Pub Date : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.00-10
Yosuke Seki
Dialogue systems, which give users quick and easy access to required information interactively, have been widely used in various fields. To increase user satisfaction, it is important to analyze usage status in detail after introduction of dialogue systems. However, since usage status is analyzed from a large number of logs and other collected information, it can take much time and effort to find beneficial information. This study proposes a method that utilizes the dialogue system introduced for public relations in universities to support the analysis of usage status by visualization, aiming discovery by intuitive awareness. In the results of evaluation using real data of the dialogue system, a variety of information that matches different purposes and unexpected information were discovered by intuitive awareness and supporting functions.
{"title":"Visualization for Analyzing Usage Status from Dialogue Systems","authors":"Yosuke Seki","doi":"10.1109/COMPSAC48688.2020.00-10","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.00-10","url":null,"abstract":"Dialogue systems, which give users quick and easy access to required information interactively, have been widely used in various fields. To increase user satisfaction, it is important to analyze usage status in detail after introduction of dialogue systems. However, since usage status is analyzed from a large number of logs and other collected information, it can take much time and effort to find beneficial information. This study proposes a method that utilizes the dialogue system introduced for public relations in universities to support the analysis of usage status by visualization, aiming discovery by intuitive awareness. In the results of evaluation using real data of the dialogue system, a variety of information that matches different purposes and unexpected information were discovered by intuitive awareness and supporting functions.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"236 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133398416","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.00-55
Higor Pereira Delfino, R. M. Costa, J. P. Félix, João Gabriel Junqueira da Silva, Hedenir Monteiro Pinheiro, V. Siqueira, E. Camilo, D. Fernandes, Fabrízzio Soares
This work aims to investigate, by means of a Systematic Literature Review, to evaluate the current state of the use of artificial intelligence in automated pupillometric technology and its application in helping to diagnose diseases, to identify the methods and equipment used and propose case new equipment based on computer vision is feasible. We also investigated the accuracy of methodologies and equipment that use computerized pupilometry to identify pathologies or disorders, as well as the viability and usability of existing pupilometers. In this sense, creating a pupilometer capable of stimulating and varying wavelengths, providing an interface to preview the exam, and embedding the classification algorithms is a great challenge. In this systematic review of the literature, we consider publications from the last ten years (2010 - 2020) indexed by seven solid scientific databases. The review identified a vast amount of work on pupillometry; however, a small amount related to the construction and viability of a pupilometer with an embedded system, easy to use and with a preview interface. Having identified this, we propose a new methodology for the construction of the pupilometer as well as the algorithm for extracting the characteristics through pupilometry.
{"title":"Techniques and Equipment for Automated Pupillometry and its Application to Aid in the Diagnosis of Diseases: A Literature Review","authors":"Higor Pereira Delfino, R. M. Costa, J. P. Félix, João Gabriel Junqueira da Silva, Hedenir Monteiro Pinheiro, V. Siqueira, E. Camilo, D. Fernandes, Fabrízzio Soares","doi":"10.1109/COMPSAC48688.2020.00-55","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.00-55","url":null,"abstract":"This work aims to investigate, by means of a Systematic Literature Review, to evaluate the current state of the use of artificial intelligence in automated pupillometric technology and its application in helping to diagnose diseases, to identify the methods and equipment used and propose case new equipment based on computer vision is feasible. We also investigated the accuracy of methodologies and equipment that use computerized pupilometry to identify pathologies or disorders, as well as the viability and usability of existing pupilometers. In this sense, creating a pupilometer capable of stimulating and varying wavelengths, providing an interface to preview the exam, and embedding the classification algorithms is a great challenge. In this systematic review of the literature, we consider publications from the last ten years (2010 - 2020) indexed by seven solid scientific databases. The review identified a vast amount of work on pupillometry; however, a small amount related to the construction and viability of a pupilometer with an embedded system, easy to use and with a preview interface. Having identified this, we propose a new methodology for the construction of the pupilometer as well as the algorithm for extracting the characteristics through pupilometry.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133866268","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.00-72
Shuvalaxmi Dass, Xiaozhen Xue, A. Namin
The performance of coverage-based fault localization greatly depends on the quality of test cases being executed. These test cases execute some lines of the given program and determine whether the underlying tests are passed or failed. In particular, some test cases may be well-behaved (i.e., passed) while executing faulty statements. These test cases, also known as coincidentally correct test cases, may negatively influence the performance of the spectra-based fault localization and thus be less helpful as a tool for the purpose of automated debugging. In other words, the involvement of these coincidentally correct test cases may introduce noises to the fault localization computation and thus cause in divergence of effectively localizing the location of possible bugs in the given code. In this paper, we propose a hybrid approach of ensemble learning combined with a supervised learning algorithm namely, Random Forests (RF) for the purpose of correctly identifying test cases that are mislabeled to be the passing test cases. A cost-effective analysis of flipping the test status or trimming (i.e., eliminating from the computation) the coincidental correct test cases is also reported.
{"title":"Ensemble Random Forests Classifier for Detecting Coincidentally Correct Test Cases","authors":"Shuvalaxmi Dass, Xiaozhen Xue, A. Namin","doi":"10.1109/COMPSAC48688.2020.00-72","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.00-72","url":null,"abstract":"The performance of coverage-based fault localization greatly depends on the quality of test cases being executed. These test cases execute some lines of the given program and determine whether the underlying tests are passed or failed. In particular, some test cases may be well-behaved (i.e., passed) while executing faulty statements. These test cases, also known as coincidentally correct test cases, may negatively influence the performance of the spectra-based fault localization and thus be less helpful as a tool for the purpose of automated debugging. In other words, the involvement of these coincidentally correct test cases may introduce noises to the fault localization computation and thus cause in divergence of effectively localizing the location of possible bugs in the given code. In this paper, we propose a hybrid approach of ensemble learning combined with a supervised learning algorithm namely, Random Forests (RF) for the purpose of correctly identifying test cases that are mislabeled to be the passing test cases. A cost-effective analysis of flipping the test status or trimming (i.e., eliminating from the computation) the coincidental correct test cases is also reported.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122931270","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.0-151
Layan Etaiwi, Sylvie Hamel, Yann-Gaël Guéhéneuc, William Flageol, Rodrigo Morales
The continuous growth of the mobile apps industry creates a competition among apps developers. To succeed, app developers must attract and retain users. User reviews provide a wealth of information about bugs to fix and features to add and can help app developers offer high-quality apps. However, apps may receive hundreds of unstructured reviews, which makes transforming them into change requests a difficult task. Approaches exist for analyzing and extracting topics from mobile app reviews, however, prioritizing these reviews has not gained much attention. In this study, we introduce the use of a consensus algorithm to help developers prioritize user reviews for the purpose of app evolution. We evaluate the usefulness of our approach and meaningfulness of its consensus rankings on four Android apps. We compare the rankings against reviews ranked by app developers manually and show that there is a strong correlation between the two (average Kendall rank correlation coefficient = 0.516). Thus, our approach can prioritize user reviews and help developers focus their time/effort on improving their apps instead of on identifying reviews to address in the next release.
{"title":"Order in Chaos: Prioritizing Mobile App Reviews using Consensus Algorithms","authors":"Layan Etaiwi, Sylvie Hamel, Yann-Gaël Guéhéneuc, William Flageol, Rodrigo Morales","doi":"10.1109/COMPSAC48688.2020.0-151","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.0-151","url":null,"abstract":"The continuous growth of the mobile apps industry creates a competition among apps developers. To succeed, app developers must attract and retain users. User reviews provide a wealth of information about bugs to fix and features to add and can help app developers offer high-quality apps. However, apps may receive hundreds of unstructured reviews, which makes transforming them into change requests a difficult task. Approaches exist for analyzing and extracting topics from mobile app reviews, however, prioritizing these reviews has not gained much attention. In this study, we introduce the use of a consensus algorithm to help developers prioritize user reviews for the purpose of app evolution. We evaluate the usefulness of our approach and meaningfulness of its consensus rankings on four Android apps. We compare the rankings against reviews ranked by app developers manually and show that there is a strong correlation between the two (average Kendall rank correlation coefficient = 0.516). Thus, our approach can prioritize user reviews and help developers focus their time/effort on improving their apps instead of on identifying reviews to address in the next release.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124693802","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.0-193
Ryohei Banno, Kazuyuki Shudo
Publish/subscribe is a communication model for exchanging messages via a broker while providing loose coupling. So far, several studies have been conducted to address load concentration on the broker by forming distributed brokers. However, although they achieve higher throughput by load distribution among multiple brokers, these existing studies require an increased latency for message delivery. In this paper, we propose a novel method to construct and maintain an adaptive topology that features both scalability and immediacy in distributed publish/subscribe messaging. The proposed method is for topic-based publish/subscribe systems and uses a number of brokers to form an overlay network. Its topology changes dynamically to compose a subgraph for each topic in a single-hop or multi-hop manner according to the topic load (i.e., the number of clients). The experimental results show that compared to existing studies, the proposed method reduces the delivery path length, which is a principal factor that affects latency. Especially for low load topics, the reduction rate of the proposed method reaches values greater than 60%.
{"title":"Adaptive Topology for Scalability and Immediacy in Distributed Publish/Subscribe Messaging","authors":"Ryohei Banno, Kazuyuki Shudo","doi":"10.1109/COMPSAC48688.2020.0-193","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.0-193","url":null,"abstract":"Publish/subscribe is a communication model for exchanging messages via a broker while providing loose coupling. So far, several studies have been conducted to address load concentration on the broker by forming distributed brokers. However, although they achieve higher throughput by load distribution among multiple brokers, these existing studies require an increased latency for message delivery. In this paper, we propose a novel method to construct and maintain an adaptive topology that features both scalability and immediacy in distributed publish/subscribe messaging. The proposed method is for topic-based publish/subscribe systems and uses a number of brokers to form an overlay network. Its topology changes dynamically to compose a subgraph for each topic in a single-hop or multi-hop manner according to the topic load (i.e., the number of clients). The experimental results show that compared to existing studies, the proposed method reduces the delivery path length, which is a principal factor that affects latency. Especially for low load topics, the reduction rate of the proposed method reaches values greater than 60%.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124752797","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.00-77
You Liang, A. Thavaneswaran, Zimo Zhu, R. Thulasiram, Md. Erfanul Hoque
Regularization methods allow data scientists and risk managers to enhance the predictive power of a statistical model and improve the quality of risk forecasts. Financial risk forecasting is about forecasting volatility, Value at Risk (VaR), expected shortfall (ES) and model risk ratio. While regularized estimates have been shown to perform well in model selection and parameter estimation, their applications in financial risk forecasting has not yet been studied. In this paper, regularized adaptive forecasts and computationally efficient forecasting algorithms for volatility, VaR, ES and model risk are studied using various regularization methods such as ridge, lasso and elastic net. Sample sign correlation of standardized log returns (standardized by volatility forecasts) is used to identify the conditional distribution of the log returns series and provide regularized interval forecasts as well as regularized probability forecasts. Superiority of the regularized risk forecasts is demonstrated using different volatility models including a recently proposed generalized data-driven volatility model in [8]. Validation of the regularized risk forecasts using real financial data is given. Regularized probabilistic forecasts for stationary time series models are also discussed in some detail.
{"title":"Data-Driven Adaptive Regularized Risk Forecasting","authors":"You Liang, A. Thavaneswaran, Zimo Zhu, R. Thulasiram, Md. Erfanul Hoque","doi":"10.1109/COMPSAC48688.2020.00-77","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.00-77","url":null,"abstract":"Regularization methods allow data scientists and risk managers to enhance the predictive power of a statistical model and improve the quality of risk forecasts. Financial risk forecasting is about forecasting volatility, Value at Risk (VaR), expected shortfall (ES) and model risk ratio. While regularized estimates have been shown to perform well in model selection and parameter estimation, their applications in financial risk forecasting has not yet been studied. In this paper, regularized adaptive forecasts and computationally efficient forecasting algorithms for volatility, VaR, ES and model risk are studied using various regularization methods such as ridge, lasso and elastic net. Sample sign correlation of standardized log returns (standardized by volatility forecasts) is used to identify the conditional distribution of the log returns series and provide regularized interval forecasts as well as regularized probability forecasts. Superiority of the regularized risk forecasts is demonstrated using different volatility models including a recently proposed generalized data-driven volatility model in [8]. Validation of the regularized risk forecasts using real financial data is given. Regularized probabilistic forecasts for stationary time series models are also discussed in some detail.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"443 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132932544","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.0-210
Na Li, R. Murugesan, Lin Li, Hao Zheng
In the era of digital communities, a massive volume of data is created from people's online activities on a daily basis. Such data is sometimes shared with third-parties for commercial benefits, which has caused people's concerns about privacy disclosure. Privacy preserving technologies have been developed to protect people's sensitive information in data publishing. However, due to the availability of data from other sources, e.g., blogging, it is still possible to de-anonymize users even from anonymized data sets. This paper presents the design and implementation of an Interactive De-Anonymization Learning system—IDEAL. The system can help students learn about de-anonymization through engaging hands-on activities, such as tuning different parameters to evaluate their impact on the accuracy of de-anonymization, and observing the affect of data anonymization on de-anonymization. A pilot lab session to evaluate the system was conducted among thirty-five students at Prairie View A&M University and the feedback was very positive.
{"title":"IDEAL: An Interactive De-Anonymization Learning System","authors":"Na Li, R. Murugesan, Lin Li, Hao Zheng","doi":"10.1109/COMPSAC48688.2020.0-210","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.0-210","url":null,"abstract":"In the era of digital communities, a massive volume of data is created from people's online activities on a daily basis. Such data is sometimes shared with third-parties for commercial benefits, which has caused people's concerns about privacy disclosure. Privacy preserving technologies have been developed to protect people's sensitive information in data publishing. However, due to the availability of data from other sources, e.g., blogging, it is still possible to de-anonymize users even from anonymized data sets. This paper presents the design and implementation of an Interactive De-Anonymization Learning system—IDEAL. The system can help students learn about de-anonymization through engaging hands-on activities, such as tuning different parameters to evaluate their impact on the accuracy of de-anonymization, and observing the affect of data anonymization on de-anonymization. A pilot lab session to evaluate the system was conducted among thirty-five students at Prairie View A&M University and the feedback was very positive.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133493100","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.0-176
S. Rahman, A. Marzouqi, Swetha Variyath, Shristee Rahman, Masud Rabbani, Sheikh Iqbal Ahamed
From the statistics, almost 5 billion people in 2020 will be connected to Social Media (SM). Studies have drawn attention to the harms of SM to the health of students; it affects their attention span, memory, sleep, vision, and overall physical, mental, and social health. In this paper, we investigate the effects of SM use on the health and academic performance of students at the University of Sharjah. This study shows that students with more self-regulation have better control over social media use. A cross-sectional mixed approach (CSMA) was used to conduct the research using both quantitative and qualitative data. Out of 300 student participants in our study, the majority of them used Instagram, followed by WhatsApp and Twitter. Students reported an average time of 3-4 hours per day on social media; however, qualitative data showed that many students spent all day on social media. A majority of the students used social media to chat with friends and make new connections. They agreed that their use of social media has reduced reading of paper-based resources and has affected their grammar and writing skills. The use of SM delayed their bedtime and left fewer hours for sleep and caused eyestrain, neck/shoulder pain, fatigue, and poor posture, with declining physical activity. This study concludes that social media use does affect academic performance and health among the students of the University of Sharjah. Considering the negative consequences of extensive social media use, universities need to create awareness programs and can incorporate this as a topic in health education and awareness courses. Our study also generated new information and insights about the effects of high levels of SM usage on the health and academic performance among university students, thereby creating opportunities for further research.
{"title":"Effects of Social Media Use on Health and Academic Performance Among Students at the University of Sharjah","authors":"S. Rahman, A. Marzouqi, Swetha Variyath, Shristee Rahman, Masud Rabbani, Sheikh Iqbal Ahamed","doi":"10.1109/COMPSAC48688.2020.0-176","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.0-176","url":null,"abstract":"From the statistics, almost 5 billion people in 2020 will be connected to Social Media (SM). Studies have drawn attention to the harms of SM to the health of students; it affects their attention span, memory, sleep, vision, and overall physical, mental, and social health. In this paper, we investigate the effects of SM use on the health and academic performance of students at the University of Sharjah. This study shows that students with more self-regulation have better control over social media use. A cross-sectional mixed approach (CSMA) was used to conduct the research using both quantitative and qualitative data. Out of 300 student participants in our study, the majority of them used Instagram, followed by WhatsApp and Twitter. Students reported an average time of 3-4 hours per day on social media; however, qualitative data showed that many students spent all day on social media. A majority of the students used social media to chat with friends and make new connections. They agreed that their use of social media has reduced reading of paper-based resources and has affected their grammar and writing skills. The use of SM delayed their bedtime and left fewer hours for sleep and caused eyestrain, neck/shoulder pain, fatigue, and poor posture, with declining physical activity. This study concludes that social media use does affect academic performance and health among the students of the University of Sharjah. Considering the negative consequences of extensive social media use, universities need to create awareness programs and can incorporate this as a topic in health education and awareness courses. Our study also generated new information and insights about the effects of high levels of SM usage on the health and academic performance among university students, thereby creating opportunities for further research.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122170925","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.00-97
Katsuya Matsubara, Yuhei Takagawa
Web services have seen early adoption and rapid growth with the introduction of various web system frameworks, and not only large companies but also smaller businesses or individuals can provide their own web services offering access to their products, entertainment, and information. Therefore, as the number of Internet users increases, especially with the spread of smartphones, even relatively small web service infrastructure need to have both high access performance and availability, although the cost of additional computational resources and redundant servers may be hard to bear depending on the load. We focus on the fact that the performance characteristics may differ depending on the internal implementation of the operating system (OS), even when the available computing resources are the same. This paper investigates the possibility of developing a system that achieves both high access performance and availability of the web server by dynamically switching the OS on which the web server is running, without requiring additional computing resources or using redundant servers. This paper identifies the differences between Linux and FreeBSD in terms of network processing and describes the mechanism of process migration among heterogeneous OSes to switch the OSes. It then demonstrates the feasibility of our approach with experimental results on the performance characteristics and load tolerance of a web server in operation when the OSes are dynamically switched.
{"title":"Adaptive OS Switching for Improving Availability During Web Traffic Surges: A Feasibility Study","authors":"Katsuya Matsubara, Yuhei Takagawa","doi":"10.1109/COMPSAC48688.2020.00-97","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.00-97","url":null,"abstract":"Web services have seen early adoption and rapid growth with the introduction of various web system frameworks, and not only large companies but also smaller businesses or individuals can provide their own web services offering access to their products, entertainment, and information. Therefore, as the number of Internet users increases, especially with the spread of smartphones, even relatively small web service infrastructure need to have both high access performance and availability, although the cost of additional computational resources and redundant servers may be hard to bear depending on the load. We focus on the fact that the performance characteristics may differ depending on the internal implementation of the operating system (OS), even when the available computing resources are the same. This paper investigates the possibility of developing a system that achieves both high access performance and availability of the web server by dynamically switching the OS on which the web server is running, without requiring additional computing resources or using redundant servers. This paper identifies the differences between Linux and FreeBSD in terms of network processing and describes the mechanism of process migration among heterogeneous OSes to switch the OSes. It then demonstrates the feasibility of our approach with experimental results on the performance characteristics and load tolerance of a web server in operation when the OSes are dynamically switched.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116459977","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 : 2020-07-01DOI: 10.1109/COMPSAC48688.2020.0-192
Fumiya Toyoda, Yusuke Sakumoto, H. Ohsaki
A blind search in a network is used to discover a target node without detailed knowledge on the network. Because of its simplicity and the robust against network uncertainty, the blind search has been widely utilized by diverse applications in different types of networks (e.g., unstructured P2P (Peer-to-Peer) networks, ICNs (Information Centric Networks), mobile ad-hoc networks, and social networks). One of the major drawbacks of the blind search is its inefficiency; i.e., a large number of message exchanges is unavoidable for shortening the search time. In this paper, we propose an efficient blind search method utilizing the rendezvous of multiple random walkers, whose transition probabilities are adjusted based on our analysis results. Through simulation experiments, we show that the performance of the proposed search method is comparable with the flooding, which is the fastest but the least efficient method among blind search methods, and that it requires much smaller message exchanges than the flooding. We also show that the proposed search method works more effectively in scale-free networks than in non-scale-free networks.
{"title":"Proposal of an Efficient Blind Search Utilizing the Rendezvous of Random Walk Agents","authors":"Fumiya Toyoda, Yusuke Sakumoto, H. Ohsaki","doi":"10.1109/COMPSAC48688.2020.0-192","DOIUrl":"https://doi.org/10.1109/COMPSAC48688.2020.0-192","url":null,"abstract":"A blind search in a network is used to discover a target node without detailed knowledge on the network. Because of its simplicity and the robust against network uncertainty, the blind search has been widely utilized by diverse applications in different types of networks (e.g., unstructured P2P (Peer-to-Peer) networks, ICNs (Information Centric Networks), mobile ad-hoc networks, and social networks). One of the major drawbacks of the blind search is its inefficiency; i.e., a large number of message exchanges is unavoidable for shortening the search time. In this paper, we propose an efficient blind search method utilizing the rendezvous of multiple random walkers, whose transition probabilities are adjusted based on our analysis results. Through simulation experiments, we show that the performance of the proposed search method is comparable with the flooding, which is the fastest but the least efficient method among blind search methods, and that it requires much smaller message exchanges than the flooding. We also show that the proposed search method works more effectively in scale-free networks than in non-scale-free networks.","PeriodicalId":430098,"journal":{"name":"2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116735036","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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