Pub Date : 2019-11-01DOI: 10.1109/SMART46866.2019.9117484
Gona Ashwini Rao, R. Nagaswetha, D. Singh
We propose an innovative Voice Based Virtual Agri Farming Analyzer (v2) which creates a virtual environment where the climate will be monitored and controlled by the sensors connected to a microcontroller. These sensors accept the real time data of temperature, humidity, soil moisture and soil temperature from the agriculture fields. On comparing values with the standard one, necessary actions will be taken by the actuators like fans, cool mist humidifier, water motors. In the background, the data will be continuously visualized using cloud platform and will be displayed on the screen, the data will be applied with prediction algorithms in a web tool. Final predicted value will be generated in the format of a tree model with a range of optimum values. These optimum values can be used inside the system to maintain the effective growth. An inlet for fertilizers is present at the top of the system. This inlet drops the fertilizer along with the water whenever required for that specific plants. A touch-display will be available for the user to obtain any of the internal conditions. A voice enabled device is attached which provides information about the internal processes taking place. A push notification will be sent to the farmers through the cloud service whenever any action is being taken internally.
{"title":"Voice Based Virtual Agri Farming Analyzer with BigML Algorithms","authors":"Gona Ashwini Rao, R. Nagaswetha, D. Singh","doi":"10.1109/SMART46866.2019.9117484","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117484","url":null,"abstract":"We propose an innovative Voice Based Virtual Agri Farming Analyzer (v2) which creates a virtual environment where the climate will be monitored and controlled by the sensors connected to a microcontroller. These sensors accept the real time data of temperature, humidity, soil moisture and soil temperature from the agriculture fields. On comparing values with the standard one, necessary actions will be taken by the actuators like fans, cool mist humidifier, water motors. In the background, the data will be continuously visualized using cloud platform and will be displayed on the screen, the data will be applied with prediction algorithms in a web tool. Final predicted value will be generated in the format of a tree model with a range of optimum values. These optimum values can be used inside the system to maintain the effective growth. An inlet for fertilizers is present at the top of the system. This inlet drops the fertilizer along with the water whenever required for that specific plants. A touch-display will be available for the user to obtain any of the internal conditions. A voice enabled device is attached which provides information about the internal processes taking place. A push notification will be sent to the farmers through the cloud service whenever any action is being taken internally.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123879139","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117286
A.N.M. Jubaer, A. Sayem, Md. Ashikur Rahman
Toxic comment classification problem is a popular classification problem nowadays. There are many attempts in English but it's rare in Bangla language. We tried to build a classifier for Bangla language. We tried different approach to find the optimized classifier with better accuracy and optimized for log-loss, hamming-loss. As this is a multilevel problem, we used binary relevance methods for binary classifiers.
{"title":"Bangla Toxic Comment Classification (Machine Learning and Deep Learning Approach)","authors":"A.N.M. Jubaer, A. Sayem, Md. Ashikur Rahman","doi":"10.1109/SMART46866.2019.9117286","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117286","url":null,"abstract":"Toxic comment classification problem is a popular classification problem nowadays. There are many attempts in English but it's rare in Bangla language. We tried to build a classifier for Bangla language. We tried different approach to find the optimized classifier with better accuracy and optimized for log-loss, hamming-loss. As this is a multilevel problem, we used binary relevance methods for binary classifiers.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116170443","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117458
M. Jagtap, R. Tripathi
Gaining popularity in digital world imposes the challenge to preserve the semantic significances in the original image while display on any arbitrary device irrespective of its size or aspect ratio is the well-known ‘Image Retargeting’. When the image is to be tailored by focusing on its objectives tenacity, then the insignificant portions of the images are identified and wipe out. The historical method envisages the due respect to the pixels by considering its bottom to top style. On the contrary, the projected method builds by using top-down tactic. This appraisal is fused by ‘Classification guided Fusion Network (CFN). The feature is widely applied on 3D images which fuses left as well as right eye images which are having different viewpoints and differently designed. The disparity map acquisition algorithm fuses the images with semantic collage of the images.
{"title":"A Novel 3-D Image Retargeting by using Stereo Seam Carving with Disparity Map Acquisition (DMA) Algorithm","authors":"M. Jagtap, R. Tripathi","doi":"10.1109/SMART46866.2019.9117458","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117458","url":null,"abstract":"Gaining popularity in digital world imposes the challenge to preserve the semantic significances in the original image while display on any arbitrary device irrespective of its size or aspect ratio is the well-known ‘Image Retargeting’. When the image is to be tailored by focusing on its objectives tenacity, then the insignificant portions of the images are identified and wipe out. The historical method envisages the due respect to the pixels by considering its bottom to top style. On the contrary, the projected method builds by using top-down tactic. This appraisal is fused by ‘Classification guided Fusion Network (CFN). The feature is widely applied on 3D images which fuses left as well as right eye images which are having different viewpoints and differently designed. The disparity map acquisition algorithm fuses the images with semantic collage of the images.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116928690","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117273
Md. Robel Mia, Amit Chakraborty Chhoton, Mahadi Hasan Mozumder, S. A. Hossain, Awolad Hossan
Bangladesh extensively depends on agriculture in terms of economy as well as food security for its huge population. For this reason, it is very important to efficiently grow a plant and enhance its yield. We often face some problem which need to be solved. We build a Mango Disease Recognition system which can recognize the mango disease. It's Very useful to the farmers because using this system they can easily identify their mango disease which is very important to produce more fruits. Using our system user can easily identify the problem and they can take action for better production. There also some existing project of similar topic but theses project are not available to the all users. More over some system recognize disease very poorly and there have less accuracy and it's a huge problem to use the system. Comparing other system our system can be use more efficiently. Recognition of Mango diseases poses two challenging problems, i.e. detection and classification of disease. In here we used K means clustering for feature extraction and SVM for classification. The novelty of our work is that here we recognize the mango diseases which is not existing and our project accuracy is 94.13%. So we think user will be benefited from our project to produce more product which can effect in our economy.
{"title":"An Approach for Mango Disease Recognition using K-Means Clustering and SVM Classifier","authors":"Md. Robel Mia, Amit Chakraborty Chhoton, Mahadi Hasan Mozumder, S. A. Hossain, Awolad Hossan","doi":"10.1109/SMART46866.2019.9117273","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117273","url":null,"abstract":"Bangladesh extensively depends on agriculture in terms of economy as well as food security for its huge population. For this reason, it is very important to efficiently grow a plant and enhance its yield. We often face some problem which need to be solved. We build a Mango Disease Recognition system which can recognize the mango disease. It's Very useful to the farmers because using this system they can easily identify their mango disease which is very important to produce more fruits. Using our system user can easily identify the problem and they can take action for better production. There also some existing project of similar topic but theses project are not available to the all users. More over some system recognize disease very poorly and there have less accuracy and it's a huge problem to use the system. Comparing other system our system can be use more efficiently. Recognition of Mango diseases poses two challenging problems, i.e. detection and classification of disease. In here we used K means clustering for feature extraction and SVM for classification. The novelty of our work is that here we recognize the mango diseases which is not existing and our project accuracy is 94.13%. So we think user will be benefited from our project to produce more product which can effect in our economy.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127050766","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117513
S. Chowdhury, Zerin Nasrin Tumpa, F. Khatun, S. F. Rabby
Crime is one of the major challenges of the world which is affecting the normal life and socio-economic development. Therefore, many governments are trying to use advanced technology to address or tackle such issues to maintain the peace of the country. So the analysis on Crime data has a great impact and value for the current scenario of the world. Nowadays, online newspaper is very popular among the people and contents varieties of crime news which can be a great source to understand the types and occurrence of crime. The aim of this paper is to monitor the crime, based on the headlines of the online newspaper provided in Twitter. Our approach is based on sentiment analysis by applying lexicon based methods and understand the crime categorized in a day, month, location and week. This piece of research work will help to deep understanding the pattern of the crime as well as the possibilities of occurrence of the crime in the specific time or day which will bear a great value to ensure the security purpose.
{"title":"Crime Monitoring from Newspaper Data based on Sentiment Analysis","authors":"S. Chowdhury, Zerin Nasrin Tumpa, F. Khatun, S. F. Rabby","doi":"10.1109/SMART46866.2019.9117513","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117513","url":null,"abstract":"Crime is one of the major challenges of the world which is affecting the normal life and socio-economic development. Therefore, many governments are trying to use advanced technology to address or tackle such issues to maintain the peace of the country. So the analysis on Crime data has a great impact and value for the current scenario of the world. Nowadays, online newspaper is very popular among the people and contents varieties of crime news which can be a great source to understand the types and occurrence of crime. The aim of this paper is to monitor the crime, based on the headlines of the online newspaper provided in Twitter. Our approach is based on sentiment analysis by applying lexicon based methods and understand the crime categorized in a day, month, location and week. This piece of research work will help to deep understanding the pattern of the crime as well as the possibilities of occurrence of the crime in the specific time or day which will bear a great value to ensure the security purpose.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129162851","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117280
S. Saxena, Mohammad Zubair Khan, Ravendra Singh
In the current scenario the demand for high performance computing system increases day by day to achieve maximum computation in minimum time. Rapid growth of Internet or Internet based services, increased the interest in network based computing or on-demand computing systems like cloud computing system. High computing servers are being deployed in large quantity for cloud computing in form of data Centers through which many different services on internet are provide to the cloud users in a very smooth and efficient manner. A large distributed system is described as a data center that includes a huge quantity of computing servers connected by an efficient network. So the consumption of energy in such data centers is enormously very high. Not only the maintenance of the data centers are too exorbitant, but also socially very harmful. High vitality costs and immense carbon footprints are brought in these data centers because the servers needed a substantial amount of electricity for their computation as well as for their cooling. As cost of energy increases and availability decreases, focus should be shifted towards the optimization of data centre servers for best performance alone with the policies of less energy consumption to justify the level of service performance with social impact. So in this paper we proposed energy aware consolidation technique for cloud data centers based on prediction of future client's requests to increase the utilization of computing servers as per request of users/clients which associated some demand of cloud resources for maintain the power consumption in cloud.
{"title":"Energy Saving Heuristics for Optimization of Cloud Data Center","authors":"S. Saxena, Mohammad Zubair Khan, Ravendra Singh","doi":"10.1109/SMART46866.2019.9117280","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117280","url":null,"abstract":"In the current scenario the demand for high performance computing system increases day by day to achieve maximum computation in minimum time. Rapid growth of Internet or Internet based services, increased the interest in network based computing or on-demand computing systems like cloud computing system. High computing servers are being deployed in large quantity for cloud computing in form of data Centers through which many different services on internet are provide to the cloud users in a very smooth and efficient manner. A large distributed system is described as a data center that includes a huge quantity of computing servers connected by an efficient network. So the consumption of energy in such data centers is enormously very high. Not only the maintenance of the data centers are too exorbitant, but also socially very harmful. High vitality costs and immense carbon footprints are brought in these data centers because the servers needed a substantial amount of electricity for their computation as well as for their cooling. As cost of energy increases and availability decreases, focus should be shifted towards the optimization of data centre servers for best performance alone with the policies of less energy consumption to justify the level of service performance with social impact. So in this paper we proposed energy aware consolidation technique for cloud data centers based on prediction of future client's requests to increase the utilization of computing servers as per request of users/clients which associated some demand of cloud resources for maintain the power consumption in cloud.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125602723","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117496
Mohammad Tamsir, A. Gahlot
This work presents numerical simulation of 2D Sine-Gordon equation (SGE) via modified extended cubic B-spline DQM (MECB-DQM). The ECB works as a basis function in DQM for computing the weighting coefficients of derivatives with respect to space variables. The SGE converts into system of ODEs by using these weighting coefficients which is solved by RK(5,4) method. Both the cases of damped and undamped are chosen for numerical simulation. Obtained results are more finer than the results available in literature and initiated a better correspondence with the exact and earlier numerical solutions. The analysis of ROC is also preformed.
{"title":"Numerical Simulation of 2D Nonlinear Sine-Gordon Soliton Waves via a DQM Based on Extended Cubic B-Splines","authors":"Mohammad Tamsir, A. Gahlot","doi":"10.1109/SMART46866.2019.9117496","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117496","url":null,"abstract":"This work presents numerical simulation of 2D Sine-Gordon equation (SGE) via modified extended cubic B-spline DQM (MECB-DQM). The ECB works as a basis function in DQM for computing the weighting coefficients of derivatives with respect to space variables. The SGE converts into system of ODEs by using these weighting coefficients which is solved by RK(5,4) method. Both the cases of damped and undamped are chosen for numerical simulation. Obtained results are more finer than the results available in literature and initiated a better correspondence with the exact and earlier numerical solutions. The analysis of ROC is also preformed.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126107767","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117470
Amit Sharma, Devesh Sharma
For design of any refrigerant and air conditioning equipment one needs an equation of state (EoS) to know its thermodynamic and thermo physical properties. Chlorofluorocarbons (CFCs) have been widely used in industries and commercial applications such as in cold storage and refrigerants. But CFCs have been banned and planned to complete phase out by 2030 because of their high ozone depletion and global warming potential. This work represent the comparison of Dieterici, van der waal, Berthelot, Redlich-Kwong and Peng-Robinson equation of states for the refrigerants are now is use in place of phased out refrigerants like-R-134a,R-152a in place of R12; R123 in place of R11and R 290 replacing R22. Criterion, kept in this work is to get vapour specific volume using EoS and comparison of calculated values is done with the experimental data from ASHRAE handbook. Percentage deviation and root mean square deviations are calculated for predicting best equation in different temperature ranges. For R-134a & R-152a Berthelot, for R-123 and R-22 Redlich-Kwong and Dieterici giving promising results.
对于任何制冷剂和空调设备的设计，都需要状态方程(EoS)来了解其热力学和热物理性质。氯氟烃(CFCs)已广泛用于工业和商业应用，如冷藏和制冷剂。但由于氯氟烃的高臭氧消耗和全球变暖潜力，它已被禁止使用，并计划在2030年之前完全淘汰。这项工作代表了Dieterici, van der waal, Berthelot, Redlich-Kwong和Peng-Robinson状态方程的比较，目前正在使用的制冷剂，以取代逐步淘汰的制冷剂，如- r -134a,R-152a代替R12;R123代替r11, r290代替R22。在这项工作中，保持的标准是使用EoS获得蒸汽比容，并将计算值与ASHRAE手册中的实验数据进行比较。计算了在不同温度范围内预测最佳方程的百分比偏差和均方根偏差。R-134a和R-152a的Berthelot, R-123和R-22的Redlich-Kwong和Dieterici给出了有希望的结果。
{"title":"Study of Dieterici and Two Constant EoS Models for R-134a, R-152a, R-123 and R-290","authors":"Amit Sharma, Devesh Sharma","doi":"10.1109/SMART46866.2019.9117470","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117470","url":null,"abstract":"For design of any refrigerant and air conditioning equipment one needs an equation of state (EoS) to know its thermodynamic and thermo physical properties. Chlorofluorocarbons (CFCs) have been widely used in industries and commercial applications such as in cold storage and refrigerants. But CFCs have been banned and planned to complete phase out by 2030 because of their high ozone depletion and global warming potential. This work represent the comparison of Dieterici, van der waal, Berthelot, Redlich-Kwong and Peng-Robinson equation of states for the refrigerants are now is use in place of phased out refrigerants like-R-134a,R-152a in place of R12; R123 in place of R11and R 290 replacing R22. Criterion, kept in this work is to get vapour specific volume using EoS and comparison of calculated values is done with the experimental data from ASHRAE handbook. Percentage deviation and root mean square deviations are calculated for predicting best equation in different temperature ranges. For R-134a & R-152a Berthelot, for R-123 and R-22 Redlich-Kwong and Dieterici giving promising results.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116332450","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117445
Abir Abdullha, Yeasin Habib, Md. Raisul Islam Masum, AKM SHAHARIAR AZAD RABBY
Most countries are now in a dangerous place for forestation and some are in developed forestation. So forestation and trees percentage prediction are to predict the condition of the countries about their condition of forestation and tress percentage. The paper is about a machine learning model to predict the countries condition. We used logistic regression, SVM AND Naive Bayes to predict the condition also for matrix. we also find the accuracy of logistic regression, SVM, Nave Bayes, Ada boosting classifier, Decision tree, ANN, Linear Discriminant Analysis, Gradient Boosting Classifier, MLP Classifier to find our best accuracy and compare with them with our data. we give details of selected algorithms. We collected some previous data and present data and comparing them to predict the condition of the country. we use some conditions and logic for machine learning. By logistic regression, SVM and Nave Bayes will show us the prediction and condition of those chosen countries.
{"title":"Countries Condition of Forestation and Trees Percentage using Machine learning","authors":"Abir Abdullha, Yeasin Habib, Md. Raisul Islam Masum, AKM SHAHARIAR AZAD RABBY","doi":"10.1109/SMART46866.2019.9117445","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117445","url":null,"abstract":"Most countries are now in a dangerous place for forestation and some are in developed forestation. So forestation and trees percentage prediction are to predict the condition of the countries about their condition of forestation and tress percentage. The paper is about a machine learning model to predict the countries condition. We used logistic regression, SVM AND Naive Bayes to predict the condition also for matrix. we also find the accuracy of logistic regression, SVM, Nave Bayes, Ada boosting classifier, Decision tree, ANN, Linear Discriminant Analysis, Gradient Boosting Classifier, MLP Classifier to find our best accuracy and compare with them with our data. we give details of selected algorithms. We collected some previous data and present data and comparing them to predict the condition of the country. we use some conditions and logic for machine learning. By logistic regression, SVM and Nave Bayes will show us the prediction and condition of those chosen countries.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115486436","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 : 2019-11-01DOI: 10.1109/SMART46866.2019.9117308
Harsh Karna, Vidhu Baggan, A. Sahoo, P. Sarangi
Some of the most effective routing protocols used in data transmission are (RIPv2), OSPF and EIGRP which stand for Routing Information Protocol, Open Shortest Path First (OSPF) and Enhanced Interior Gateway Routing Protocol (EIGRP) respectively. The main objective of this study is to execute a performance analysis of these protocols using parameters like Throughput, Jitter, Convergence Time, End-to-End delay and Packet Depletion through the simulated network models. Ten Generic routers are used in our simulated network topology using GNS-3(Graphical Network Stimulator). Based on the results, it can be observed that EIGRP routing protocol delivers a more superior performance as compared to OSPF routing protocol for real world applications. However, based on network variations we observe that EIGRP requires more computation than OSPF and hence consumes immense system power.
{"title":"Performance Analysis of Interior Gateway Protocols (IGPs) using GNS-3","authors":"Harsh Karna, Vidhu Baggan, A. Sahoo, P. Sarangi","doi":"10.1109/SMART46866.2019.9117308","DOIUrl":"https://doi.org/10.1109/SMART46866.2019.9117308","url":null,"abstract":"Some of the most effective routing protocols used in data transmission are (RIPv2), OSPF and EIGRP which stand for Routing Information Protocol, Open Shortest Path First (OSPF) and Enhanced Interior Gateway Routing Protocol (EIGRP) respectively. The main objective of this study is to execute a performance analysis of these protocols using parameters like Throughput, Jitter, Convergence Time, End-to-End delay and Packet Depletion through the simulated network models. Ten Generic routers are used in our simulated network topology using GNS-3(Graphical Network Stimulator). Based on the results, it can be observed that EIGRP routing protocol delivers a more superior performance as compared to OSPF routing protocol for real world applications. However, based on network variations we observe that EIGRP requires more computation than OSPF and hence consumes immense system power.","PeriodicalId":328124,"journal":{"name":"2019 8th International Conference System Modeling and Advancement in Research Trends (SMART)","volume":"47 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116400950","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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