest path.
Neuro genetic key based recursive modulo 2 substitution using mutated charact...ijcsity
In this paper, a neural genetic key based technique for encryption (NGKRMSMC) has been proposed
through recursive modulo
-
2 substitution using mutated character code generation for online wireless
communication of data/information.
Both sender and receive
r get synchronized based on their final output
.
The length of the key depends on the number of input and output neurons. Coordinated matching weight
vectors assist to generate chromosomes pool. Genetic secret key is obtained using fitness function, which i
s
the hamming distance between two chromosomes. Crossover and mutation are used to add elitism of
chromosomes.
At first
mutated character code table
based encryption strategy get perform on plain text.
.
Then the intermediate cipher text is yet again encry
pted through recursive positional modulo
-
2 substitution
technique to from next level encrypted text. This 2nd level intermediate cipher text is again encrypted to
form the final cipher text through chaining and cascaded xoring of neuro genetic key with the
identical
length intermediate cipher text block.
Receiver will perform same symmetric operation to get back the plain
text using identical key
Performance Analysis of Mtpr Routing Protocol in Power Deficient Nodepijans
Power conservation in Mobile Ad hoc Network (MANET) is a major challenge even today for researchers.
To conserve it various power aware routing protocols have been proposed. These protocols do not take into
consideration the residual power left in nodes. To find the impact of the same a simulator was designed in
MATLAB-7.01. The routing protocol used in our simulation is Minimum Total Power Routing (MTPR) and
different performance metrics such as path optimality, throughput and hop count were recorded in
presence and absence of power scarce node. The result shows significant impact of power scarce node on
MANET performance.
Vehicle Ad Hoc Networks (VANETs) have become a viable technology to improve traffic flow and safety on the roads. Due to its effectiveness and scalability, the Wingsuit Search-based Optimised Link State Routing Protocol (WS-OLSR) is frequently used for data distribution in VANETs. However, the selection of MultiPoint Relays (MPRs) plays a pivotal role in WS-OLSR's performance. This paper presents an improved MPR selection algorithm tailored to WS-OLSR, designed to enhance the overall routing efficiency and reduce overhead. The analysis found that the current OLSR protocol has problems such as redundancy of HELLO and TC message packets or failure to update routing information in time, so a WS-OLSR routing protocol based on improved-MPR selection algorithm was proposed. Firstly, factors such as node mobility and link changes are comprehensively considered to reflect network topology changes, and the broadcast cycle of node HELLO messages is controlled through topology changes. Secondly, a new MPR selection algorithm is proposed, considering link stability issues and nodes. Finally, evaluate its effectiveness in terms of packet delivery ratio, end-to-end delay, and control message overhead. Simulation results demonstrate the superior performance of our improved MR selection algorithm when compared to traditional approaches.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
May_2024 Top 10 Read Articles in Computer Networks & Communications.pdfIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
A Topology Control Algorithm Taking into Account Energy and Quality of Transm...IJCNCJournal
The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.
Multi-Server user Authentication Scheme for Privacy Preservation with Fuzzy C...IJCNCJournal
The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.
Advanced Privacy Scheme to Improve Road Safety in Smart Transportation SystemsIJCNCJournal
In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.
April 2024 - Top 10 Read Articles in Computer Networks & CommunicationsIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
DEF: Deep Ensemble Neural Network Classifier for Android Malware DetectionIJCNCJournal
Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.
High Performance NMF Based Intrusion Detection System for Big Data IOT TrafficIJCNCJournal
With the emergence of smart devices and the Internet of Things (IoT), millions of users connected to the network produce massive network traffic datasets. These vast datasets of network traffic, Big Data are challenging to store, deal with and analyse using a single computer. In this paper we developed parallel implementation using a High Performance Computer (HPC) for the Non-Negative Matrix Factorization technique as an engine for an Intrusion Detection System (HPC-NMF-IDS). The large IoT traffic datasets of order of millions samples are distributed evenly on all the computing cores for both storage and speedup purpose. The distribution of computing tasks involved in the Matrix Factorization takes into account the reduction of the communication cost between the computing cores. The experiments we conducted on the proposed HPC-IDS-NMF give better results than the traditional ML-based intrusion detection systems. We could train the HPC model with datasets of one million samples in only 31 seconds instead of the 40 minutes using one processor), that is a speed up of 87 times. Moreover, we have got an excellent detection accuracy rate of 98% for KDD dataset.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
A Topology Control Algorithm Taking into Account Energy and Quality of Transm...IJCNCJournal
The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.
Multi-Server user Authentication Scheme for Privacy Preservation with Fuzzy C...IJCNCJournal
The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.
Advanced Privacy Scheme to Improve Road Safety in Smart Transportation SystemsIJCNCJournal
In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.
DEF: Deep Ensemble Neural Network Classifier for Android Malware DetectionIJCNCJournal
Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.
High Performance NMF based Intrusion Detection System for Big Data IoT TrafficIJCNCJournal
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IoT Guardian: A Novel Feature Discovery and Cooperative Game Theory Empowered...IJCNCJournal
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Cyber intrusion attacks increasingly target the Internet of Things (IoT) ecosystem, exploiting vulnerable devices and networks. Malicious activities must be identified early to minimize damage and mitigate threats. Using actual benign and attack traffic from the CICIoT2023 dataset, this WORK aims to evaluate and benchmark machine-learning techniques for IoT intrusion detection. There are four main phases to the system. First, the CICIoT2023 dataset is refined to remove irrelevant features and clean up missing and duplicate data. The second phase employs statistical models and artificial intelligence to discover novel features. The most significant features are then selected in the third phase based on cooperative game theory. Using the original CICIoT2023 dataset and a dataset containing only novel features, we train and evaluate a variety of machine learning classifiers. On the original dataset, Random Forest achieved the highest accuracy of 99%. Still, with novel features, Random Forest's performance dropped only slightly (96%) while other models achieved significantly lower accuracy. As a whole, the work contributes substantial contributions to tailored feature engineering, feature selection, and rigorous benchmarking of IoT intrusion detection techniques. IoT networks and devices face continuously evolving threats, making it necessary to develop robust intrusion detection systems.
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Enhancing Traffic Routing Inside a Network through IoT Technology & Network C...IJCNCJournal
IoT networking uses real items as stationary or mobile nodes. Mobile nodes complicate networking. Internet of Things (IoT) networks have a lot of control overhead messages because devices are mobile. These signals are generated by the constant flow of control data as such device identity, geographical positioning, node mobility, device configuration, and others. Network clustering is a popular overhead communication management method. Many cluster-based routing methods have been developed to address system restrictions. Node clustering based on the Internet of Things (IoT) protocol, may be used to cluster all network nodes according to predefined criteria. Each cluster will have a Smart Designated Node. SDN cluster management is efficient. Many intelligent nodes remain in the network. The network design spreads these signals. This paper presents an intelligent and responsive routing approach for clustered nodes in IoT networks. An existing method builds a new sub-area clustered topology. The Nodes Clustering Based on the Internet of Things (NCIoT) method improves message transmission between any two nodes. This will facilitate the secure and reliable interchange of healthcare data between professionals and patients. NCIoT is a system that organizes nodes in the Internet of Things (IoT) by grouping them together based on their proximity. It also picks SDN routes for these nodes. This approach involves selecting one option from a range of choices and preparing for likely outcomes problem addressing limitations on activities is a primary focus during the review process. Predictive inquiry employs the process of analyzing data to forecast and anticipate future events. This document provides an explanation of compact units. The Predictive Inquiry Small Packets (PISP) improved its backup system and partnered with SDN to establish a routing information table for each intelligent node, resulting in higher routing performance. Both principal and secondary roads are available for use. The simulation findings indicate that NCIoT algorithms outperform CBR protocols. Enhancements lead to a substantial 78% boost in network performance. In addition, the end-to-end latency dropped by 12.5%. The PISP methodology produces 5.9% more inquiry packets compared to alternative approaches. The algorithms are constructed and evaluated against academic ones.
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Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
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In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
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Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
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Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
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1. International Journal of Computer Networks & Communications (IJCNC) Vol.7, No.4, July 2015
DOI : 10.5121/ijcnc.2015.7405 75
A GENETIC ALGORITHM TO SOLVE THE
MINIMUM-COST PATHS TREE PROBLEM
Ahmed Y. Hamed1
and M. R. Hassan2
1
College of Applied Studies and Community Services, University of Dammam,
KSA.
2
Computer Science Branch, Mathematics Department, Faculty of Science, Aswan
University, Egypt.
ABSTRACT
One of the important steps in routing is to find a feasible path based on the state information. In order to
support real-time multimedia applications, the feasible path that satisfies one or more constraints has to be
computed within a very short time. Therefore, the paper presents a genetic algorithm to solve the paths tree
problem subject to cost constraints. The objective of the algorithm is to find the set of edges connecting all
nodes such that the sum of the edge costs from the source (root) to each node is minimized. I.e. the path
from the root to each node must be a minimum cost path connecting them. The algorithm has been applied
on two sample networks, the first network with eight nodes, and the last one with eleven nodes to illustrate
its efficiency.
KEYWORDS
Computer networks; Minimum-cost paths tree; Genetic algorithms.
1. INTRODUCTION
The shortest paths tree rooted at vertex s is a spanning tree T of G, such that the path distance
from root v to any other vertex u in T is the shortest path distance from v to u in G,[1]. In the case
of single link failure, [2], proposed an algorithm to solve the optimal shortest paths tree. When
considering multicast tree, [3], the authors presented an algorithm to find the Shortest Best Path
Tree (SBPT). Based on labeling techniques, Ziliaskopoulos et al. in [4], proposed an algorithm to
solve the shortest path trees. Also, The shortest paths tree problem has been solved by an efficient
modified continued pulse coupled neural network (MCPCNN) model, [5].
Heuristic and approximate algorithms for multi-constrained routing (MCR) are not effective in
dynamic network environment for real-time applications when the state information of the
network is out of date, [6]. The authors in [6] presented a genetic algorithm to solve the MCR
problem subject to transmission delay and transmission success ratio. Younes in [7] proposed a
genetic algorithm to determine the k shortest paths with bandwidth constraints from a single
source node to multiple destinations nodes. Liu et al. in [8] presented an oriented spanning tree
(OST) based genetic algorithm (GA) for solving both the multi-criteria shortest path problem
(MSPP) and the multi-criteria constrained shortest path problems (MCSPP). Also, in [9] the
genetic algorithm is used to find the low-cost multicasting tree with bandwidth and delay
constraints.
The paper presents a genetic algorithm to solve the paths tree problem under cost constraint. The
algorithm reads the connection matrix and the cost matrix of a given network. Also, given the
source (root) node s, then the genetic operations are executed to search the minimum cost paths
that construct the minimum cost paths tree rooted at the source node s.
2. International Journal of Computer Networks & Communications (IJCNC) Vol.7, No.4, July 2015
76
The rest of the paper is organized as follows: Section 2 presents notations. The problem
description in section 3. The proposed GA and its components are given in section 4. Section 5
provides the pseudo code of the entire GA. Section 6 shows the illustrative examples. Finally,
section 7 presents conclusions.
2. Notations
G
N
E
eij
ce
M
CM
np
Ts
A network graph.
The number of nodes in G.
The number of edges in G.
An edge between node i and node j in G.
The cost of an edge e.
The connection matrix of the given network.
The cost matrix of the given network.
The number of paths from node s to t
The shortest path rooted at node s
3. THE PROBLEM DESCRIPTION
Given a specified vertex s. Let Pi
(s, t) be a path number i from s to t. Let Ci
(P(s, t)) be the cost of the
path Pi
(s, t), i = 1,2, …, np. The path Pk
(s, t) has a minimum cost among all the (s, t)-paths if:
Where
Therefore, the minimum-cost paths tree Ts is the collection of minimum cost paths from the
source (root) node s to the destination nodes ti. I.e.
The presented method in this paper depend on reading both the connection and cost matrices of a
given network, and then find the minimum-cost paths tree rooted at the source node.
Consider the following network with five nodes, shown in Figure 1.
3. International Journal of Computer Networks & Communications (IJCNC) Vol.7, No.4, July 2015
77
Figure 1. Five nodes network.
The connection matrix (a square matrix of dimension N x N that represents a connection between
each node-pairs) of the Figure 1 network is:
Figure 2. The connection matrix of network in Figure 1
The cost matrix CM for the network shown in Figure 1 is in the following form:
Figure 3. The cost matrix network in Figure 1.
In Figure 4, we show that the minimum-cost paths tree rooted at node 1 with the minimum cost
equals to 23.
Figure 4. Minimum-cost paths tree rooted at node 1
4. International Journal of Computer Networks & Communications (IJCNC) Vol.7, No.4, July 2015
78
4. THE PROPOSED GENETIC ALGORITHM (GA)
In the proposed GA, each candidate path is represented by a binary string with length N that can
be used as a chromosome. Each element of the chromosome represents a node in the network
topology. So, for a network of N nodes, there are N string components in each candidate solution
x. Each chromosome must contain at least two none zero elements.
For example if N = 8, the path of Figure 5 is represented as a chromosome as shown in Figure 6.
Figure
Figure 5. A candidate Path.
1 2 3 4 5 6 7 8
1 0 1 1 0 0 0 1
Figure 6. The chromosome corresponding to the path given in Figure 2.
In the following subsections we give an explanation of different components (operations) of the
presented genetic algorithm.
4.1. Initial Population
The generated chromosome in initial population must contain at least two none zero elements to
be a real candidate path. The following steps show how to generate pop_size chromosomes of the
initial population:
1. Randomly generate a chromosome x.
2. Check if x represents a real candidate path, i.e. contains at least two non zero elements.
3. Repeat steps 1 to 2 to generate pop_size chromosomes.
4.2. The objective function
The cost of the candidate path is used as objective function to compare the solutions and find the
best one. The cost of the candidate path is calculated when it satisfies the following conditions:
The chromosome must contain at least two none zero elements.
The chromosome contains a connected candidate path. I.e. each node in the path connects
at least one another.
5. International Journal of Computer Networks & Communications (IJCNC) Vol.7, No.4, July 2015
79
4.3. Genetic Crossover Operation
In the proposed GA, we use the single cut point crossover to breed a new offspring from two
parents. The crossover operation will be performed if the crossover ratio (Pc=0.90) is verified.
The cut point is randomly selected. Figure 7 shows the crossover operation.
Cut point
Parent 1 1 1 0 1 1 0 0
Child 1 1 1 0 1 1 0 1
Parent 1 0 1 0 0 1 0 1
Figure 7. Example of the crossover operation.
4.4. Genetic Mutation Operation
The mutation operation is performed on bit-by-bit basis. In the proposed approach, the mutation
operation will be performed if the mutation ratio (Pm) is verified. The Pm in this approach is
chosen experimentally to be 0.02. The point to be mutated is selected randomly. The offspring
generated by mutation is shown in Figure 8.
1 0 1 1 0 0 0 1
1 1 1 0 0 0 0 0
Figure 8. An example of the mutation operation.
5. THE ENTIRE ALGORITHM
The following pseudocode illustrates the use of our different components of the GA algorithm to
generate the minimum-cost paths tree of a given network.
Algorithm Find minimum-cost paths tree
Input : Set the parameters: pop_size, max_gen, Pm, Pc.
Output : Minimum-cost paths tree
1. Set j = 2, the destination node.
2. Generate the initial population according to the steps in Section 0.
3. gen←1.
4. While (gen < = max_gen) do {
5. P ← 1
6. While (P <= pop_size) do {
7. Apply Genetic operations to obtain new population
7.1. Apply crossover according to Pc parameter (Pc >=0.90) as described in section 4.3.
7.2. Apply Mutation as shown in section 4.4.
7.3. Compute the total cost of the candidate path according to Section 3.
8. P ← P+1.
9. }
10. Set gen =gen + 1
6. International Journal of Computer Networks & Communications (IJCNC) Vol.7, No.4, July 2015
80
11. if gen > max_gen then stop
12. }
13. Save the candidate path for the destination j that has the minimum cost (the shortest path
between the root node and the destination node j).
14. Set j = j + 1
15. If j <= N Goto Step 2, otherwise stop the entire algorithm and print out the minimum-cost
paths tree.
5. EXPERIMENTAL RESULTS
The proposed algorithm is implemented using Borland C++ Ver. 5.5 and the initial values of the
parameters are: population size (pop-size=20), maximum generation (max_gen=50), Pc=0.90,
and Pm=0.02. The technique reads both the connection and cost matrices of the given network.
Then it generates the shortest paths tree of the network that posses the minimum cost. Two
Examples are used to test and validate the proposed technique.
5.1 Eight nodes example
In this section, we illustrate the results of applying the presented GA on an eight nodes
network example, as shown in Figure 9. The final output o the GA is shown in Table 1.
Figure 10 shows the shortest paths tree rooted at node 1.
Figure 9. Eight nodes network.
Table 1: The final output of the GA.
The chromosome The shortest paths set The cost
(1 1 0 0 0 0 0 0) {1, 2} 6
(1 0 1 0 0 0 0 0) {1, 3} 5
(1 0 1 1 0 0 0 0) {1, 3, 4} 9
(1 0 0 0 1 0 0 0) {1, 5} 4
(1 0 0 0 0 1 0 0) {1, 6} 6
(1 0 0 0 0 1 1 0) {1, 6, 7} 10
(1 0 1 1 0 0 0 1) {1, 3, 4, 8} 13
7. International Journal of Computer Networks & Communications (IJCNC) Vol.7, No.4, July 2015
81
Figure 10: The shortest paths tree
6.2. Eleven nodes example
In this section, the GA is applied on eleven nodes example as shown in Figure 11. The final
output of the GA is shown in Table 2. Figure 12 shows the minimum-cost paths tree rooted at
node 1.
Figure 11: Eleven nodes network.
8. International Journal of Computer Networks & Communications (IJCNC) Vol.7, No.4, July 2015
82
Table 2. The final output of the GA.
The chromosome The shortest paths set The cost
(1 1 0 0 0 0 0 0 0 0 0) {1, 2} 8
(1 0 1 0 0 0 0 0 0 0 1) {1, 11, 3} 8
(1 0 1 1 0 0 0 0 0 0 1) {1, 11, 3, 4} 17
(1 1 0 0 1 0 0 0 0 0 0) {1, 2, 5} 10
(1 0 0 0 0 1 1 0 0 0 0) {1, 7, 6} 17
(1 0 0 0 0 1 0 0 0 0 0) {1, 7} 9
(1 0 0 0 0 0 0 1 1 0 0) {1, 9, 8} 9
(1 0 0 0 0 0 0 0 1 0 0) {1, 9} 6
(1 0 0 0 0 0 0 0 0 1 1) {1, 11, 10} 11
(1 0 0 0 0 0 0 0 0 0 1) {1, 11} 3
Figure 12: The minimum-cost paths tree rooted at node 1.
6.3. Sixteen nodes example
Also, the GA is applied on sixteen nodes example as shown in Figure 13. The final output of the
GA is shown in Table 3. Figure 14 shows the minimum-cost paths tree rooted at node 1.
10. International Journal of Computer Networks & Communications (IJCNC) Vol.7, No.4, July 2015
84
Figure 14: The minimum-cost paths tree rooted at node 1.
7. CONCLUSIONS
The paper addressed the minimum-cost paths tree problem and presented an efficient GA to solve
this problem. The algorithm reads both the connection and cost matrices of a given network, then
search the minimum-cost paths that construct the minimum-cost paths tree rooted at a given node
s. The GA has been applied on two examples, the results proved that the efficiency of the
proposed GA. For the future work, the GA can be extended to solve multi-constrained paths tree
problem.
References
[1] Pierre Hansen and Maolin Zheng, “Shortest shortest path trees of a network”, Discrete Applied
Mathematics, Vol. 65, Issues 1–3, March 1996, pp.275–284.
[2] Yueping Li, Zhe Nie and Xiaohong Zhou, “Finding the Optimal Shortest Path Tree with Respect to
Single Link Failure Recovery”, Fourth International Conference on Networked Computing and
Advanced Information Management, 2008, NCM '08, Vol. 1, pp. 412 – 415.
[3] Hiroshi Fujinoki and Kenneth J. Christensen, “The New Shortest Best Path Tree (SBPT) Algorithm
for Dynamic Multicast Trees”, Conference onLocal Computer Networks, 1999. LCN '99. pp. 201-
211.
[4] Athanasios K. Ziliaskopoulos, Fotios D. Mandanas, and Hani S. Mahmassani,”An extension of
labeling techniques for finding shortest path trees”, European Journal of Operational Research, Vol.
198 (2009), pp. 63–72.
[5] Hong Qua, Simon X. Yang, Zhang Yi, and Xiaobin Wanga, “A novel neural network method for
shortest path tree computation”, Applied Soft Computing, Vol. 12 (2012), pp. 3246–3259.
[6] Ting Lu and Jie Zhu, “A genetic algorithm for finding a path subject to two constraints”, Applied Soft
Computing, Vol. 13, Issue 2, February 2013, pp. 891-898.
[7] A. Younes , “A genetic algorithm for finding the k shortest paths in a network”, Egyptian Informatics
Journal, Vol. 11, Issue 2, December 2010, pp. 75-79.
[8 Linzhong Liu, Haibo Mu, Xinfeng Yang, Ruichun He, and Yinzhen LiAn, “oriented spanning tree
based genetic algorithm for multi-criteria shortest path problems”, Applied Soft Computing, Vol. 12,
Issue 1, January 2012, pp. 506-515.
[9] A. Younes, “Multicast routing with bandwidth and delay constraints based on genetic algorithms”,
Egyptian Informatics Journal, Vol. 12, Issue 2, July 2011, pp. 107-114.
11. International Journal of Computer Networks & Communications (IJCNC) Vol.7, No.4, July 2015
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AUTHORS
Ahmed Younes Hamed received his PhD degree in Sept. 1996 from South Valley
University, Egypt. His research interests include Artificial Intelligence and genetic
algorithms; specifically in the area of computer networks. Recently, he has started conducting
a research in the area of Image Processing. Currently, he works as an Associate Professor in
University of Dammam, KSA. Younes always publishes the outcome of his research in
international journals and conferences.
Moatamad Hassan holds a PhD of Computer Science in June 2006 from Aswan University,
Faculty of Science, Aswan, Egypt. He is currently an assistant professor at the Department of
Mathematics, Computer Science Branch, Faculty of Science, Aswan University, Aswan,
Egypt. His work deals with QoS, Reliability, and Computer Network Design problems.