Pub Date : 2016-12-01DOI: 10.1109/IC3I.2016.7917987
K. Pradeep, N. Naveen
Diabetes is a severe disease within which the deceased cannot appropriately manage the amount of sugar in the blood since it does not have adequate insulin, it is also a situation within which the extent of blood glucose stage is elevated than regular. In the area of medicine to discover patient's data as well as to attain a predictive model or a set of rules, Classification techniques have been persistently used. The key purpose of this is to explore and facilitate a better diagnosis of diabetes by predicting the blood glucose level in advance that is before 2 hours. Presently there are quite a lot of other methodologies do endure on classification for the diabetes disease (DD). The planned methodology that has been adopted for the classification and prediction, on the selected feature is J48 Decision Tree algorithm. Primal Diagnosis of DD provides a way with less cost which is always preferable. J48 algorithm is noted for its accuracy.
{"title":"Predictive analysis of diabetes using J48 algorithm of classification techniques","authors":"K. Pradeep, N. Naveen","doi":"10.1109/IC3I.2016.7917987","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917987","url":null,"abstract":"Diabetes is a severe disease within which the deceased cannot appropriately manage the amount of sugar in the blood since it does not have adequate insulin, it is also a situation within which the extent of blood glucose stage is elevated than regular. In the area of medicine to discover patient's data as well as to attain a predictive model or a set of rules, Classification techniques have been persistently used. The key purpose of this is to explore and facilitate a better diagnosis of diabetes by predicting the blood glucose level in advance that is before 2 hours. Presently there are quite a lot of other methodologies do endure on classification for the diabetes disease (DD). The planned methodology that has been adopted for the classification and prediction, on the selected feature is J48 Decision Tree algorithm. Primal Diagnosis of DD provides a way with less cost which is always preferable. J48 algorithm is noted for its accuracy.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132511542","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7917930
Samiya Khan, K. A. Shakil, Mansaf Alam
Big Data technology is a generic technology, which can be applied to any real-world problem that involves a lot of data. Moreover, the use of cloud-based infrastructure to implement the big data technology makes it a cost-effective solution to the big data problem. One of the fundamental sectors that can benefit from this technology is education and research. The education system can use big data analytics to provide better education and administer the institutional operations. Research, which is an extension of education, can use analytics of big scholar data, for diverse applications, to facilitate research at the individual, team and organization level. With that said, the practical implementation and adoption of big data for education and research, collectively referred to as ‘Educational Intelligence’, faces several challenges, particularly in a developing country like India. This research paper explores how cloud-based big data analytics can be applied to Indian education and research and reviews the challenges that need to be addressed before the true benefits of this technology can be obtained.
{"title":"Educational intelligence: Applying cloud-based big data analytics to the Indian education sector","authors":"Samiya Khan, K. A. Shakil, Mansaf Alam","doi":"10.1109/IC3I.2016.7917930","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917930","url":null,"abstract":"Big Data technology is a generic technology, which can be applied to any real-world problem that involves a lot of data. Moreover, the use of cloud-based infrastructure to implement the big data technology makes it a cost-effective solution to the big data problem. One of the fundamental sectors that can benefit from this technology is education and research. The education system can use big data analytics to provide better education and administer the institutional operations. Research, which is an extension of education, can use analytics of big scholar data, for diverse applications, to facilitate research at the individual, team and organization level. With that said, the practical implementation and adoption of big data for education and research, collectively referred to as ‘Educational Intelligence’, faces several challenges, particularly in a developing country like India. This research paper explores how cloud-based big data analytics can be applied to Indian education and research and reviews the challenges that need to be addressed before the true benefits of this technology can be obtained.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133139199","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7918062
Mantinder Jit Singh, Prakhar Agarwal, K. Padmanabh
Energy Consumption in a neighborhood depends upon its socioeconomic parameters. Demographical diversities in a neighborhood in India warrants load prediction at distribution transformer (DT) rather than at utility level. In this paper two interesting techniques of load forecasting have been proposed which have not be explored till date. In both these technique a unique pattern of consumption has been deciphered for a day using parametric estimation and subsequently regression, neural network and support vector regression have been used to find the total consumption of the day which is subsequently redistributed according to pattern of the day to deduce final load pattern. In the first technique a unique model has been created for each day of the week. Though the results have been very encouraging with average error of 12% however it is not sufficient for many applications. In the second approach a set of model is created for the entire year and depending upon the previous pattern. A particular model having correlation more than 95% and similar total consumption is selected out of these models. In this case mean error has been reported as approximately 7%. Neural network considers all factors affecting the consumption and hence its corresponding predictions have been found more accurate.
{"title":"Load forecasting at distribution transformer using IoT based smart meter data from 6000 Irish homes","authors":"Mantinder Jit Singh, Prakhar Agarwal, K. Padmanabh","doi":"10.1109/IC3I.2016.7918062","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7918062","url":null,"abstract":"Energy Consumption in a neighborhood depends upon its socioeconomic parameters. Demographical diversities in a neighborhood in India warrants load prediction at distribution transformer (DT) rather than at utility level. In this paper two interesting techniques of load forecasting have been proposed which have not be explored till date. In both these technique a unique pattern of consumption has been deciphered for a day using parametric estimation and subsequently regression, neural network and support vector regression have been used to find the total consumption of the day which is subsequently redistributed according to pattern of the day to deduce final load pattern. In the first technique a unique model has been created for each day of the week. Though the results have been very encouraging with average error of 12% however it is not sufficient for many applications. In the second approach a set of model is created for the entire year and depending upon the previous pattern. A particular model having correlation more than 95% and similar total consumption is selected out of these models. In this case mean error has been reported as approximately 7%. Neural network considers all factors affecting the consumption and hence its corresponding predictions have been found more accurate.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133153111","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7917985
B. Misra, B. Nayak
Grid-tied distributed energy sources needs a proper synchronization technique which will estimate the phase angle of the grid voltage. The most common synchronisation techniques are being the phase locked loops (PLL)s, which decides the quality of grid utility power. By using different filtering techniques, the disturbance rejection capability in the (PLL)s can be improved. Synchronous reference frame phase locked loop (SRF-PLL) is the most commonly used synchronisation technique because of its simple operation good dynamic response. The conventional (SRF-PLL) controller with high bandwidth when used for synchronization work provides satisfactory performance when the grid voltage is undistorted and balanced. However SRF-PLL does not work properly in case of distorted and polluted grid conditions, so the estimated phase can have a substantial amount of unnecessary ripple. In case the grid voltage is balanced but polluted with higher order harmonic with reasonable amplitude, the detection system bandwidth can be reduced in order to attenuate the effect of harmonics on the output. Here second order adaptive filters (SOAF) are used to extract the harmonic components existing in balanced and polluted harmonic grid signals.
{"title":"Performance analysis of second order adaptive filter using Matlab Simulink","authors":"B. Misra, B. Nayak","doi":"10.1109/IC3I.2016.7917985","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917985","url":null,"abstract":"Grid-tied distributed energy sources needs a proper synchronization technique which will estimate the phase angle of the grid voltage. The most common synchronisation techniques are being the phase locked loops (PLL)s, which decides the quality of grid utility power. By using different filtering techniques, the disturbance rejection capability in the (PLL)s can be improved. Synchronous reference frame phase locked loop (SRF-PLL) is the most commonly used synchronisation technique because of its simple operation good dynamic response. The conventional (SRF-PLL) controller with high bandwidth when used for synchronization work provides satisfactory performance when the grid voltage is undistorted and balanced. However SRF-PLL does not work properly in case of distorted and polluted grid conditions, so the estimated phase can have a substantial amount of unnecessary ripple. In case the grid voltage is balanced but polluted with higher order harmonic with reasonable amplitude, the detection system bandwidth can be reduced in order to attenuate the effect of harmonics on the output. Here second order adaptive filters (SOAF) are used to extract the harmonic components existing in balanced and polluted harmonic grid signals.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116430009","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7917989
Somjit Nath, Paramita Banerjee, R. Biswas, S. Mitra, M. K. Naskar
The system proposed is a door unlocking system containing multiple doors any of which can be used to access a certain zone e.g. a laboratory or library. The system is implemented using a central server which contains a central database gathering all the information about the authorized personnel. The hardware components required are RFID reader, passive RFID tags, wireless transmitter & receiver (433 MHz) and an Arduino microcontroller. Software assistance of Arduino IDE and Processing Development Environment (PDE) are required for control. There is also provision for real-time monitoring of users' activities i.e. entry and exit. This is made possible by automatic synchronization of the system with a secured webpage via internet.
提出的系统是一个包含多个门的门解锁系统，其中任何一个门都可以用于进入特定区域，例如实验室或图书馆。该系统使用中央服务器来实现，该服务器包含一个中央数据库，收集有关授权人员的所有信息。所需的硬件组件是RFID阅读器，无源RFID标签，无线发射器和接收器(433 MHz)和Arduino微控制器。控制需要Arduino IDE和Processing Development Environment (PDE)的软件辅助。还提供了对用户活动的实时监控，即进入和退出。这是通过互联网自动同步系统与安全网页。
{"title":"Arduino based door unlocking system with real time control","authors":"Somjit Nath, Paramita Banerjee, R. Biswas, S. Mitra, M. K. Naskar","doi":"10.1109/IC3I.2016.7917989","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917989","url":null,"abstract":"The system proposed is a door unlocking system containing multiple doors any of which can be used to access a certain zone e.g. a laboratory or library. The system is implemented using a central server which contains a central database gathering all the information about the authorized personnel. The hardware components required are RFID reader, passive RFID tags, wireless transmitter & receiver (433 MHz) and an Arduino microcontroller. Software assistance of Arduino IDE and Processing Development Environment (PDE) are required for control. There is also provision for real-time monitoring of users' activities i.e. entry and exit. This is made possible by automatic synchronization of the system with a secured webpage via internet.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116739145","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7917947
A. Abbas, H. Qasem
Development of algorithms for discovering the location of nodes in a wireless sensor network is a task that offers a lot challenges to the research community. In this paper, we present a protocol for locating nodes in a wireless sensor network. The proposed protocol follows a locate-promote and split strategy. We analyze the number of iterations needed to locate almost all nodes in a network and the delays incurred in the process of localization. We show that the rate of localization of the proposed protocol in terms of the number of nodes localized with respect to the number of iterations is exponential.
{"title":"Locate, promote and split: An exponentially fast localization algorithm for wireless sensor networks","authors":"A. Abbas, H. Qasem","doi":"10.1109/IC3I.2016.7917947","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917947","url":null,"abstract":"Development of algorithms for discovering the location of nodes in a wireless sensor network is a task that offers a lot challenges to the research community. In this paper, we present a protocol for locating nodes in a wireless sensor network. The proposed protocol follows a locate-promote and split strategy. We analyze the number of iterations needed to locate almost all nodes in a network and the delays incurred in the process of localization. We show that the rate of localization of the proposed protocol in terms of the number of nodes localized with respect to the number of iterations is exponential.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131917642","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7918057
D. Thara, B. Premasudha, V. Ram, R. Suma
As the volume of data generating is increasing day by day in this internet world, the term Big Data is becoming a very popular buzzword in today's market. Big Data is used in various sectors of the internet world. In this paper an effort is made to demonstrate that even the healthcare industries are stepping into Big Data pool to take all benefits from its various advanced tools and technologies. The paper presents the review of various research efforts made in healthcare domain using Big Data concepts and methodologies. The thought of Big Data can be used for better health planning. Its methodologies can be used for healthcare data analytics which helps in better decision making to increase the business value and customer interest and to provide eHealth services among various healthcare stakeholders by using messaging standards like Health Level?, Digital Imaging and Communications in Medicine (DICOM), Health Insurance Portability and Accountability (HIPAA), message broker etc. Big Data techniques can be applied to develop systems for the early diagnosis of disease, understand connection between HATS (HIV/AIDS Tuberculosis and Silicosis) and also to develop integrated data analytics platforms. After presenting these many positive progresses of Big Data on healthcare, the paper also presents the hurdles faced by healthcare systems in using Big Data technologies. Further the paper includes the list of various Big Data tools, few case studies, few applications which are worth implementing using Big Data in healthcare followed by the concluding remarks.
{"title":"Impact of big data in healthcare: A survey","authors":"D. Thara, B. Premasudha, V. Ram, R. Suma","doi":"10.1109/IC3I.2016.7918057","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7918057","url":null,"abstract":"As the volume of data generating is increasing day by day in this internet world, the term Big Data is becoming a very popular buzzword in today's market. Big Data is used in various sectors of the internet world. In this paper an effort is made to demonstrate that even the healthcare industries are stepping into Big Data pool to take all benefits from its various advanced tools and technologies. The paper presents the review of various research efforts made in healthcare domain using Big Data concepts and methodologies. The thought of Big Data can be used for better health planning. Its methodologies can be used for healthcare data analytics which helps in better decision making to increase the business value and customer interest and to provide eHealth services among various healthcare stakeholders by using messaging standards like Health Level?, Digital Imaging and Communications in Medicine (DICOM), Health Insurance Portability and Accountability (HIPAA), message broker etc. Big Data techniques can be applied to develop systems for the early diagnosis of disease, understand connection between HATS (HIV/AIDS Tuberculosis and Silicosis) and also to develop integrated data analytics platforms. After presenting these many positive progresses of Big Data on healthcare, the paper also presents the hurdles faced by healthcare systems in using Big Data technologies. Further the paper includes the list of various Big Data tools, few case studies, few applications which are worth implementing using Big Data in healthcare followed by the concluding remarks.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132744261","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7917925
N. Gandhi, L. Armstrong
This paper provides a review of research on the application of data mining techniques for decision making in agriculture. The paper reports the application of a number of data mining techniques including artificial neural networks, Bayesian networks and support vector machines. The review has outlined a number of promising techniques that have been used to understand the relationships of various climate and other factors on crop production. This review proposes that further investigations are needed to understand how these techniques can be used with complex agricultural datasets for crop yield prediction integrating seasonal and spatial factors by using GIS technologies.
{"title":"A review of the application of data mining techniques for decision making in agriculture","authors":"N. Gandhi, L. Armstrong","doi":"10.1109/IC3I.2016.7917925","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917925","url":null,"abstract":"This paper provides a review of research on the application of data mining techniques for decision making in agriculture. The paper reports the application of a number of data mining techniques including artificial neural networks, Bayesian networks and support vector machines. The review has outlined a number of promising techniques that have been used to understand the relationships of various climate and other factors on crop production. This review proposes that further investigations are needed to understand how these techniques can be used with complex agricultural datasets for crop yield prediction integrating seasonal and spatial factors by using GIS technologies.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133455465","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7918008
Brinzel Rodrigues, Anita Chaudhari, Shraddha S. More
The use of QR code-based technologies and systems has become a current trend in recent years where QR codes are acknowledged to be a practical and interesting data representation and processing mechanism amongst worldwide users. Our aim is to design and implement a two-factor identification authentication system with the use of QR codes and to make the relevant mechanism and process that could be more convenient for the user to use and practical than one time password (OTP) mechanisms used with similar intentions today. One time password (OTP) mechanisms are vulnerable since they can be compromised using man-in-the-middle attack, phishing, spoofing, etc. This system provides another level of security where QR code acts as the first factor and the android mobile acts as the second factor.
{"title":"Two factor verification using QR-code: A unique authentication system for Android smartphone users","authors":"Brinzel Rodrigues, Anita Chaudhari, Shraddha S. More","doi":"10.1109/IC3I.2016.7918008","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7918008","url":null,"abstract":"The use of QR code-based technologies and systems has become a current trend in recent years where QR codes are acknowledged to be a practical and interesting data representation and processing mechanism amongst worldwide users. Our aim is to design and implement a two-factor identification authentication system with the use of QR codes and to make the relevant mechanism and process that could be more convenient for the user to use and practical than one time password (OTP) mechanisms used with similar intentions today. One time password (OTP) mechanisms are vulnerable since they can be compromised using man-in-the-middle attack, phishing, spoofing, etc. This system provides another level of security where QR code acts as the first factor and the android mobile acts as the second factor.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132428714","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 : 2016-12-01DOI: 10.1109/IC3I.2016.7917991
M. U. Farooq, K. Khan, Salwa Mohammed
Data dissemination is a major area of concern in VANETS because they are highly dynamic in nature. Many researchers have introduced several technologies for dissemination of data. We address this problem of vehicular communication in hybrid networks and present a mechanism for efficient dissemination of data in VANETS. In this paper we analyze some of the existing solutions in order to overcome the drawbacks of these solutions. Here we propose two solutions which are used for controlling broadcast storm problem. The first solution is unidirectional flooding and second is Selection flooding using Knapsack method. These methods are being applied to the infrastructural support of inter-vehicle, inter-roadside and vehicle-to-roadside communications in hybrid networks.
{"title":"Selective flooding techniques for dissemination in VANETs","authors":"M. U. Farooq, K. Khan, Salwa Mohammed","doi":"10.1109/IC3I.2016.7917991","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917991","url":null,"abstract":"Data dissemination is a major area of concern in VANETS because they are highly dynamic in nature. Many researchers have introduced several technologies for dissemination of data. We address this problem of vehicular communication in hybrid networks and present a mechanism for efficient dissemination of data in VANETS. In this paper we analyze some of the existing solutions in order to overcome the drawbacks of these solutions. Here we propose two solutions which are used for controlling broadcast storm problem. The first solution is unidirectional flooding and second is Selection flooding using Knapsack method. These methods are being applied to the infrastructural support of inter-vehicle, inter-roadside and vehicle-to-roadside communications in hybrid networks.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126087518","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：