Pub Date : 2016-07-06DOI: 10.1109/DIPDMWC.2016.7529409
Nikitha Johnsirani Venkatesan, Earl Kim, D. Shin
With rapid innovations and growing Internet population, petabytes of information are being generated every second. Processing these enormous data and analysing is a tedious process now-a-days. The amount of data in real-time is growing tremendously. Nearly 80% of the data is in unstructured format. Analysis of unstructured data in real-time is a very challenging task. Existing traditional business intelligence (BI) tools perform best only in a pre-defined schema. Most of the real-time data are logs and dont have any defined schema. Doing queries over these large datasets takes long time. During streaming of real-time data, much unwanted information is extracted from the data source causing overhead in the system. This results in an increase in the cost of construction and maintenance. Each and every second, new data streams keeps accumulating in the system consistently about whats going on in the world. Gathering these data and processing is an essential skill to know, for preparing a vital report. In this paper, we propose a Piece of News (PoN) end-to-end solution where we used the appropriate Hadoop components for real-time data analytics. Our aim is to extract the health data from the normal news data so that we can predict any real-time breakouts immediately. Rather than collecting all the news, we filtered only the important news based on certain threshold, thus reducing the cost. We compared historical data with real-time data which leads to take prompt action as we already knew the outbreaks from the previous data. One step ahead we can even detect any dangerous outbreaks before anyone else in the world. Not only we did real-time analytics using Hadoop componants but also we ran queries over the collected news dataset using Hive and Pig. Finally, we presented their performance comparison.
{"title":"PoN: Open source solution for real-time data analysis","authors":"Nikitha Johnsirani Venkatesan, Earl Kim, D. Shin","doi":"10.1109/DIPDMWC.2016.7529409","DOIUrl":"https://doi.org/10.1109/DIPDMWC.2016.7529409","url":null,"abstract":"With rapid innovations and growing Internet population, petabytes of information are being generated every second. Processing these enormous data and analysing is a tedious process now-a-days. The amount of data in real-time is growing tremendously. Nearly 80% of the data is in unstructured format. Analysis of unstructured data in real-time is a very challenging task. Existing traditional business intelligence (BI) tools perform best only in a pre-defined schema. Most of the real-time data are logs and dont have any defined schema. Doing queries over these large datasets takes long time. During streaming of real-time data, much unwanted information is extracted from the data source causing overhead in the system. This results in an increase in the cost of construction and maintenance. Each and every second, new data streams keeps accumulating in the system consistently about whats going on in the world. Gathering these data and processing is an essential skill to know, for preparing a vital report. In this paper, we propose a Piece of News (PoN) end-to-end solution where we used the appropriate Hadoop components for real-time data analytics. Our aim is to extract the health data from the normal news data so that we can predict any real-time breakouts immediately. Rather than collecting all the news, we filtered only the important news based on certain threshold, thus reducing the cost. We compared historical data with real-time data which leads to take prompt action as we already knew the outbreaks from the previous data. One step ahead we can even detect any dangerous outbreaks before anyone else in the world. Not only we did real-time analytics using Hadoop componants but also we ran queries over the collected news dataset using Hive and Pig. Finally, we presented their performance comparison.","PeriodicalId":298218,"journal":{"name":"2016 Third International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125243973","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 : 2016-07-06DOI: 10.1109/DIPDMWC.2016.7529355
Beibei Zhu, Xiaoyu Wu, Lei Yang, Yinghua Shen, Linglin Wu
Advances have been made continuously in detection networks such as SPPnet and Fast R-CNN. Recently the novel region proposal method RPN shares full-image convolutional features with the detection network and enables a state-of-the-art object detection network Faster R-CNN. In this work we apply Faster R-CNN to train a detection network on our digital image database of books and implement automatic recognition and positioning of books. Experiments show that retrained Faster R-CNN achieves fine detection results in terms of both speed and accuracy, and it also solves the problem of testing negative examples in our previous study. This provides great help for the study of practical book retrieval system.
{"title":"Automatic detection of books based on Faster R-CNN","authors":"Beibei Zhu, Xiaoyu Wu, Lei Yang, Yinghua Shen, Linglin Wu","doi":"10.1109/DIPDMWC.2016.7529355","DOIUrl":"https://doi.org/10.1109/DIPDMWC.2016.7529355","url":null,"abstract":"Advances have been made continuously in detection networks such as SPPnet and Fast R-CNN. Recently the novel region proposal method RPN shares full-image convolutional features with the detection network and enables a state-of-the-art object detection network Faster R-CNN. In this work we apply Faster R-CNN to train a detection network on our digital image database of books and implement automatic recognition and positioning of books. Experiments show that retrained Faster R-CNN achieves fine detection results in terms of both speed and accuracy, and it also solves the problem of testing negative examples in our previous study. This provides great help for the study of practical book retrieval system.","PeriodicalId":298218,"journal":{"name":"2016 Third International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129814100","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 : 2016-07-06DOI: 10.1109/DIPDMWC.2016.7529388
A. Epishkina, S. Zapechnikov
Big data analytics are very fruitful for solving problems in cybersecurity. We have analyzed modern trends in intelligent security systems research and practice and worked out a syllabus for a new university course in the area of data mining and machine learning with applications to cybersecurity. The course is for undergraduate and graduate students studying the cybersecurity. The main objective of the course is to provide students with fundamental concepts in data mining (in particular, mining frequent patterns, associations and correlations, classification, cluster analysis, outlier detection), machine learning (including neural networks, support vector machines etc.) and related issues, e.g. the basics of multidimensional statistics. Contrary to the traditional data mining and machine learning courses we illustrate course topics by cases from the area of cybersecurity including botnet detection, intrusion detection, deep packet inspection, fraud monitoring, malware detection, phishing detection, active authentication. We note that our course has great potential for development.
{"title":"A syllabus on data mining and machine learning with applications to cybersecurity","authors":"A. Epishkina, S. Zapechnikov","doi":"10.1109/DIPDMWC.2016.7529388","DOIUrl":"https://doi.org/10.1109/DIPDMWC.2016.7529388","url":null,"abstract":"Big data analytics are very fruitful for solving problems in cybersecurity. We have analyzed modern trends in intelligent security systems research and practice and worked out a syllabus for a new university course in the area of data mining and machine learning with applications to cybersecurity. The course is for undergraduate and graduate students studying the cybersecurity. The main objective of the course is to provide students with fundamental concepts in data mining (in particular, mining frequent patterns, associations and correlations, classification, cluster analysis, outlier detection), machine learning (including neural networks, support vector machines etc.) and related issues, e.g. the basics of multidimensional statistics. Contrary to the traditional data mining and machine learning courses we illustrate course topics by cases from the area of cybersecurity including botnet detection, intrusion detection, deep packet inspection, fraud monitoring, malware detection, phishing detection, active authentication. We note that our course has great potential for development.","PeriodicalId":298218,"journal":{"name":"2016 Third International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130492166","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}
In order to give more support to the research and development of large geophysical prospecting equipment like seismic prospecting instrument, this paper describes a design based on ADS1271 chip. The design applies to the large-scale cable digital telemetry seismograph and the development of distributed seismic acquisition unit of high precision but low power consumption, which uses high precision A/D conversion and FPGA embedded technology as well as micro-power consumption power source technology. The acquisition unit composes of data acquisition circuit board and FPGA master control circuit board. The acquisition board circuit consists of front end conditioning circuit, amplifying circuit, single-ended signal to differential signal conversion circuit, A/D switching circuit and power switching circuit; in the meanwhile a Cyclone IV E based FPGA master control board has been designed. For software, drive programs are designed for the acquisition board (including driver AD8253 and ADS1271) to achieve the function of data acquisition and the transfer of the acquisition unit.
为了更好地支持地震勘探仪等大型物探设备的研发，本文介绍了一种基于ADS1271芯片的设计方案。本设计应用于大型电缆数字遥测地震仪，采用高精度A/D转换和FPGA嵌入式技术以及微功耗电源技术，开发高精度低功耗的分布式地震采集单元。采集单元由数据采集电路板和FPGA主控电路板组成。采集板电路由前端调理电路、放大电路、单端信号到差分信号转换电路、A/D开关电路和功率开关电路组成;同时设计了基于Cyclone IV E的FPGA主控板。软件方面，为采集板设计驱动程序(包括AD8253和ADS1271驱动程序)，实现数据采集和采集单元的传输功能。
{"title":"Research and development of ADS1271 based distributed engineering seismic acquisition unit","authors":"Zhenzhong Yuan, Yongqing Wang, Shenghui Liu, Yu Wang, Xin-yue Zhang, M. Zhao, Qisheng Zhang","doi":"10.1109/DIPDMWC.2016.7529407","DOIUrl":"https://doi.org/10.1109/DIPDMWC.2016.7529407","url":null,"abstract":"In order to give more support to the research and development of large geophysical prospecting equipment like seismic prospecting instrument, this paper describes a design based on ADS1271 chip. The design applies to the large-scale cable digital telemetry seismograph and the development of distributed seismic acquisition unit of high precision but low power consumption, which uses high precision A/D conversion and FPGA embedded technology as well as micro-power consumption power source technology. The acquisition unit composes of data acquisition circuit board and FPGA master control circuit board. The acquisition board circuit consists of front end conditioning circuit, amplifying circuit, single-ended signal to differential signal conversion circuit, A/D switching circuit and power switching circuit; in the meanwhile a Cyclone IV E based FPGA master control board has been designed. For software, drive programs are designed for the acquisition board (including driver AD8253 and ADS1271) to achieve the function of data acquisition and the transfer of the acquisition unit.","PeriodicalId":298218,"journal":{"name":"2016 Third International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121399736","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 : 2016-07-06DOI: 10.1109/DIPDMWC.2016.7529381
S. Jafari, H. Taghavi, Mozhgan Yeganeh Daryakenari, Shirin Shahbazi
A very new issue in current age of marketing is mobile advertisement to which there is a little recognition on its effectiveness. Ignoring users' interests and needs as well as sending huge volume of mobile advertisements leads into wasting advertisement investment. Firms should utilize different strategies to design and send mobile advertisement. The developed model for this study considers affecting factors on intention to accept mobile advertisements by consumers. To test the research model, the data from a sample of 436 mobile users was gathered by judgment sampling method via questionnaire. Data analysis was conducted by structural equation modeling (SEM) in AMOS software. Results indicate that user's trust, entertainment, informativeness and ground determine 54% of changes in attitude toward accepting mobile advertisement. Additionally, trust in the third party has remarkable indirect impact on intention to accept this kind of advertisements.
{"title":"Impact of trust and perceived content of advertisement on intention to accept mobile advertisement","authors":"S. Jafari, H. Taghavi, Mozhgan Yeganeh Daryakenari, Shirin Shahbazi","doi":"10.1109/DIPDMWC.2016.7529381","DOIUrl":"https://doi.org/10.1109/DIPDMWC.2016.7529381","url":null,"abstract":"A very new issue in current age of marketing is mobile advertisement to which there is a little recognition on its effectiveness. Ignoring users' interests and needs as well as sending huge volume of mobile advertisements leads into wasting advertisement investment. Firms should utilize different strategies to design and send mobile advertisement. The developed model for this study considers affecting factors on intention to accept mobile advertisements by consumers. To test the research model, the data from a sample of 436 mobile users was gathered by judgment sampling method via questionnaire. Data analysis was conducted by structural equation modeling (SEM) in AMOS software. Results indicate that user's trust, entertainment, informativeness and ground determine 54% of changes in attitude toward accepting mobile advertisement. Additionally, trust in the third party has remarkable indirect impact on intention to accept this kind of advertisements.","PeriodicalId":298218,"journal":{"name":"2016 Third International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125459355","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 : 2016-07-06DOI: 10.1109/DIPDMWC.2016.7529376
L. Zotov, Elena Scheplova
Multichannel singular spectrum analysis (MSSA) is applied to the globally gridded oceanic angular momentum (OAM) data from ECCO (KF080) model, Atmospheric Angular Momentum from ECMWF model, and Earth gravity field from GRACE satellites. Principal components of the oceanic, atmospheric, and hydrological changes and their influence on the rotation of the Earth (polar motion PM and length of day LOD) are extracted. The regions where mass and motion terms make the largest input into PM excitation and LOD changes are identified. The trends, annual, and other global-scale modes are separated. Multichannel singular spectrum analysis is found to be a promising method for signal filtering and modes decomposition. Possible connections between climate change and Earth rotation are discussed.
{"title":"MSSA of globally gridded OAM from ECCO, AAM from ECMWF, and gravity from GRACE","authors":"L. Zotov, Elena Scheplova","doi":"10.1109/DIPDMWC.2016.7529376","DOIUrl":"https://doi.org/10.1109/DIPDMWC.2016.7529376","url":null,"abstract":"Multichannel singular spectrum analysis (MSSA) is applied to the globally gridded oceanic angular momentum (OAM) data from ECCO (KF080) model, Atmospheric Angular Momentum from ECMWF model, and Earth gravity field from GRACE satellites. Principal components of the oceanic, atmospheric, and hydrological changes and their influence on the rotation of the Earth (polar motion PM and length of day LOD) are extracted. The regions where mass and motion terms make the largest input into PM excitation and LOD changes are identified. The trends, annual, and other global-scale modes are separated. Multichannel singular spectrum analysis is found to be a promising method for signal filtering and modes decomposition. Possible connections between climate change and Earth rotation are discussed.","PeriodicalId":298218,"journal":{"name":"2016 Third International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC)","volume":"58 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124354376","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 : 2016-07-06DOI: 10.1109/DIPDMWC.2016.7529412
F. M. Khiyabani
Variational models of unconstrained optimization problems have been found in a variety of significant applications of research areas, such as image restoration. Among the QN methods, memoryless methods have been regarded effective techniques for solving large-scale problems that can be considered as one step limited memory QN methods. In this paper, we present an efficient memoryless symmetric rank-one (SR1) updating formula to compute meaningful solutions for large-scale problems arising in some image restoration problems. It is shown that the numerical experiments support the theoretical considerations for the usefulness of the proposed method. Meanwhile, comparisons on various well-known methods in the literature are presented to illustrate the effectiveness of the proposed method particularly for images of large size.
{"title":"Approximation SR1-based algorithms for nonlinear image processing","authors":"F. M. Khiyabani","doi":"10.1109/DIPDMWC.2016.7529412","DOIUrl":"https://doi.org/10.1109/DIPDMWC.2016.7529412","url":null,"abstract":"Variational models of unconstrained optimization problems have been found in a variety of significant applications of research areas, such as image restoration. Among the QN methods, memoryless methods have been regarded effective techniques for solving large-scale problems that can be considered as one step limited memory QN methods. In this paper, we present an efficient memoryless symmetric rank-one (SR1) updating formula to compute meaningful solutions for large-scale problems arising in some image restoration problems. It is shown that the numerical experiments support the theoretical considerations for the usefulness of the proposed method. Meanwhile, comparisons on various well-known methods in the literature are presented to illustrate the effectiveness of the proposed method particularly for images of large size.","PeriodicalId":298218,"journal":{"name":"2016 Third International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128663108","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 : 2016-07-06DOI: 10.1109/DIPDMWC.2016.7529379
K. Jariwala, U. Dalal, Amal Vincent
Gaze estimation is the process of determining the point of gaze in the space, or the visual axis of an eye. It plays an important role in representing human attention; therefore, it can be most appropriately used in Human Computer Interaction as a means of an advance computer input. Here, the focus is to develop a gaze estimation method for Human Computer Interaction using an ordinary webcam mounted on the top of the computer screen without any additional or specialized hardware. The eye center coordinates are obtained with the geometrical eye model and edge gradients. To improve the reliability, the estimates from two eye centers are combined to reduce the noise and improve the accuracy. Facial land marking is done to identify a precise reference point on the face between the nose. The ellipse fitting and RANSAC method is used to estimate the gaze coordinates and to reject the outliers. This approach can estimate the gaze coordinates with high degree of accuracy even when significant numbers of outliers are present in the data set. Several refinements such as feedback and masking, queuing and averaging are proposed to make the system more stable and useful practically. The results show that the proposed method can be successfully applied to commercial gaze tracking systems using ordinary webcams.
{"title":"A robust eye gaze estimation using geometric eye features","authors":"K. Jariwala, U. Dalal, Amal Vincent","doi":"10.1109/DIPDMWC.2016.7529379","DOIUrl":"https://doi.org/10.1109/DIPDMWC.2016.7529379","url":null,"abstract":"Gaze estimation is the process of determining the point of gaze in the space, or the visual axis of an eye. It plays an important role in representing human attention; therefore, it can be most appropriately used in Human Computer Interaction as a means of an advance computer input. Here, the focus is to develop a gaze estimation method for Human Computer Interaction using an ordinary webcam mounted on the top of the computer screen without any additional or specialized hardware. The eye center coordinates are obtained with the geometrical eye model and edge gradients. To improve the reliability, the estimates from two eye centers are combined to reduce the noise and improve the accuracy. Facial land marking is done to identify a precise reference point on the face between the nose. The ellipse fitting and RANSAC method is used to estimate the gaze coordinates and to reject the outliers. This approach can estimate the gaze coordinates with high degree of accuracy even when significant numbers of outliers are present in the data set. Several refinements such as feedback and masking, queuing and averaging are proposed to make the system more stable and useful practically. The results show that the proposed method can be successfully applied to commercial gaze tracking systems using ordinary webcams.","PeriodicalId":298218,"journal":{"name":"2016 Third International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127872823","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 : 2016-07-06DOI: 10.1109/DIPDMWC.2016.7529361
Divyansh Kaushik, Karamjit Kaur
In today's world where awareness for Breast Cancer is being carried out at a large scale, we still lack the diagnostic tools to suggest whether a person is suffering from Breast Cancer or not. Mammography remains the most significant method of diagnosing someone with Breast Cancer. However, mammograms sometimes are not definite due to which a radiologist cannot pronounce his/her decision based solely on them and has to resort to a biopsy. This paper proposes a data mining technique based on Ensemble of classifiers following data pre-processing, to predict the outcomes of the biopsy using the features extracted from the mammograms. The results achieved in this paper on the Mammographic Masses dataset are highly promising and have an accuracy of 83.5% and an ROC (Receiver Operating Characteristics) area of 0.907 which is higher than the existing approaches.
{"title":"Application of Data Mining for high accuracy prediction of breast tissue biopsy results","authors":"Divyansh Kaushik, Karamjit Kaur","doi":"10.1109/DIPDMWC.2016.7529361","DOIUrl":"https://doi.org/10.1109/DIPDMWC.2016.7529361","url":null,"abstract":"In today's world where awareness for Breast Cancer is being carried out at a large scale, we still lack the diagnostic tools to suggest whether a person is suffering from Breast Cancer or not. Mammography remains the most significant method of diagnosing someone with Breast Cancer. However, mammograms sometimes are not definite due to which a radiologist cannot pronounce his/her decision based solely on them and has to resort to a biopsy. This paper proposes a data mining technique based on Ensemble of classifiers following data pre-processing, to predict the outcomes of the biopsy using the features extracted from the mammograms. The results achieved in this paper on the Mammographic Masses dataset are highly promising and have an accuracy of 83.5% and an ROC (Receiver Operating Characteristics) area of 0.907 which is higher than the existing approaches.","PeriodicalId":298218,"journal":{"name":"2016 Third International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128847433","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 : 2016-07-06DOI: 10.1109/DIPDMWC.2016.7529403
Yaw-Chung Chen, Chun-Yu Liao
Nowadays multimedia streaming is running on mobile devices under WiFi networks. To send the same media stream to multiple receivers, multicast is usually considered for efficient data transmission. Since multicast frames won't be acknowledged, it is difficult to evaluate the QoS of data delivery over WiFi. In this work, we proposed a so called Statistic Collection multicast scheme based on X-beacon mechanism and corresponding MAC management messages for WiFi multicast. Our work features the following characteristics: (1) implements acknowledgement for multicast, (2) improves awareness on WiFi multicast, (3) measures transmission power and performs power-adjustment, and (4) extends the coverage for all receivers.
{"title":"A study of QoS feedback schemes on WiFi multicast for media streaming services","authors":"Yaw-Chung Chen, Chun-Yu Liao","doi":"10.1109/DIPDMWC.2016.7529403","DOIUrl":"https://doi.org/10.1109/DIPDMWC.2016.7529403","url":null,"abstract":"Nowadays multimedia streaming is running on mobile devices under WiFi networks. To send the same media stream to multiple receivers, multicast is usually considered for efficient data transmission. Since multicast frames won't be acknowledged, it is difficult to evaluate the QoS of data delivery over WiFi. In this work, we proposed a so called Statistic Collection multicast scheme based on X-beacon mechanism and corresponding MAC management messages for WiFi multicast. Our work features the following characteristics: (1) implements acknowledgement for multicast, (2) improves awareness on WiFi multicast, (3) measures transmission power and performs power-adjustment, and (4) extends the coverage for all receivers.","PeriodicalId":298218,"journal":{"name":"2016 Third International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116061583","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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