Pub Date : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208335
R. Kaniezhil, C. Chandrasekar, S. Rekha
The current utilization of the spectrum is quite inefficient; consequently, if properly used, there is no shortage of the spectrum that is presently available. Therefore, it is anticipated that more flexible use of spectrum and spectrum sharing between radio systems will be key enablers to facilitate the successful implementation of future systems. Cognitive radio, however, is known as the most intelligent and promising technique in solving the problem of spectrum sharing. In this paper, we consider the technique of spectrum sharing among users of service providers to share the licensed spectrum of licensed service providers. It is shown that the proposed technique reduces the call blocking rate and improves the spectrum utilization.
{"title":"Dynamic spectrum sharing for heterogeneous wireless network via cognitive radio","authors":"R. Kaniezhil, C. Chandrasekar, S. Rekha","doi":"10.1109/ICPRIME.2012.6208335","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208335","url":null,"abstract":"The current utilization of the spectrum is quite inefficient; consequently, if properly used, there is no shortage of the spectrum that is presently available. Therefore, it is anticipated that more flexible use of spectrum and spectrum sharing between radio systems will be key enablers to facilitate the successful implementation of future systems. Cognitive radio, however, is known as the most intelligent and promising technique in solving the problem of spectrum sharing. In this paper, we consider the technique of spectrum sharing among users of service providers to share the licensed spectrum of licensed service providers. It is shown that the proposed technique reduces the call blocking rate and improves the spectrum utilization.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128371641","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208378
Ayan Nigam, Bhawna Nigam, Chayan Bhaisare, N. Arya
It is always important in the Software Industry to know about what types of bugs are getting reported into the applications developed or maintained by them. Categorizing bugs based on their characteristics helps Software Development team to take appropriate actions in order to reduce similar defects that might get reported in future releases. Defects or Bugs can be classified into many classes, for which a training set is required, known as the Class Label Data Set. If Classification is performed manually then it will consume more time and efforts. Also, human resource having expert testing skills & domain knowledge will be required for labelling the data. Therefore Semi Supervised Techniques are been used to reduce the work of labelling dataset, which takes some labeled with unlabeled dataset to train the classifier. In this paper Self Training Algorithm is used for Semi Supervised Learning and Winner-Takes-All strategy is applied to perform Multi Class Classification. This model provides Classification accuracy up to 93%.
{"title":"Classifying the bugs using multi-class semi supervised support vector machine","authors":"Ayan Nigam, Bhawna Nigam, Chayan Bhaisare, N. Arya","doi":"10.1109/ICPRIME.2012.6208378","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208378","url":null,"abstract":"It is always important in the Software Industry to know about what types of bugs are getting reported into the applications developed or maintained by them. Categorizing bugs based on their characteristics helps Software Development team to take appropriate actions in order to reduce similar defects that might get reported in future releases. Defects or Bugs can be classified into many classes, for which a training set is required, known as the Class Label Data Set. If Classification is performed manually then it will consume more time and efforts. Also, human resource having expert testing skills & domain knowledge will be required for labelling the data. Therefore Semi Supervised Techniques are been used to reduce the work of labelling dataset, which takes some labeled with unlabeled dataset to train the classifier. In this paper Self Training Algorithm is used for Semi Supervised Learning and Winner-Takes-All strategy is applied to perform Multi Class Classification. This model provides Classification accuracy up to 93%.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128230475","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208386
B. Nagaraja, H. S. Jayanna
Nowadays, Speaker identification system plays a very important role in the field of fast growing internet based communication/transactions. In this paper, speaker identification in the context of Mono-lingual and Cross-lingual are demonstrated for Indian languages with the constraint of limited data. The languages considered for the study are English, Hindi and Kannada. Since the standard Multi-lingual database is not available, experiments are carried out on an our own created database of 30 speakers who can speak the three different languages. It was found out in the experimental study that the Mono-lingual speaker identification gives better performance with English as training and testing language though it is not a native language of speakers considered for the study. Further, it was observed in Cross-lingual study that the use of English language either in training or testing gives better identification performance.
{"title":"Mono and Cross lingual speaker identification with the constraint of limited data","authors":"B. Nagaraja, H. S. Jayanna","doi":"10.1109/ICPRIME.2012.6208386","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208386","url":null,"abstract":"Nowadays, Speaker identification system plays a very important role in the field of fast growing internet based communication/transactions. In this paper, speaker identification in the context of Mono-lingual and Cross-lingual are demonstrated for Indian languages with the constraint of limited data. The languages considered for the study are English, Hindi and Kannada. Since the standard Multi-lingual database is not available, experiments are carried out on an our own created database of 30 speakers who can speak the three different languages. It was found out in the experimental study that the Mono-lingual speaker identification gives better performance with English as training and testing language though it is not a native language of speakers considered for the study. Further, it was observed in Cross-lingual study that the use of English language either in training or testing gives better identification performance.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114945274","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208357
P. Bagchi, D. Bhattacharjee, M. Nasipuri, D. K. Basu
This paper is based on n application of smoothing of 3D face images followed by feature detection i.e. detecting the nose tip. The present method uses a weighted mesh median filtering technique for smoothing. In this present smoothing technique we have built the neighborhood surrounding a particular point in 3D face and replaced that with the weighted value of the surrounding points in 3D face image. After applying the smoothing technique to the 3D face images our experimental results show that we have obtained considerable improvement as compared to the algorithm without smoothing. We have used here the maximum intensity algorithm for detecting the nose-tip and this method correctly detects the nose-tip in case of any pose i.e. along X, Y, and Z axes. The present technique gave us worked successfully on 535 out of 542 3D face images as compared to the method without smoothing which worked only on 521 3D face images out of 542 face images. Thus we have obtained a 98.70% performance rate over 96.12% performance rate of the algorithm without smoothing. All the experiments have been performed on the FRAV3D database.
{"title":"A novel approach for nose tip detection using smoothing by weighted median filtering applied to 3D face images in variant poses","authors":"P. Bagchi, D. Bhattacharjee, M. Nasipuri, D. K. Basu","doi":"10.1109/ICPRIME.2012.6208357","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208357","url":null,"abstract":"This paper is based on n application of smoothing of 3D face images followed by feature detection i.e. detecting the nose tip. The present method uses a weighted mesh median filtering technique for smoothing. In this present smoothing technique we have built the neighborhood surrounding a particular point in 3D face and replaced that with the weighted value of the surrounding points in 3D face image. After applying the smoothing technique to the 3D face images our experimental results show that we have obtained considerable improvement as compared to the algorithm without smoothing. We have used here the maximum intensity algorithm for detecting the nose-tip and this method correctly detects the nose-tip in case of any pose i.e. along X, Y, and Z axes. The present technique gave us worked successfully on 535 out of 542 3D face images as compared to the method without smoothing which worked only on 521 3D face images out of 542 face images. Thus we have obtained a 98.70% performance rate over 96.12% performance rate of the algorithm without smoothing. All the experiments have been performed on the FRAV3D database.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116715867","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208387
S. Seeri, S. Giraddi, B. Prashant
Popularity of the digital cameras is increasing rapidly day by day because of advanced applications and availability of digital cameras. The detection and extraction of text regions in an image is a well known problem in the computer vision. Text in images contains useful semantic information which can be used to fully understand the images. Proposed method aims at detecting and extracting Kannada text from government organization signboard images acquired by digital camera. Segmentation is performed using edge detection method and heuristic features are used to remove the non text regions. Kannada text identification is performed using the structural feature boundary length of the object strokes. Rule based method is employed to validate the objects as Kannada text. The proposed method is effective, efficient and encouraging results are obtained. It has the precision rate of 84.21%, recall rate of 83.16% and Kannada text identification accuracy of 75.77%. Hence proposed method is robust with font size, small orientation and alignment of text.
{"title":"A novel approach for Kannada text extraction","authors":"S. Seeri, S. Giraddi, B. Prashant","doi":"10.1109/ICPRIME.2012.6208387","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208387","url":null,"abstract":"Popularity of the digital cameras is increasing rapidly day by day because of advanced applications and availability of digital cameras. The detection and extraction of text regions in an image is a well known problem in the computer vision. Text in images contains useful semantic information which can be used to fully understand the images. Proposed method aims at detecting and extracting Kannada text from government organization signboard images acquired by digital camera. Segmentation is performed using edge detection method and heuristic features are used to remove the non text regions. Kannada text identification is performed using the structural feature boundary length of the object strokes. Rule based method is employed to validate the objects as Kannada text. The proposed method is effective, efficient and encouraging results are obtained. It has the precision rate of 84.21%, recall rate of 83.16% and Kannada text identification accuracy of 75.77%. Hence proposed method is robust with font size, small orientation and alignment of text.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114730089","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208383
N. Raju, P. Preethi, T. L. Priya, S. Mathini
The emotional influence on human behavior can be identified by speech. Recognition of emotion plays a vital role in many fields such as automatic emotion recognition etc. In this paper, we distinguish a normal person from the terrorist/victim by identifying their emotional state from speech. Emotional states dealt with in this paper are neutral, sad, anger, fear, etc. Two different algorithm of pitch is used to extract the pitch here. Moreover, support vector machine is used to classify the emotional state. The accuracy level of the classifier differentiates the emotional state of the normal person from the terrorist/victim. For the classification of all emotions, the average accuracy of both male and female is 80%.
{"title":"Emotion recognition — An approach to identify the terrorist","authors":"N. Raju, P. Preethi, T. L. Priya, S. Mathini","doi":"10.1109/ICPRIME.2012.6208383","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208383","url":null,"abstract":"The emotional influence on human behavior can be identified by speech. Recognition of emotion plays a vital role in many fields such as automatic emotion recognition etc. In this paper, we distinguish a normal person from the terrorist/victim by identifying their emotional state from speech. Emotional states dealt with in this paper are neutral, sad, anger, fear, etc. Two different algorithm of pitch is used to extract the pitch here. Moreover, support vector machine is used to classify the emotional state. The accuracy level of the classifier differentiates the emotional state of the normal person from the terrorist/victim. For the classification of all emotions, the average accuracy of both male and female is 80%.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"2020 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114733926","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208302
P. Saranya, A. Sridevi
The application of multiple clocking domains with dedicated clock buffer will be implemented. In this paper, an algorithm is proposed for determining the minimum number of clock domains to be used for multi domain clock skew scheduling. Non-tree based distributions provide a high tolerance towards process variations. The clock mesh constraints can be overcome by two processes. First a simultaneous buffer placement and sizing is done which satisfies the signal slew constraints while minimizing the total buffer size by heuristic algorithm. The second one reduces the mesh by deleting certain edges, thereby trading off skew tolerance for low power dissipation by post processing techniques. Finally comparisons of wire length, power dissipation, nominal skew and variation skews using H-SPICE software for various sized benchmark circuits are performed.
{"title":"An efficient heuristic algorithm for fast clock mesh realization","authors":"P. Saranya, A. Sridevi","doi":"10.1109/ICPRIME.2012.6208302","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208302","url":null,"abstract":"The application of multiple clocking domains with dedicated clock buffer will be implemented. In this paper, an algorithm is proposed for determining the minimum number of clock domains to be used for multi domain clock skew scheduling. Non-tree based distributions provide a high tolerance towards process variations. The clock mesh constraints can be overcome by two processes. First a simultaneous buffer placement and sizing is done which satisfies the signal slew constraints while minimizing the total buffer size by heuristic algorithm. The second one reduces the mesh by deleting certain edges, thereby trading off skew tolerance for low power dissipation by post processing techniques. Finally comparisons of wire length, power dissipation, nominal skew and variation skews using H-SPICE software for various sized benchmark circuits are performed.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128569927","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208300
M. Janagan, M. Devanathan
Elliptic curve cryptography (ECC) is an alternative to traditional public key cryptographic systems. Even though, RSA (Rivest-Shamir-Adleman) was the most prominent cryptographic scheme, it is being replaced by ECC in many systems. This is due to the fact that ECC gives higher security with shorter bit length than RSA. In Elliptic curve based algorithms elliptic curve point multiplication is the most computationally intensive operation. Therefore implementing point multiplication using hardware makes ECC more attractive for high performance servers and small devices. This paper gives the scope of Montgomery ladder computationally. Montgomery ladder algorithm is effective in computation of Elliptic Curve Point Multiplication (ECPM) when compared to Elliptic Curve Digital Signature Algorithm (ECDSA). Compactness is achieved by reducing data paths by using multipliers and carry-chain logic. Multiplier performs effectively in terms of area/time if the word size of multiplier is large. A solution for Simple Power Analysis (SPA) attack is also provided. In Montgomery modular inversion 33% of saving in Montgomery multiplication is achieved and a saving of 50% on the number of gates required in implementation can be achieved.
椭圆曲线加密(ECC)是传统公钥加密系统的替代方案。尽管RSA (Rivest-Shamir-Adleman)是最著名的加密方案，但在许多系统中它正在被ECC所取代。这是因为ECC比RSA提供了更高的安全性和更短的比特长度。在基于椭圆曲线的算法中，椭圆曲线点乘法运算是计算量最大的运算。因此，使用硬件实现点乘法使ECC对高性能服务器和小型设备更具吸引力。本文给出了蒙哥马利梯的计算范围。与椭圆曲线数字签名算法(ECDSA)相比，Montgomery阶梯算法在椭圆曲线点乘法(ECPM)的计算中具有较高的效率。紧凑性是通过使用乘法器和携带链逻辑减少数据路径来实现的。如果乘数的字长较大，则乘数在面积/时间方面表现有效。提出了简单功率分析(Simple Power Analysis, SPA)攻击的解决方案。在Montgomery模反转中，可以实现33%的Montgomery乘法节省，并且可以实现所需的门数节省50%。
{"title":"Area compactness architecture for elliptic curve cryptography","authors":"M. Janagan, M. Devanathan","doi":"10.1109/ICPRIME.2012.6208300","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208300","url":null,"abstract":"Elliptic curve cryptography (ECC) is an alternative to traditional public key cryptographic systems. Even though, RSA (Rivest-Shamir-Adleman) was the most prominent cryptographic scheme, it is being replaced by ECC in many systems. This is due to the fact that ECC gives higher security with shorter bit length than RSA. In Elliptic curve based algorithms elliptic curve point multiplication is the most computationally intensive operation. Therefore implementing point multiplication using hardware makes ECC more attractive for high performance servers and small devices. This paper gives the scope of Montgomery ladder computationally. Montgomery ladder algorithm is effective in computation of Elliptic Curve Point Multiplication (ECPM) when compared to Elliptic Curve Digital Signature Algorithm (ECDSA). Compactness is achieved by reducing data paths by using multipliers and carry-chain logic. Multiplier performs effectively in terms of area/time if the word size of multiplier is large. A solution for Simple Power Analysis (SPA) attack is also provided. In Montgomery modular inversion 33% of saving in Montgomery multiplication is achieved and a saving of 50% on the number of gates required in implementation can be achieved.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121945596","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208358
P. Patil, M. Chavan
Noise removal of Electrocardiogram has always been a subject of wide research. ECG signals change their statistical properties over time. Wavelet transform is the most powerful tool for analyzing the non-stationary signals. This paper shows that how it is useful in denoising non-stationary signals e.g. The ECG signals. We considered two types of ECG signal, without additional noise and corrupted by powerline interference and we realized the signal's denoising using wavelet filtering. The ECG data is taken from standard MIT-BIH Arrhythmia database, while noise signal is generated and added to the original signal using instructions in MATLAB environment. In this paper, we present Daubechies wavelet analysis method with a decomposition tree of level 5 for analysis of noisy ECG signals. The implementation includes the procedures of signal decomposition and reconstruction with hard and soft thresholding. Furthermore quantitative study of result evaluation has been done based on Signal to Noise Ratio (SNR). The results show that, on contrast with traditional methods wavelet method can achieve optimal denoising of ECG signal.
{"title":"A wavelet based method for denoising of biomedical signal","authors":"P. Patil, M. Chavan","doi":"10.1109/ICPRIME.2012.6208358","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208358","url":null,"abstract":"Noise removal of Electrocardiogram has always been a subject of wide research. ECG signals change their statistical properties over time. Wavelet transform is the most powerful tool for analyzing the non-stationary signals. This paper shows that how it is useful in denoising non-stationary signals e.g. The ECG signals. We considered two types of ECG signal, without additional noise and corrupted by powerline interference and we realized the signal's denoising using wavelet filtering. The ECG data is taken from standard MIT-BIH Arrhythmia database, while noise signal is generated and added to the original signal using instructions in MATLAB environment. In this paper, we present Daubechies wavelet analysis method with a decomposition tree of level 5 for analysis of noisy ECG signals. The implementation includes the procedures of signal decomposition and reconstruction with hard and soft thresholding. Furthermore quantitative study of result evaluation has been done based on Signal to Noise Ratio (SNR). The results show that, on contrast with traditional methods wavelet method can achieve optimal denoising of ECG signal.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"93 Pt A 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115786461","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 : 2012-03-21DOI: 10.1109/ICPRIME.2012.6208336
S. Poongodi, P. Tamilselvi
Several medium access control protocols have been proposed in the recent past for vehicles for accessing radio channels and for distributing timely active safety messages for inter-vehicle communication in Vehicular Ad hoc Networks (VANETs). As contention period is high in Medium Access Control (MAC) for channel access, MAC is unable to distribute timely safety messages. To reduce the contention period, Region based Clustering Mechanism (RCM) is applied with MAC protocols. RCM caters to the reduction of contention because the number of vehicles for each cluster is limited. In addition, it resolves the competition among vehicles to access radio channels for inter-vehicle communication. Ad Hoc On-Demand Distance Vector (AODV) routing protocol is used for providing shortest path between source and destination which increases the amount of packet reception and cluster formation. Geo cache is included in VANET in order to retain directory that includes information about nodes that have left a particular cluster through neighboring nodes.
最近提出了几种媒介访问控制协议，用于车辆访问无线电信道和在车辆自组织网络(VANETs)中及时分发车辆间通信的主动安全信息。由于通道访问的介质访问控制(Medium Access Control, MAC)争用周期长，导致MAC无法及时分发安全消息。为了缩短争用周期，MAC协议采用了基于区域的聚类机制(RCM)。RCM用于减少争用，因为每个集群的车辆数量是有限的。此外，它还解决了车辆间对无线通信信道的竞争问题。采用AODV (Ad Hoc On-Demand Distance Vector)路由协议，在源端和目的端之间提供最短路径，增加了数据包的接收量和集群的形成。地理缓存包含在VANET中是为了保留目录，其中包含通过邻近节点离开特定集群的节点的信息。
{"title":"Global clustering based geo cache for Vehicular Ad hoc Networks","authors":"S. Poongodi, P. Tamilselvi","doi":"10.1109/ICPRIME.2012.6208336","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208336","url":null,"abstract":"Several medium access control protocols have been proposed in the recent past for vehicles for accessing radio channels and for distributing timely active safety messages for inter-vehicle communication in Vehicular Ad hoc Networks (VANETs). As contention period is high in Medium Access Control (MAC) for channel access, MAC is unable to distribute timely safety messages. To reduce the contention period, Region based Clustering Mechanism (RCM) is applied with MAC protocols. RCM caters to the reduction of contention because the number of vehicles for each cluster is limited. In addition, it resolves the competition among vehicles to access radio channels for inter-vehicle communication. Ad Hoc On-Demand Distance Vector (AODV) routing protocol is used for providing shortest path between source and destination which increases the amount of packet reception and cluster formation. Geo cache is included in VANET in order to retain directory that includes information about nodes that have left a particular cluster through neighboring nodes.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128443565","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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