Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045342
M. Lalitha, T. Janardhan, R. Mohan
In recent years the Double-Fed Induction Generator (DFIG) gaining more popular due to their variable speed and variable pitch control. A dynamic Solid oxide fuel cell (SOFC) is integrated with Double fed Induction Generator (DFIG), due to their fluctuating nature of wind energy. This paper presents a simulation of SOFC fuel cell integrated with a doubly fed induction generator to maintain grid voltage constant 440 V and 50 Hz. Existing literature used PI controller based vector control technique for the control of DFIG. In this work, fuzzy logic controller is proposed to decrease total harmonic distortion in grid current. The performance of the system for sudden load changes with PI control and proposed control technique has been obtained and compared, by using MATLAB SIMULINK.
{"title":"Fuzzy logic based wind energy conversion system with Solid oxide fuel cell","authors":"M. Lalitha, T. Janardhan, R. Mohan","doi":"10.1109/ICHPCA.2014.7045342","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045342","url":null,"abstract":"In recent years the Double-Fed Induction Generator (DFIG) gaining more popular due to their variable speed and variable pitch control. A dynamic Solid oxide fuel cell (SOFC) is integrated with Double fed Induction Generator (DFIG), due to their fluctuating nature of wind energy. This paper presents a simulation of SOFC fuel cell integrated with a doubly fed induction generator to maintain grid voltage constant 440 V and 50 Hz. Existing literature used PI controller based vector control technique for the control of DFIG. In this work, fuzzy logic controller is proposed to decrease total harmonic distortion in grid current. The performance of the system for sudden load changes with PI control and proposed control technique has been obtained and compared, by using MATLAB SIMULINK.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"65 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129600653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045361
C. Subramaniam, R. V. Selvakarthik, M. Karthikeyan, K. Abinesh Kumar, P. Giridhara Madhavan
The objective of the research work is to propose a trigger-action-reaction (TAR) based impact analysis model with the outcome due to Artificial Energy Drinks (AED) on Indian youth. The AED causes a drastic behavioural changes leading to potential health risks in India and the studies suggest that young people or college students are therefore vulnerable to increased problems from ingesting these products. The young community is more likely to take risks than adults and to suffer high rates of alcohol problems, including alcohol-related traffic accidents, violence, sexual assault, and suicide as per the studies. The reaction induces faster metabolism in youth by AEDs resulting to uncontrollable emotional outbursts leading to different health and legal problems. A parallel action reaction based impact analysis with number of AEDs sold out in India that results in criminal activities due to massive consumption of AEDs by the society. A formal model of trigger-action-reaction is applied and validated by multi-core programming using CUDA.
{"title":"Trigger action reaction model in high performance computing for impact analysis due to Artificial Energy Drinks","authors":"C. Subramaniam, R. V. Selvakarthik, M. Karthikeyan, K. Abinesh Kumar, P. Giridhara Madhavan","doi":"10.1109/ICHPCA.2014.7045361","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045361","url":null,"abstract":"The objective of the research work is to propose a trigger-action-reaction (TAR) based impact analysis model with the outcome due to Artificial Energy Drinks (AED) on Indian youth. The AED causes a drastic behavioural changes leading to potential health risks in India and the studies suggest that young people or college students are therefore vulnerable to increased problems from ingesting these products. The young community is more likely to take risks than adults and to suffer high rates of alcohol problems, including alcohol-related traffic accidents, violence, sexual assault, and suicide as per the studies. The reaction induces faster metabolism in youth by AEDs resulting to uncontrollable emotional outbursts leading to different health and legal problems. A parallel action reaction based impact analysis with number of AEDs sold out in India that results in criminal activities due to massive consumption of AEDs by the society. A formal model of trigger-action-reaction is applied and validated by multi-core programming using CUDA.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129033427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045344
Neha Sharma, Sujata, G. Purohit
Regression testing is an expensive process. A number of methodologies of regression testing are used to improve its effectiveness. These are retest all, test case selection, test case reduction and test case prioritization. Retest all technique involves re-execution of all available test suites, which are critical moreover cost effective. In order to increase efficiency, test case prioritization is being utilized for rearranging the test cases. A number of algorithms has been stated in the literature survey such as Greedy Algorithms and Metaheuristic search algorithms. A simple greedy algorithm focuses on test case prioritization but results in less efficient manner, due to which researches moved towards the additional greedy and 2-Optimal algorithms. Forthcoming metaheuristic search technique (Hill climbing and Genetic Algorithm) produces a much better solution to the test case prioritization problem. It implements stochastic optimization while dealing with problem concern. The genetic algorithm is an evolutionary algorithm which gives an exact mathematical fitness value for the test cases on which prioritization is done. This paper focuses on the comparison of metaheuristic genetic algorithm with other algorithms and proves the efficiency of genetic algorithm over the remaining ones.
{"title":"Test case prioritization techniques “an empirical study”","authors":"Neha Sharma, Sujata, G. Purohit","doi":"10.1109/ICHPCA.2014.7045344","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045344","url":null,"abstract":"Regression testing is an expensive process. A number of methodologies of regression testing are used to improve its effectiveness. These are retest all, test case selection, test case reduction and test case prioritization. Retest all technique involves re-execution of all available test suites, which are critical moreover cost effective. In order to increase efficiency, test case prioritization is being utilized for rearranging the test cases. A number of algorithms has been stated in the literature survey such as Greedy Algorithms and Metaheuristic search algorithms. A simple greedy algorithm focuses on test case prioritization but results in less efficient manner, due to which researches moved towards the additional greedy and 2-Optimal algorithms. Forthcoming metaheuristic search technique (Hill climbing and Genetic Algorithm) produces a much better solution to the test case prioritization problem. It implements stochastic optimization while dealing with problem concern. The genetic algorithm is an evolutionary algorithm which gives an exact mathematical fitness value for the test cases on which prioritization is done. This paper focuses on the comparison of metaheuristic genetic algorithm with other algorithms and proves the efficiency of genetic algorithm over the remaining ones.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114598782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045346
Dwaipayan Chakraborty, S. Saha, Oindrilla Dutta
Ensemblelearning of classifier has been a hot topic in pattern recognition problems for the last twenty years. This is because standalone classifier does not improve the performance when the dataset suffers from class imbalance.Ensemble learning is generally based on boosting and bagging techniques. Boostingcombines multiple classifiers of the same type, trained with weighted sample sets. Our aim is to improve the general boosting algorithm by usingdiversekinds of classifiers to build the ensemble of classifiers. Two different kinds of classifier - BP-MLP and RBFNN are considered for constructing the initial ensemble in our algorithm. Thestrategy is to assign an adaptive weight to the different types of classifiers based on their individual performancein order toboost a particular kind of classifier amongst the above two. Benchmark datasets from UCI repository are used for analysis which confirm that our method outperforms single type of learner based boosting.
{"title":"Weighted bag hybrid multiple classifier machine for boosting prediction accuracy","authors":"Dwaipayan Chakraborty, S. Saha, Oindrilla Dutta","doi":"10.1109/ICHPCA.2014.7045346","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045346","url":null,"abstract":"Ensemblelearning of classifier has been a hot topic in pattern recognition problems for the last twenty years. This is because standalone classifier does not improve the performance when the dataset suffers from class imbalance.Ensemble learning is generally based on boosting and bagging techniques. Boostingcombines multiple classifiers of the same type, trained with weighted sample sets. Our aim is to improve the general boosting algorithm by usingdiversekinds of classifiers to build the ensemble of classifiers. Two different kinds of classifier - BP-MLP and RBFNN are considered for constructing the initial ensemble in our algorithm. Thestrategy is to assign an adaptive weight to the different types of classifiers based on their individual performancein order toboost a particular kind of classifier amongst the above two. Benchmark datasets from UCI repository are used for analysis which confirm that our method outperforms single type of learner based boosting.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120945421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045321
Bhabani Sankar Samantray, Debananda Kanhar
A large number of algorithms have been developed for solving large dimension matrix multiplication through parallel computation. Lots of algorithms have been developed keeping performance matrices such as speed up, efficiency, isoefficiency etc. in linear order. We have compared the performance of simple block checkerboard partitioning algorithm with cannon's algorithm over 2D mesh topology in HPC Maverick (Rocks 5.4) by taking the mathematical problem matrix multiplication. Till the date not any of the algorithms clearly claimed to be superior then the others. It seems to be advantageous to partition matrix into blocks for multiplying on the 2D Mesh.
{"title":"Implementation of dense matrix multiplication on 2D mesh","authors":"Bhabani Sankar Samantray, Debananda Kanhar","doi":"10.1109/ICHPCA.2014.7045321","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045321","url":null,"abstract":"A large number of algorithms have been developed for solving large dimension matrix multiplication through parallel computation. Lots of algorithms have been developed keeping performance matrices such as speed up, efficiency, isoefficiency etc. in linear order. We have compared the performance of simple block checkerboard partitioning algorithm with cannon's algorithm over 2D mesh topology in HPC Maverick (Rocks 5.4) by taking the mathematical problem matrix multiplication. Till the date not any of the algorithms clearly claimed to be superior then the others. It seems to be advantageous to partition matrix into blocks for multiplying on the 2D Mesh.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116826654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045339
Mahesh Jangid, S. Srivastava
This manuscript is focus on the utilization of object detection algorithm GLAC (Gradient Local Auto-Correlation) for the handwritten character recognition (HCR) problem. HOG and SIFT are already used in this (HCR) field except GLAC which produced good results than HOG and SIFT for object detection problem like human in images, pedestrian detection and image patch matching. This paper utilized GLAC algorithm to recognize the handwritten Devanagari characters. GLAC applied on two handwritten Devanagari databases, ISIDCHAR and V2DMDCHAR. The images of databases are also normalized with and without preserving aspect ratio. Using GLAC method and SVM classifier, the best results obtained on ISIDCHAR and V2DMDCHAR are 93.21%, 95.21 % respectively that justified the utilization of GLAC algorithm for character recognition problem.
本文主要研究目标检测算法GLAC (Gradient Local Auto-Correlation，梯度局部自相关)在手写字符识别中的应用。除了GLAC在图像中人、行人检测和图像补丁匹配等目标检测问题上取得了比HOG和SIFT更好的效果外，HOG和SIFT已经应用于该(HCR)领域。本文利用GLAC算法对手写体德文汉字进行识别。GLAC应用于两个手写Devanagari数据库，ISIDCHAR和V2DMDCHAR。同时对数据库图像进行了保留宽高比和不保留宽高比的归一化处理。使用GLAC方法和SVM分类器，在ISIDCHAR和V2DMDCHAR上获得的最佳识别率分别为93.21%和95.21%，证明了GLAC算法用于字符识别问题的合理性。
{"title":"Gradient Local Auto-Correlation for handwritten Devanagari character recognition","authors":"Mahesh Jangid, S. Srivastava","doi":"10.1109/ICHPCA.2014.7045339","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045339","url":null,"abstract":"This manuscript is focus on the utilization of object detection algorithm GLAC (Gradient Local Auto-Correlation) for the handwritten character recognition (HCR) problem. HOG and SIFT are already used in this (HCR) field except GLAC which produced good results than HOG and SIFT for object detection problem like human in images, pedestrian detection and image patch matching. This paper utilized GLAC algorithm to recognize the handwritten Devanagari characters. GLAC applied on two handwritten Devanagari databases, ISIDCHAR and V2DMDCHAR. The images of databases are also normalized with and without preserving aspect ratio. Using GLAC method and SVM classifier, the best results obtained on ISIDCHAR and V2DMDCHAR are 93.21%, 95.21 % respectively that justified the utilization of GLAC algorithm for character recognition problem.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115361129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045348
S. Saha, Dwaipayan Chakraborty, Oindrilla Dutta
Training of feed-forward neural network using stochastic optimization techniques recently gained a lot of importance invarious pattern recognition and data mining applications because of its capability of escaping local minima trap. However such techniques may suffer from slow and poor convergence. This fact inspires us to work on meta-heuristic optimization technique for training the neural network. In this respect, to train the neural network, we focus on implementing the gravitational search algorithm(GSA) which is based on the Newton's law of motion principle and the interaction of masses. GSA has good ability to search for the global optimum, but it may suffer from slow searching speed in the last iterations. Our work is directed towards the smart convergence by modifying the original GSA and also guiding the algorithm to make it immune to local minima trap. Results on various benchmark datasets prove the robustness of the modified algorithm.
{"title":"Guided convergence for training feed-forward neural network using novel gravitational search optimization","authors":"S. Saha, Dwaipayan Chakraborty, Oindrilla Dutta","doi":"10.1109/ICHPCA.2014.7045348","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045348","url":null,"abstract":"Training of feed-forward neural network using stochastic optimization techniques recently gained a lot of importance invarious pattern recognition and data mining applications because of its capability of escaping local minima trap. However such techniques may suffer from slow and poor convergence. This fact inspires us to work on meta-heuristic optimization technique for training the neural network. In this respect, to train the neural network, we focus on implementing the gravitational search algorithm(GSA) which is based on the Newton's law of motion principle and the interaction of masses. GSA has good ability to search for the global optimum, but it may suffer from slow searching speed in the last iterations. Our work is directed towards the smart convergence by modifying the original GSA and also guiding the algorithm to make it immune to local minima trap. Results on various benchmark datasets prove the robustness of the modified algorithm.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115434799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045299
S. Mohanty, Pothuri Bhanu Sai Pavan Kumar, Kodavatikanti Hanok
We propose a timestamped signature scheme which can be verified universally using signer's public parameters. A trusted third party, the Time-Stamping System provides timestamp to a signature without even knowing the content of the document. The proposed scheme can withstand active attacks, such as forgery attack and chosen cipher text attack. It also provides the message recovery feature, i.e., from the time stamped signature, the message can be recovered by the receiver. Hence, the message need not be sent with the signature. The suggested scheme do not require any hash function and there by reduces the verification cost as compared to existing schemes at the expense of marginal increase in signature generation cost. Further, the scheme is more secured as its security lies in solving three computationally hard assumptions.
{"title":"A Timestamped Signature Scheme with Message Recovery","authors":"S. Mohanty, Pothuri Bhanu Sai Pavan Kumar, Kodavatikanti Hanok","doi":"10.1109/ICHPCA.2014.7045299","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045299","url":null,"abstract":"We propose a timestamped signature scheme which can be verified universally using signer's public parameters. A trusted third party, the Time-Stamping System provides timestamp to a signature without even knowing the content of the document. The proposed scheme can withstand active attacks, such as forgery attack and chosen cipher text attack. It also provides the message recovery feature, i.e., from the time stamped signature, the message can be recovered by the receiver. Hence, the message need not be sent with the signature. The suggested scheme do not require any hash function and there by reduces the verification cost as compared to existing schemes at the expense of marginal increase in signature generation cost. Further, the scheme is more secured as its security lies in solving three computationally hard assumptions.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123430331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045307
Keerti Tiwari, D. Saini
In the present wireless scenario, multiple-input and multiple-output (MIMO) is an emerging technique in wireless communication to achieve reliability and high throughput. Transmit diversity i.e. Alamouti space time block codes (STBC) and receiver diversity i.e. maximal ratio combining (MRC), are used to improve the link performance. In this paper, bit error rate (BER) performance is evaluated using distinct modulation schemes like BPSK, QPSK, and 16-QAM with STBC and MRC diversity techniques over Rayleigh, Rician and Nakagami-m fading channels. It is shown by simulated results that improved BER is achieved using MRC. Signal-to-noise ratio (SNR) is considered from 0 to 20 dB.
{"title":"BER performance comparison of MIMO system with STBC and MRC over different fading channels","authors":"Keerti Tiwari, D. Saini","doi":"10.1109/ICHPCA.2014.7045307","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045307","url":null,"abstract":"In the present wireless scenario, multiple-input and multiple-output (MIMO) is an emerging technique in wireless communication to achieve reliability and high throughput. Transmit diversity i.e. Alamouti space time block codes (STBC) and receiver diversity i.e. maximal ratio combining (MRC), are used to improve the link performance. In this paper, bit error rate (BER) performance is evaluated using distinct modulation schemes like BPSK, QPSK, and 16-QAM with STBC and MRC diversity techniques over Rayleigh, Rician and Nakagami-m fading channels. It is shown by simulated results that improved BER is achieved using MRC. Signal-to-noise ratio (SNR) is considered from 0 to 20 dB.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121740231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045367
Soumen Saha, Utpal Roy, D. Sinha
Vehicular ad hoc network (VANET) is considered as a sub-set of mobile ad hoc network (MANET). It provides smart Transport System i.e., wireless ad-hoc communication in between vehicles and vehicle to roadside equipments. Based on this technology road network is classified into two types 1. vehicle to vehicle interaction, 2. vehicle to infrastructure interaction. The objective of VANET is to provide safe, secure and automated traffic system. For this automated traffic technique several types of routing protocols have been developed. But routing protocols of MANET are not directly applicable to VANET. In this study, we proposed a modified AODV routing protocol in the context of VANET with the help of dqueue introduction into the RREQ header in the C++ code of built-in AODV protocol in NCTUns-6.0 simulator. Recently Saha et al [1] has reported the results showing the nature of modified AODV obtained from the rudimentary version of their simulation code. It is mainly based on packed delivery throughput. It shows greater In-throughput information of packet transmission compare to original AODV. It has been observed from the study that our protocols needs less overhead and yield greater performance in compared to conventional AODV.
{"title":"AODV routing protocol modification with dqueue(dqAODV) for VANET in city scenarios","authors":"Soumen Saha, Utpal Roy, D. Sinha","doi":"10.1109/ICHPCA.2014.7045367","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045367","url":null,"abstract":"Vehicular ad hoc network (VANET) is considered as a sub-set of mobile ad hoc network (MANET). It provides smart Transport System i.e., wireless ad-hoc communication in between vehicles and vehicle to roadside equipments. Based on this technology road network is classified into two types 1. vehicle to vehicle interaction, 2. vehicle to infrastructure interaction. The objective of VANET is to provide safe, secure and automated traffic system. For this automated traffic technique several types of routing protocols have been developed. But routing protocols of MANET are not directly applicable to VANET. In this study, we proposed a modified AODV routing protocol in the context of VANET with the help of dqueue introduction into the RREQ header in the C++ code of built-in AODV protocol in NCTUns-6.0 simulator. Recently Saha et al [1] has reported the results showing the nature of modified AODV obtained from the rudimentary version of their simulation code. It is mainly based on packed delivery throughput. It shows greater In-throughput information of packet transmission compare to original AODV. It has been observed from the study that our protocols needs less overhead and yield greater performance in compared to conventional AODV.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129502530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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