Pub Date : 2010-12-01DOI: 10.1109/ICCITECHN.2010.5723896
K. Mamun, Manoj Banik, M. Mace, Mark E. Lutmen, R. Vaidyanathan, Shouyan Wang
Tongue movement ear pressure (TMEP) signals have been used to generate controlling commands in assistive human machine interfaces aimed at people with disabilities. The objective of this study is to classify the controlled movement related signals of an intended action from internally occurring physiological signals which can interfere with the inter-movement classification. TMEP signals were collected, corresponding to six types of controlled movements and activity relating to the potentially interfering environment including when a subject spoke, coughed or drank. The signal processing algorithm involved TMEP signal detection, segmentation, feature extraction and selection, and classification. The features of the segmented TMEP signals were extracted using the wavelet packet transform (WPT). A multi-layer neural network was then designed and tested based on statistical properties of the WPT coefficients. The average classification performance for discriminating interference and controlled movement related TMEP signal achieved 97.05%. The classification of TMEP signals based on the WPT is robust and the interferences to the controlling commands of TMEP signals in assistive human machine interface can be significantly reduced using the multi-layer neural network when considered in this challenging environment.
{"title":"Multi-layer neural network classification of tongue movement ear pressure signal for human machine interface","authors":"K. Mamun, Manoj Banik, M. Mace, Mark E. Lutmen, R. Vaidyanathan, Shouyan Wang","doi":"10.1109/ICCITECHN.2010.5723896","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2010.5723896","url":null,"abstract":"Tongue movement ear pressure (TMEP) signals have been used to generate controlling commands in assistive human machine interfaces aimed at people with disabilities. The objective of this study is to classify the controlled movement related signals of an intended action from internally occurring physiological signals which can interfere with the inter-movement classification. TMEP signals were collected, corresponding to six types of controlled movements and activity relating to the potentially interfering environment including when a subject spoke, coughed or drank. The signal processing algorithm involved TMEP signal detection, segmentation, feature extraction and selection, and classification. The features of the segmented TMEP signals were extracted using the wavelet packet transform (WPT). A multi-layer neural network was then designed and tested based on statistical properties of the WPT coefficients. The average classification performance for discriminating interference and controlled movement related TMEP signal achieved 97.05%. The classification of TMEP signals based on the WPT is robust and the interferences to the controlling commands of TMEP signals in assistive human machine interface can be significantly reduced using the multi-layer neural network when considered in this challenging environment.","PeriodicalId":149135,"journal":{"name":"2010 13th International Conference on Computer and Information Technology (ICCIT)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133199662","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 : 2010-12-01DOI: 10.1109/ICCITECHN.2010.5723826
S. Monira, Zaman M. Faisal, Hideo Hirose
Rainfall forecasting has been one of the most scientifically and technologically challenging task in the climate dynamics and climate prediction theory around the world in the last century. This is due to the great effect of forecasting on human activities and also for the significant computational advances that are utilized in this research field. In this paper our main objective is to forecast over a very short-term and specified local area weather using local data which is not always available by forecast center but will be available in the future by social network or some other methods. For this purpose in this paper we have applied three different algorithms belonging to the paradigm of artificial intelligence in short-term forecast of rainfalls (24 hours) using a regional rainfall data of Bihar (India) as a case study. This forecast is about predicting the categorical rainfall (some pre-defined category based on the amount of total daily rainfall) amount for the next day. We have used two classifier ensemble methods and a single classifier model for this purpose. The ensemble methods used in this paper are LogitBoosting (LB), and Random Forest (RF). The single classifier model is a Least Square Support Vector Machine (LS-SVM). We have optimized each of the models on validation sets and then forecast with the optimum model on the out of sample (or test) dataset. We have also verified our forecast results with some of the latest verification tools available. The experimental and verification results suggest that these methods are capable of efficiently forecasting the categorical rainfall amount in short term.
{"title":"Comparison of artificially intelligent methods in short term rainfall forecast","authors":"S. Monira, Zaman M. Faisal, Hideo Hirose","doi":"10.1109/ICCITECHN.2010.5723826","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2010.5723826","url":null,"abstract":"Rainfall forecasting has been one of the most scientifically and technologically challenging task in the climate dynamics and climate prediction theory around the world in the last century. This is due to the great effect of forecasting on human activities and also for the significant computational advances that are utilized in this research field. In this paper our main objective is to forecast over a very short-term and specified local area weather using local data which is not always available by forecast center but will be available in the future by social network or some other methods. For this purpose in this paper we have applied three different algorithms belonging to the paradigm of artificial intelligence in short-term forecast of rainfalls (24 hours) using a regional rainfall data of Bihar (India) as a case study. This forecast is about predicting the categorical rainfall (some pre-defined category based on the amount of total daily rainfall) amount for the next day. We have used two classifier ensemble methods and a single classifier model for this purpose. The ensemble methods used in this paper are LogitBoosting (LB), and Random Forest (RF). The single classifier model is a Least Square Support Vector Machine (LS-SVM). We have optimized each of the models on validation sets and then forecast with the optimum model on the out of sample (or test) dataset. We have also verified our forecast results with some of the latest verification tools available. The experimental and verification results suggest that these methods are capable of efficiently forecasting the categorical rainfall amount in short term.","PeriodicalId":149135,"journal":{"name":"2010 13th International Conference on Computer and Information Technology (ICCIT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133333512","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 : 2010-12-01DOI: 10.1109/ICCITECHN.2010.5723905
Md. Tarek Habib, M. Rokonuzzaman
Over the years significant research has been performed for automated, i.e. machine vision based fabric inspection systems in order to replace manual inspection, which is time consuming and not accurate enough. Automated fabric inspection systems mainly involve two challenging problems, one of which is defect classification. The amount of research done to date to solve the defect classification problem is insufficient. Scene analysis and feature selection play a very important role in the classification process. Insufficient scene analysis results in an inappropriate set of features. Selection of an inappropriate feature set increases complexities of subsequent steps and makes the classification task harder. Considering this observation, we present a possibly appropriate feature set in order to address the problem of fabric defect classification using neural network (NN). We justify the features from the point of view of distinguishing quality and feature extraction difficulty. We perform some experiments in order to show the utility of proposed features. Promising classification accuracy has been found.
{"title":"Selection of distinguishing features for fabric defect classification using neural network","authors":"Md. Tarek Habib, M. Rokonuzzaman","doi":"10.1109/ICCITECHN.2010.5723905","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2010.5723905","url":null,"abstract":"Over the years significant research has been performed for automated, i.e. machine vision based fabric inspection systems in order to replace manual inspection, which is time consuming and not accurate enough. Automated fabric inspection systems mainly involve two challenging problems, one of which is defect classification. The amount of research done to date to solve the defect classification problem is insufficient. Scene analysis and feature selection play a very important role in the classification process. Insufficient scene analysis results in an inappropriate set of features. Selection of an inappropriate feature set increases complexities of subsequent steps and makes the classification task harder. Considering this observation, we present a possibly appropriate feature set in order to address the problem of fabric defect classification using neural network (NN). We justify the features from the point of view of distinguishing quality and feature extraction difficulty. We perform some experiments in order to show the utility of proposed features. Promising classification accuracy has been found.","PeriodicalId":149135,"journal":{"name":"2010 13th International Conference on Computer and Information Technology (ICCIT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123946604","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 : 2010-12-01DOI: 10.1109/ICCITECHN.2010.5723904
Shafin Rahman, S. M. Naim, Abdullah Al Farooq, M. Islam
Face recognition is considered as a high dimensionality problem. To handle high dimensionality, a numerous methods have been proposed in literature. In this paper, we propose a novel face recognition method that efficiently solves that problem using MPEG-7 edge histogram descriptor. To the authors' knowledge, this is the first attempt to use edge histogram descriptor in face recognition. Although MPEG-7 standard represents only local edge histogram we use global and semi-global edge histogram also. We find that local edge histogram mostly helpful for face recognition. We test our system not only using the entire face image as input but also dividing the image into different sub-divisions. PCA is then applied to the edge histogram descriptors of sub-divisions in-stead of raw pixel intensity values of images which traditional methods do. Since we use normalized edge histogram, our face recognition method becomes scale, translation and rotation invariant. Furthermore, our proposed method does not necessarily require all images to be of same resolution as input. We evaluate the proposed method using ORL, Yale and Face94 face databases and achieve superior performance.
{"title":"Performance of MPEG-7 edge histogram descriptor in face recognition using Principal Component Analysis","authors":"Shafin Rahman, S. M. Naim, Abdullah Al Farooq, M. Islam","doi":"10.1109/ICCITECHN.2010.5723904","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2010.5723904","url":null,"abstract":"Face recognition is considered as a high dimensionality problem. To handle high dimensionality, a numerous methods have been proposed in literature. In this paper, we propose a novel face recognition method that efficiently solves that problem using MPEG-7 edge histogram descriptor. To the authors' knowledge, this is the first attempt to use edge histogram descriptor in face recognition. Although MPEG-7 standard represents only local edge histogram we use global and semi-global edge histogram also. We find that local edge histogram mostly helpful for face recognition. We test our system not only using the entire face image as input but also dividing the image into different sub-divisions. PCA is then applied to the edge histogram descriptors of sub-divisions in-stead of raw pixel intensity values of images which traditional methods do. Since we use normalized edge histogram, our face recognition method becomes scale, translation and rotation invariant. Furthermore, our proposed method does not necessarily require all images to be of same resolution as input. We evaluate the proposed method using ORL, Yale and Face94 face databases and achieve superior performance.","PeriodicalId":149135,"journal":{"name":"2010 13th International Conference on Computer and Information Technology (ICCIT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124100866","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 : 2010-12-01DOI: 10.1109/ICCITECHN.2010.5723899
M. N. Huda, Md. Shahadat Hossain, Foyzul Hassan, Mohammad Mahedi Hasan, N. J. Lisa, G. Muhammad
This paper describes an evaluation of Inhibition/Enhancement (In/En) network for noise robust automatic speech recognition (ASR). In articulatory feature based speech recognition using neural network, the In/En network is needed to discriminate whether the articulatory features (AFs) dynamic patterns of trajectories are convex or concave. The network is used to achieve categorical AFs movement by enhancing AFs peak patterns (convex patterns) and inhibiting AFs dip patterns (concave patterns). We have analyzed the effectiveness of the In/En algorithm by incorporating it into a system which consists of three stages: a) Multilayer Neural Networks (MLNs), b) an In/En Network and c) the Gram-Schmidt (GS) algorithm for orthogonalization. From the experiments using Japanese Newspaper Article Sentences (JNAS) database in clean and noisy acoustic environments, it is observed that the In/En network plays a significant role on the improvement of phoneme recognition performance. Moreover, the In/En network reduces the number of mixture components needed in Hidden Markov Models (HMMs).
{"title":"An Inhibition/Enhancement network for noise robust ASR","authors":"M. N. Huda, Md. Shahadat Hossain, Foyzul Hassan, Mohammad Mahedi Hasan, N. J. Lisa, G. Muhammad","doi":"10.1109/ICCITECHN.2010.5723899","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2010.5723899","url":null,"abstract":"This paper describes an evaluation of Inhibition/Enhancement (In/En) network for noise robust automatic speech recognition (ASR). In articulatory feature based speech recognition using neural network, the In/En network is needed to discriminate whether the articulatory features (AFs) dynamic patterns of trajectories are convex or concave. The network is used to achieve categorical AFs movement by enhancing AFs peak patterns (convex patterns) and inhibiting AFs dip patterns (concave patterns). We have analyzed the effectiveness of the In/En algorithm by incorporating it into a system which consists of three stages: a) Multilayer Neural Networks (MLNs), b) an In/En Network and c) the Gram-Schmidt (GS) algorithm for orthogonalization. From the experiments using Japanese Newspaper Article Sentences (JNAS) database in clean and noisy acoustic environments, it is observed that the In/En network plays a significant role on the improvement of phoneme recognition performance. Moreover, the In/En network reduces the number of mixture components needed in Hidden Markov Models (HMMs).","PeriodicalId":149135,"journal":{"name":"2010 13th International Conference on Computer and Information Technology (ICCIT)","volume":"360 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114842847","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 : 2010-12-01DOI: 10.1109/ICCITECHN.2010.5723852
K. Sakib, Z. Tari, P. Bertók
Redundant node deployment has an impact on network lifetime because redundant nodes consume excess energy by performing unnecessary repetitious tasks. A distributed node redundancy identification method, called Self-Calculated Redundancy Check (SCRC), is proposed to eliminate redundant tasks. A grid is assumed over the field to help each node to calculate its own redundancy by checking the coverage degree of its sensing region. This optimises the active node set while providing complete network coverage and connectivity. An analytical framework is presented for SCRC using the expected value optimisation technique. The framework is used to predict potentially redundant nodes under various node distributions.
{"title":"An analytical framework for identifying redundant sensor nodes from a dense sensor network","authors":"K. Sakib, Z. Tari, P. Bertók","doi":"10.1109/ICCITECHN.2010.5723852","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2010.5723852","url":null,"abstract":"Redundant node deployment has an impact on network lifetime because redundant nodes consume excess energy by performing unnecessary repetitious tasks. A distributed node redundancy identification method, called Self-Calculated Redundancy Check (SCRC), is proposed to eliminate redundant tasks. A grid is assumed over the field to help each node to calculate its own redundancy by checking the coverage degree of its sensing region. This optimises the active node set while providing complete network coverage and connectivity. An analytical framework is presented for SCRC using the expected value optimisation technique. The framework is used to predict potentially redundant nodes under various node distributions.","PeriodicalId":149135,"journal":{"name":"2010 13th International Conference on Computer and Information Technology (ICCIT)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128193128","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 : 2010-12-01DOI: 10.1109/ICCITECHN.2010.5723871
M. Azam, M. Quaddus, M. Rahim
Despite an increasing amount of initiatives and policy priorities remain in Bangladesh for ICT development and establishing an e-based society by 2021, lower level of internet penetration made the whole initiatives inconclusive although there are enormous potentials. This study attempts to examine individuals' intention and actual internet usage behaviour applying an extended version of technology acceptance model (TAM). A descriptive research design was administered in explaining the joint impact of the study constructs. Structural equation modeling approach was used with the data collected from 291 individuals in Bangladesh through a questionnaire survey. The proposed model was first measured through factor loadings, composite reliability and the constructs correlation for convergent and discriminant validity. The structural model estimation results show that experience has direct significant relation with perceive ease of use, intention and actual behaviour and indirect relation with perceived usefulness through perceived ease of use. On the other hand, perceive usefulness has direct effects on intention while perceived ease of use doesn't but indirectly related through perceived usefulness. The path analysis furthered the significant effects of intention on actual internet usage behaviour in Bangladesh. The study concludes with implications.
{"title":"How experience affects technology acceptance: A quest for ICT development strategies in Bangladesh","authors":"M. Azam, M. Quaddus, M. Rahim","doi":"10.1109/ICCITECHN.2010.5723871","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2010.5723871","url":null,"abstract":"Despite an increasing amount of initiatives and policy priorities remain in Bangladesh for ICT development and establishing an e-based society by 2021, lower level of internet penetration made the whole initiatives inconclusive although there are enormous potentials. This study attempts to examine individuals' intention and actual internet usage behaviour applying an extended version of technology acceptance model (TAM). A descriptive research design was administered in explaining the joint impact of the study constructs. Structural equation modeling approach was used with the data collected from 291 individuals in Bangladesh through a questionnaire survey. The proposed model was first measured through factor loadings, composite reliability and the constructs correlation for convergent and discriminant validity. The structural model estimation results show that experience has direct significant relation with perceive ease of use, intention and actual behaviour and indirect relation with perceived usefulness through perceived ease of use. On the other hand, perceive usefulness has direct effects on intention while perceived ease of use doesn't but indirectly related through perceived usefulness. The path analysis furthered the significant effects of intention on actual internet usage behaviour in Bangladesh. The study concludes with implications.","PeriodicalId":149135,"journal":{"name":"2010 13th International Conference on Computer and Information Technology (ICCIT)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126860397","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 : 2010-12-01DOI: 10.1109/ICCITECHN.2010.5723846
Bijoy Kumar Upadhyaya, S. Iti, S. Sanyal
Wireless technology is the fastest growing segment of the modern communication industry. The IEEE 802.16e standard, commonly known as mobile WiMAX, is the latest wireless technology that has promised to offer Broadband Wireless Access over long distance. The concept of OFDM is used in WiMAX to obtain high data rate in addition to reducing the effects like inter symbol interference and inter channel interference. It has proved to be the air interface for next generation Broadband Wireless System. In this paper, we present a finite state machine based novel technique to model the Address Generation circuitry of WiMAX multimode interleaver using VHDL on FPGA platform with all code rates and modulation schemes of IEEE 802.16e standard. Our approach provides better performance in terms of maximum operating frequency, use of flip-flops with negligible loss in terms of logic cells utilized compared to existing FPGA based implementations. Measured circuit parameters and software simulation of this model are also provided.
{"title":"Novel design of Address Generator for WiMAX multimode interleaver using FPGA based finite state machine","authors":"Bijoy Kumar Upadhyaya, S. Iti, S. Sanyal","doi":"10.1109/ICCITECHN.2010.5723846","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2010.5723846","url":null,"abstract":"Wireless technology is the fastest growing segment of the modern communication industry. The IEEE 802.16e standard, commonly known as mobile WiMAX, is the latest wireless technology that has promised to offer Broadband Wireless Access over long distance. The concept of OFDM is used in WiMAX to obtain high data rate in addition to reducing the effects like inter symbol interference and inter channel interference. It has proved to be the air interface for next generation Broadband Wireless System. In this paper, we present a finite state machine based novel technique to model the Address Generation circuitry of WiMAX multimode interleaver using VHDL on FPGA platform with all code rates and modulation schemes of IEEE 802.16e standard. Our approach provides better performance in terms of maximum operating frequency, use of flip-flops with negligible loss in terms of logic cells utilized compared to existing FPGA based implementations. Measured circuit parameters and software simulation of this model are also provided.","PeriodicalId":149135,"journal":{"name":"2010 13th International Conference on Computer and Information Technology (ICCIT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121939146","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 : 2010-12-01DOI: 10.1109/ICCITECHN.2010.5723923
S. Jahan, M. Islam, M. Amin
We evaluate performance of hierarchical network (overlay-underlay cellular system) based on convolution method under mixed offered traffic. In most of the cases, different offered traffic of a network follows different probability density functions and they are correlated in sharing channel environment and cannot be analyzed by equivalent random theory (ERT) model. Here, three different types of offered traffic are considered for determining the blocking probability in the higher-tier cells.
{"title":"Performance evaluation of multidimensional traffic in micro-macro cellular system","authors":"S. Jahan, M. Islam, M. Amin","doi":"10.1109/ICCITECHN.2010.5723923","DOIUrl":"https://doi.org/10.1109/ICCITECHN.2010.5723923","url":null,"abstract":"We evaluate performance of hierarchical network (overlay-underlay cellular system) based on convolution method under mixed offered traffic. In most of the cases, different offered traffic of a network follows different probability density functions and they are correlated in sharing channel environment and cannot be analyzed by equivalent random theory (ERT) model. Here, three different types of offered traffic are considered for determining the blocking probability in the higher-tier cells.","PeriodicalId":149135,"journal":{"name":"2010 13th International Conference on Computer and Information Technology (ICCIT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132968515","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}
The static network performance and dynamic communication performance of the Hierarchical Torus Network (HTN) using dimension-order routing algorithm have already been evaluated and shown to be superior to the performance of other interconnection networks. However, the assessment of the dynamic communication performance improvement of HTN by the efficient use of both the physical link and virtual channels has not yet been evaluated. This paper addresses three adaptive routing algorithms - link-selection, channel-selection, and a combination of link-selection and channel-selection - for the efficient use of physical links and virtual channels of an HTN to enhance dynamic communication performance. It also proves that the proposed adaptive routing algorithms are deadlock-free with 3 virtual channels. The dynamic communication performances of an HTN is evaluated by using dimension-order routing and proposed adaptive routing algorithms under various traffic patterns. It is found that the dynamic communication performance of an HTN using these adaptive routing is better than when the dimension-order routing is used, in terms of network throughput.
{"title":"Dynamic communication performance enhancement in Hierarchical Torus Network by selection algorithm","authors":"M. Rahman, Yukinori Sato, Y. Inoguchi","doi":"10.4304/jnw.7.3.468-479","DOIUrl":"https://doi.org/10.4304/jnw.7.3.468-479","url":null,"abstract":"The static network performance and dynamic communication performance of the Hierarchical Torus Network (HTN) using dimension-order routing algorithm have already been evaluated and shown to be superior to the performance of other interconnection networks. However, the assessment of the dynamic communication performance improvement of HTN by the efficient use of both the physical link and virtual channels has not yet been evaluated. This paper addresses three adaptive routing algorithms - link-selection, channel-selection, and a combination of link-selection and channel-selection - for the efficient use of physical links and virtual channels of an HTN to enhance dynamic communication performance. It also proves that the proposed adaptive routing algorithms are deadlock-free with 3 virtual channels. The dynamic communication performances of an HTN is evaluated by using dimension-order routing and proposed adaptive routing algorithms under various traffic patterns. It is found that the dynamic communication performance of an HTN using these adaptive routing is better than when the dimension-order routing is used, in terms of network throughput.","PeriodicalId":149135,"journal":{"name":"2010 13th International Conference on Computer and Information Technology (ICCIT)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134339886","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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