Pub Date : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9080011
Priya Gupta, K. Sandhu
With the incorporation of solar energy as a major chunk of the total installed capacity of INDIA (with respect to RES) there is an acute need to efficiently explore the potential it holds to procure the aforementioned grail. The technique used in this paper endeavours to achieve a nearly sinusoidal output from solar radiations incident on PV panels that can be consolidated in our system without deteriorating the power quality. Maximum power is attained by Perturb and Observe MPPT technique through boost converter. Voltage is the perturbing parameter in the P&O MPPT. The output achieved from three phase VSI is highly distorted due to harmonics, to eliminate this crucial drawback LCL filter is used to reduce the THD and thus ameliorate the output. All functions are performed and shown by the MATLAB/SIMULINK software.
{"title":"Analysis and MPPT control of PV module","authors":"Priya Gupta, K. Sandhu","doi":"10.1109/ICACCE46606.2019.9080011","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9080011","url":null,"abstract":"With the incorporation of solar energy as a major chunk of the total installed capacity of INDIA (with respect to RES) there is an acute need to efficiently explore the potential it holds to procure the aforementioned grail. The technique used in this paper endeavours to achieve a nearly sinusoidal output from solar radiations incident on PV panels that can be consolidated in our system without deteriorating the power quality. Maximum power is attained by Perturb and Observe MPPT technique through boost converter. Voltage is the perturbing parameter in the P&O MPPT. The output achieved from three phase VSI is highly distorted due to harmonics, to eliminate this crucial drawback LCL filter is used to reduce the THD and thus ameliorate the output. All functions are performed and shown by the MATLAB/SIMULINK software.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132289021","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9080005
Sudheendra Harwalkar, D. Sitaram, Shivangi Jadon
Disaster recovery (DR) for the distributed workload and data in multi-cloud environments is very complex and challenging. There exist point tools for failover from one cloud to another cloud with active/passive data replications or with simple backup of private cloud data to public cloud(s). However, these point solutions are not integrated with the cloud environment. In this paper, we demonstrate how cost-effective DR process/solution can be accomplished with our Federated Cloud Services Framework (middleware), which is built upon OpenStack [16], by leveraging existing OpenStack functionalities. As our solution leverages the functionality of the federated cloud environment, it generalizes easily to multi-cloud scenarios, and is better integrated with the cloud infrastructure. We also compare our solution to current DR process/solutions available in the market.
{"title":"Multi-cloud DRaaS using OpenStack Keystone Federation","authors":"Sudheendra Harwalkar, D. Sitaram, Shivangi Jadon","doi":"10.1109/ICACCE46606.2019.9080005","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9080005","url":null,"abstract":"Disaster recovery (DR) for the distributed workload and data in multi-cloud environments is very complex and challenging. There exist point tools for failover from one cloud to another cloud with active/passive data replications or with simple backup of private cloud data to public cloud(s). However, these point solutions are not integrated with the cloud environment. In this paper, we demonstrate how cost-effective DR process/solution can be accomplished with our Federated Cloud Services Framework (middleware), which is built upon OpenStack [16], by leveraging existing OpenStack functionalities. As our solution leverages the functionality of the federated cloud environment, it generalizes easily to multi-cloud scenarios, and is better integrated with the cloud infrastructure. We also compare our solution to current DR process/solutions available in the market.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124172147","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9079951
Subrata Das, A. Wahi, S. Sundaramurthy, N. Thulasiram, S. Keerthika
Classification of defects in knitted fabric is an active area of research around the globe. This paper presents a classification method to detect defects such as holes and thick places in knitted fabric. The work has been carried out in two phases. In the first phase the images of the defective samples of two classes were collected by a high resolution camera. The colour images of the samples were converted into grey scale images. The features were extracted from each grey scale image and stored in a database. In the second phase a neural classifier was trained with error back-propagation algorithm on the training dataset. After successful training of the neural network on train dataset, the performance of the trained neural network was evaluated on the test dataset. Different experiments were carried out by increasing the no of training data samples, it was found that the best evaluation performance was obtained as 83.3%.
{"title":"Classification of knitted fabric defect detection using Artificial Neural Networks","authors":"Subrata Das, A. Wahi, S. Sundaramurthy, N. Thulasiram, S. Keerthika","doi":"10.1109/ICACCE46606.2019.9079951","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9079951","url":null,"abstract":"Classification of defects in knitted fabric is an active area of research around the globe. This paper presents a classification method to detect defects such as holes and thick places in knitted fabric. The work has been carried out in two phases. In the first phase the images of the defective samples of two classes were collected by a high resolution camera. The colour images of the samples were converted into grey scale images. The features were extracted from each grey scale image and stored in a database. In the second phase a neural classifier was trained with error back-propagation algorithm on the training dataset. After successful training of the neural network on train dataset, the performance of the trained neural network was evaluated on the test dataset. Different experiments were carried out by increasing the no of training data samples, it was found that the best evaluation performance was obtained as 83.3%.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116591060","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9079986
R. S. Kumar, P. Anand, S. Karthick, R. N. Kumar, R. Poornachandran, N. Kumar
High Electron Mobility Transistor (HEMT) is currently playing a major role in electronics industries for low and high-power applications along with high frequency operations. In this paper, simulation of single gate enhancement mode InAs based composite channel MOSHEMT devices is performed for low power applications leading to the superior analog and RF performances. This performance is achieved by focusing the work towards the lattice matched composite channel, a recessed gate structure, HfO2 gate dielectric, and optimized source to drain spacing. The device performance characteristics are systematically analyzed with the optimized device dimensions of gate length (LG) = 50 nm, Barrier thickness (TB) = 3 nm, channel thickness (TCH) = 15 nm for the various gate to drain spacing. The reduction of a gate to drain spacing helps in minimizing the drain resistance and increased electron velocity. This effects in improving the transconductance (gm), drain current (ID), cutoff frequency (ft) along with the expense of short channel effects.
{"title":"Performance Analysis of Enhancement Mode Composite Channel MOSHEMT Device for Low Power Applications","authors":"R. S. Kumar, P. Anand, S. Karthick, R. N. Kumar, R. Poornachandran, N. Kumar","doi":"10.1109/ICACCE46606.2019.9079986","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9079986","url":null,"abstract":"High Electron Mobility Transistor (HEMT) is currently playing a major role in electronics industries for low and high-power applications along with high frequency operations. In this paper, simulation of single gate enhancement mode InAs based composite channel MOSHEMT devices is performed for low power applications leading to the superior analog and RF performances. This performance is achieved by focusing the work towards the lattice matched composite channel, a recessed gate structure, HfO2 gate dielectric, and optimized source to drain spacing. The device performance characteristics are systematically analyzed with the optimized device dimensions of gate length (LG) = 50 nm, Barrier thickness (TB) = 3 nm, channel thickness (TCH) = 15 nm for the various gate to drain spacing. The reduction of a gate to drain spacing helps in minimizing the drain resistance and increased electron velocity. This effects in improving the transconductance (gm), drain current (ID), cutoff frequency (ft) along with the expense of short channel effects.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122503757","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9079959
Shivani, K. Sandhu, Anil Ramchandran Nair
Due to depletion of conventional energy resources, the exploration of renewable energy resources has gained a lot of significance. Better forecasting models for the forthcoming supply of renewable energy resources are necessary to reduce the energy consumption from conventional power plants. Wind is a fluctuating kind of energy and accurately predicting the output power of wind energy is important to obtain optimal energy utilization in today's grid operation, dealing with the power load and pollution free atmosphere. This paper presents two machine learning tactics for short term wind power forecasting and that are Support Vector Regression (SVR) and Random Forest Regression (RFR). For this we take number of past observations of a series and that we have used to form the input pattern to train our both the models with which forecasts can be made for a present data point.
{"title":"Machine Learning approach for Short Term Wind Speed Forecasting","authors":"Shivani, K. Sandhu, Anil Ramchandran Nair","doi":"10.1109/ICACCE46606.2019.9079959","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9079959","url":null,"abstract":"Due to depletion of conventional energy resources, the exploration of renewable energy resources has gained a lot of significance. Better forecasting models for the forthcoming supply of renewable energy resources are necessary to reduce the energy consumption from conventional power plants. Wind is a fluctuating kind of energy and accurately predicting the output power of wind energy is important to obtain optimal energy utilization in today's grid operation, dealing with the power load and pollution free atmosphere. This paper presents two machine learning tactics for short term wind power forecasting and that are Support Vector Regression (SVR) and Random Forest Regression (RFR). For this we take number of past observations of a series and that we have used to form the input pattern to train our both the models with which forecasts can be made for a present data point.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126915658","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9080006
B. Gomathy, V. Nirmala
Agriculture is the backbone of India and it increases the economy of this country. Plant diseases detection plays a major role in agriculture. Quantity, quality or productivity is affected due to Plant diseases which are quite natural. Plant disease diagnosis is the most important activity for increasing the yield. The manual detection of Plant disease is time consuming due to lack of experts. Automatic methodologies using Image Processing methods will make the process easier. Delay in detection may destroy a big farm area. This paper presents the survey of different methods used in literature for disease diagnosis. From the analysis it's been reported in this paper that further improvements are required to diagnose diseases effectively.
{"title":"Survey on Plant diseases detection and Classification Techniques","authors":"B. Gomathy, V. Nirmala","doi":"10.1109/ICACCE46606.2019.9080006","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9080006","url":null,"abstract":"Agriculture is the backbone of India and it increases the economy of this country. Plant diseases detection plays a major role in agriculture. Quantity, quality or productivity is affected due to Plant diseases which are quite natural. Plant disease diagnosis is the most important activity for increasing the yield. The manual detection of Plant disease is time consuming due to lack of experts. Automatic methodologies using Image Processing methods will make the process easier. Delay in detection may destroy a big farm area. This paper presents the survey of different methods used in literature for disease diagnosis. From the analysis it's been reported in this paper that further improvements are required to diagnose diseases effectively.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134421569","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 number of road accidents has increased deliberately. This paper explores cooperative, intelligent and cognitive vehicular networks and examines how intelligent transportation systems make more efficient transportation in urban environments and offers comfort and luxurious travel. Driver's comfort and increased safety is among the priority factor of automation in the vehicle. It creates a need to develop a module to manage the outflow of the resources and to prevent road accidents. The advantage of the alerting system (using GSM module) offers the users or consumers the quickest response and the accurate detection of an emergency situation, which in turn helps in the faster diffusion of the critical situation. A prototype is proposed to design a physical system that will make driving safe and comfortable and outline a next generation vehicular networks technology.
{"title":"Intelligent Vehicular Networks","authors":"Shivani Rohilla, Ashutosh Deshwal, Lavanya Balasubramanian","doi":"10.1109/ICACCE46606.2019.9079957","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9079957","url":null,"abstract":"The number of road accidents has increased deliberately. This paper explores cooperative, intelligent and cognitive vehicular networks and examines how intelligent transportation systems make more efficient transportation in urban environments and offers comfort and luxurious travel. Driver's comfort and increased safety is among the priority factor of automation in the vehicle. It creates a need to develop a module to manage the outflow of the resources and to prevent road accidents. The advantage of the alerting system (using GSM module) offers the users or consumers the quickest response and the accurate detection of an emergency situation, which in turn helps in the faster diffusion of the critical situation. A prototype is proposed to design a physical system that will make driving safe and comfortable and outline a next generation vehicular networks technology.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133121855","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9079991
Gitanjali Ganpatrao Nikam, Simon Gupta, Priya Chourasiya, Medha Yadav
Numerous strategies are executed for the identification of peculiarities on the framework. Irregularities based strategies are looking at as proficient from that client purpose based methodology is favored for the Usage of oddity recognition. Presently multi day's decent variety of abnormality strategies are accessible In view of this, it is difficult to think about these strategies. To know this, diverse abnormality Identification is checked on and make a nitty-gritty examination in this. This paper contains examination consider of various oddity discovery strategies. Interruption perception has gained a wide consideration and turns into a gainful field for different looks into, and as yet is the subject of all-inclusive intrigue by specialists. The interruption recognition network still stands up to troublesome circumstance even after numerous long periods of research. Decreasing the tremendous number of wrong cautions all through the procedure of recognizing obscure assault designs stays vague issue. In any case, different research results as of late have appeared there are potential answers for this issue. Inconsistency identification is a key issue of interruption recognition in which Irritations of ordinary conduct determine an appearance of planned or unintended impact assaults, flaw, deformities, and others. This paper displays an outline of research bearings for applying composed and disorderly strategies to handle the issue of inconsistency discovery. The references referred to will cover the huge hypothetical issues lead the analyst in fascinating examination bearings.
{"title":"Object Tracking and Anomaly Detection in Live Environment: A Survey","authors":"Gitanjali Ganpatrao Nikam, Simon Gupta, Priya Chourasiya, Medha Yadav","doi":"10.1109/ICACCE46606.2019.9079991","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9079991","url":null,"abstract":"Numerous strategies are executed for the identification of peculiarities on the framework. Irregularities based strategies are looking at as proficient from that client purpose based methodology is favored for the Usage of oddity recognition. Presently multi day's decent variety of abnormality strategies are accessible In view of this, it is difficult to think about these strategies. To know this, diverse abnormality Identification is checked on and make a nitty-gritty examination in this. This paper contains examination consider of various oddity discovery strategies. Interruption perception has gained a wide consideration and turns into a gainful field for different looks into, and as yet is the subject of all-inclusive intrigue by specialists. The interruption recognition network still stands up to troublesome circumstance even after numerous long periods of research. Decreasing the tremendous number of wrong cautions all through the procedure of recognizing obscure assault designs stays vague issue. In any case, different research results as of late have appeared there are potential answers for this issue. Inconsistency identification is a key issue of interruption recognition in which Irritations of ordinary conduct determine an appearance of planned or unintended impact assaults, flaw, deformities, and others. This paper displays an outline of research bearings for applying composed and disorderly strategies to handle the issue of inconsistency discovery. The references referred to will cover the huge hypothetical issues lead the analyst in fascinating examination bearings.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127841195","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9080014
R. Priyadarshini, A. Banu, T. Nagamani
Human behavior prediction became an active research topic to determine the criminal and suspicious activities of a person. Gerontology deals with the everyday life activities of an individual including walking, climbing, eating, drinking, sitting and so on. It helps in ambient assisted living for the old persons in a self-reliant manner. The emergence of sensors and smart environment made the sensing process in an easier way. In general, the sensed dare classified using decision tree logic-based approach. The classification accuracy is low in case of decision tree approach. Hence, in this paper the gradient boosted tree is integrated with the decision tree approach to achieve greater accuracy. The triaccelerometer wearable sensor is used to collect the three-dimensional data of each activity of human being. The results showed that the integrated approach showed better accuracy and less error rate.
{"title":"Gradient Boosted Decision Tree based Classification for Recognizing Human Behavior","authors":"R. Priyadarshini, A. Banu, T. Nagamani","doi":"10.1109/ICACCE46606.2019.9080014","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9080014","url":null,"abstract":"Human behavior prediction became an active research topic to determine the criminal and suspicious activities of a person. Gerontology deals with the everyday life activities of an individual including walking, climbing, eating, drinking, sitting and so on. It helps in ambient assisted living for the old persons in a self-reliant manner. The emergence of sensors and smart environment made the sensing process in an easier way. In general, the sensed dare classified using decision tree logic-based approach. The classification accuracy is low in case of decision tree approach. Hence, in this paper the gradient boosted tree is integrated with the decision tree approach to achieve greater accuracy. The triaccelerometer wearable sensor is used to collect the three-dimensional data of each activity of human being. The results showed that the integrated approach showed better accuracy and less error rate.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121200541","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 : 2019-04-01DOI: 10.1109/ICACCE46606.2019.9080013
B. P. Lohani, Ajit Singh, Vimal Bibhu
Big data and its application are very popular now a day because due to technological advancement in the field of Information technology the amount of data generation rate is too high. Data Mining & analysis is done for making better decision with respect to the data generated from different sources. Decision making for the route in the traffic environment is also a problem of Big Data because it creates a huge amount of data so we need to optimize or seprate the data with respect to various criteria, for this we need to know about the optimization algorithms. Evolutionary Computing is a branch of Computer science which works upon the concept of Darwinian evolution and the evolutionary computing algorithms are used to find the optimal solution. The review of optimization algorithm is presented in this paper. For the optimization process we have selected Ant Colony optimization algorithm to find the best route and implemented the algorithm using the concept of Map reduce architecture for parallel processing.
{"title":"A hybrid optimization approach using Evolutionary Computing and Map Reduce Architecture","authors":"B. P. Lohani, Ajit Singh, Vimal Bibhu","doi":"10.1109/ICACCE46606.2019.9080013","DOIUrl":"https://doi.org/10.1109/ICACCE46606.2019.9080013","url":null,"abstract":"Big data and its application are very popular now a day because due to technological advancement in the field of Information technology the amount of data generation rate is too high. Data Mining & analysis is done for making better decision with respect to the data generated from different sources. Decision making for the route in the traffic environment is also a problem of Big Data because it creates a huge amount of data so we need to optimize or seprate the data with respect to various criteria, for this we need to know about the optimization algorithms. Evolutionary Computing is a branch of Computer science which works upon the concept of Darwinian evolution and the evolutionary computing algorithms are used to find the optimal solution. The review of optimization algorithm is presented in this paper. For the optimization process we have selected Ant Colony optimization algorithm to find the best route and implemented the algorithm using the concept of Map reduce architecture for parallel processing.","PeriodicalId":317123,"journal":{"name":"2019 International Conference on Advances in Computing and Communication Engineering (ICACCE)","volume":"229 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126040150","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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