Pub Date : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257242
Kui Xu, D. Yao, Manuel A. Pérez-Quiñones, Casey Link, E. Geller
Understanding the capabilities of adversaries (e.g., how much the adversary knows about a target) is important for building strong security defenses. Computing an adversary's knowledge about a target requires new modeling techniques and experimental methods. Our work describes a quantitative analysis technique for modeling an adversary's knowledge about private information at workplace. Our technical enabler is a new emulation environment for conducting user experiments on attack behaviors. We develop a role-playing cyber game for our evaluation, where the participants take on the adversary role to launch ID theft attacks by answering challenge questions about a target. We measure an adversary's knowledge based on how well he or she answers the authentication questions about a target. We present our empirical modeling results based on the data collected from a total of 36 users.
{"title":"Role-playing game for studying user behaviors in security: A case study on email secrecy","authors":"Kui Xu, D. Yao, Manuel A. Pérez-Quiñones, Casey Link, E. Geller","doi":"10.4108/ICST.COLLABORATECOM.2014.257242","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257242","url":null,"abstract":"Understanding the capabilities of adversaries (e.g., how much the adversary knows about a target) is important for building strong security defenses. Computing an adversary's knowledge about a target requires new modeling techniques and experimental methods. Our work describes a quantitative analysis technique for modeling an adversary's knowledge about private information at workplace. Our technical enabler is a new emulation environment for conducting user experiments on attack behaviors. We develop a role-playing cyber game for our evaluation, where the participants take on the adversary role to launch ID theft attacks by answering challenge questions about a target. We measure an adversary's knowledge based on how well he or she answers the authentication questions about a target. We present our empirical modeling results based on the data collected from a total of 36 users.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128611308","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257559
W. Moody, Hongxin Hu, A. Apon
Distributed and parallel applications are critical information technology systems in multiple industries, including academia, military, government, financial, medical, and transportation. These applications present target rich environments for malicious attackers seeking to disrupt the confidentiality, integrity and availability of these systems. Applying the military concept of defense cyber maneuver to these systems can provide protection and defense mechanisms that allow survivability and operational continuity. Understanding the tradeoffs between information systems security and operational performance when applying maneuver principles is of interest to administrators, users, and researchers. To this end, we present a model of a defensive maneuver cyber platform using Stochastic Petri Nets. This model enables the understanding and evaluation of the costs and benefits of maneuverability in a distributed application environment, specifically focusing on moving target defense and deceptive defense strategies.
{"title":"Defensive maneuver cyber platform modeling with Stochastic Petri Nets","authors":"W. Moody, Hongxin Hu, A. Apon","doi":"10.4108/ICST.COLLABORATECOM.2014.257559","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257559","url":null,"abstract":"Distributed and parallel applications are critical information technology systems in multiple industries, including academia, military, government, financial, medical, and transportation. These applications present target rich environments for malicious attackers seeking to disrupt the confidentiality, integrity and availability of these systems. Applying the military concept of defense cyber maneuver to these systems can provide protection and defense mechanisms that allow survivability and operational continuity. Understanding the tradeoffs between information systems security and operational performance when applying maneuver principles is of interest to administrators, users, and researchers. To this end, we present a model of a defensive maneuver cyber platform using Stochastic Petri Nets. This model enables the understanding and evaluation of the costs and benefits of maneuverability in a distributed application environment, specifically focusing on moving target defense and deceptive defense strategies.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131312085","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257382
Makbule Gülçin Özsoy, Faruk Polat, R. Alhajj
Social networks, personal blog pages, on-line transaction web-sites, expertise web pages and location based social networks provide an attractive platform for millions of users to share opinions, comments, ratings, etc. Having this kind of diverse and comprehensive information leads to difficulties for users to reach the most appropriate and reliable conclusions. Recommendation systems form one of the solutions to deal with the information overload problem by providing personalized services. Using spatial, temporal and social information on recommender systems is a recent trend that increases the performance. Also, taking into account more than one criterion can improve the performance of the recommender systems. In this paper, a location and social network aware recommender system enhanced with multi objective filtering is proposed and described. The results show that the proposed method reaches high coverage while preserving precision. Besides, the proposed method is not affected by the range of ratings and provides persistent results in different settings.
{"title":"Multi-objective optimization based location and social network aware recommendation","authors":"Makbule Gülçin Özsoy, Faruk Polat, R. Alhajj","doi":"10.4108/ICST.COLLABORATECOM.2014.257382","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257382","url":null,"abstract":"Social networks, personal blog pages, on-line transaction web-sites, expertise web pages and location based social networks provide an attractive platform for millions of users to share opinions, comments, ratings, etc. Having this kind of diverse and comprehensive information leads to difficulties for users to reach the most appropriate and reliable conclusions. Recommendation systems form one of the solutions to deal with the information overload problem by providing personalized services. Using spatial, temporal and social information on recommender systems is a recent trend that increases the performance. Also, taking into account more than one criterion can improve the performance of the recommender systems. In this paper, a location and social network aware recommender system enhanced with multi objective filtering is proposed and described. The results show that the proposed method reaches high coverage while preserving precision. Besides, the proposed method is not affected by the range of ratings and provides persistent results in different settings.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131460137","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257833
Moustafa AbdelBaky, J. Montes, Michael Johnston, Vipin Sachdeva, Richard L. Anderson, K. E. Jordan, M. Parashar
The use of in-silico simulations in experimental science can greatly increase laboratory efficiency and provide additional insights into interactions not easily described by traditional methods. Such simulations require significant amounts of computational resources, accessible only via supercomputers of large-scale high-performance clusters. Due to the complexity of the computational experiments, as well as the usage of the underlying resources, experimental scientists heavily rely on computational scientists with HPC expertise to perform these simulations. This additional bottleneck prevents the widespread adoption of real time in-silico simulation as a driver for laboratory experimentation. In this paper, we aim to overcome this bottleneck by presenting the architecture of an end-to-end framework to enable HPC Software as a Service. This framework is designed to make it easy for scientific applications to run on top of dynamically federated HPC resources. The framework enables HPC resource sharing while maximizing throughput and utilization. We focus specifically on a use case where an experimental scientist uses a mobile portal to control dissipative particle dynamics experiments that are executed on a remote supercomputer (IBM Blue Gene/Q).
在实验科学中使用硅模拟可以极大地提高实验室效率，并为传统方法难以描述的相互作用提供额外的见解。这样的模拟需要大量的计算资源，只能通过大规模高性能集群的超级计算机来访问。由于计算实验的复杂性，以及底层资源的使用，实验科学家严重依赖具有高性能计算专业知识的计算科学家来执行这些模拟。这个额外的瓶颈阻碍了实时硅模拟作为实验室实验驱动程序的广泛采用。在本文中，我们的目标是通过提出端到端框架的体系结构来实现HPC软件即服务来克服这一瓶颈。该框架旨在使科学应用程序更容易在动态联合的HPC资源上运行。该框架支持HPC资源共享，同时最大限度地提高吞吐量和利用率。我们特别关注实验科学家使用移动门户来控制在远程超级计算机(IBM Blue Gene/Q)上执行的耗散粒子动力学实验的用例。
{"title":"Exploring HPC-based scientific software as a service using CometCloud","authors":"Moustafa AbdelBaky, J. Montes, Michael Johnston, Vipin Sachdeva, Richard L. Anderson, K. E. Jordan, M. Parashar","doi":"10.4108/ICST.COLLABORATECOM.2014.257833","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257833","url":null,"abstract":"The use of in-silico simulations in experimental science can greatly increase laboratory efficiency and provide additional insights into interactions not easily described by traditional methods. Such simulations require significant amounts of computational resources, accessible only via supercomputers of large-scale high-performance clusters. Due to the complexity of the computational experiments, as well as the usage of the underlying resources, experimental scientists heavily rely on computational scientists with HPC expertise to perform these simulations. This additional bottleneck prevents the widespread adoption of real time in-silico simulation as a driver for laboratory experimentation. In this paper, we aim to overcome this bottleneck by presenting the architecture of an end-to-end framework to enable HPC Software as a Service. This framework is designed to make it easy for scientific applications to run on top of dynamically federated HPC resources. The framework enables HPC resource sharing while maximizing throughput and utilization. We focus specifically on a use case where an experimental scientist uses a mobile portal to control dissipative particle dynamics experiments that are executed on a remote supercomputer (IBM Blue Gene/Q).","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121256108","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257533
Joseph Boman, Jonathan Taylor, A. Ngu
The Internet of Things (IoT) is a rapidly growing system of physical sensors and connected devices, enabling an advanced information gathering, interpretation and monitoring. However, IoT must be supported by a middleware that allows IoT consumers and IoT application developers to interact in a user-friendly way, despite the differences in each user's perspective of IoT system. To that end, our software attempts to bridge the gap between IoT consumers and IoT application developers. Through the coupling of GSN (an existing open source IoT middleware), Firebase (a cloud storage service), and an IoT data interpreter developed by us, we have created a software system that takes the first step towards an ubiquitous middleware for IoT.
{"title":"Flexible IoT middleware for integration of things and applications","authors":"Joseph Boman, Jonathan Taylor, A. Ngu","doi":"10.4108/ICST.COLLABORATECOM.2014.257533","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257533","url":null,"abstract":"The Internet of Things (IoT) is a rapidly growing system of physical sensors and connected devices, enabling an advanced information gathering, interpretation and monitoring. However, IoT must be supported by a middleware that allows IoT consumers and IoT application developers to interact in a user-friendly way, despite the differences in each user's perspective of IoT system. To that end, our software attempts to bridge the gap between IoT consumers and IoT application developers. Through the coupling of GSN (an existing open source IoT middleware), Firebase (a cloud storage service), and an IoT data interpreter developed by us, we have created a software system that takes the first step towards an ubiquitous middleware for IoT.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121262126","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257337
T. Marrinan, Jillian Aurisano, Arthur Nishimoto, Krishna Bharadwaj, V. Mateevitsi, L. Renambot, Lance Long, Andrew E. Johnson, J. Leigh
Current web-based collaboration systems, such as Google Hangouts, WebEx, and Skype, primarily enable single users to work with remote collaborators through video conferencing and desktop mirroring. The original SAGE software, developed in 2004 and adopted at over one hundred international sites, was designed to enable groups to work in front of large shared displays in order to solve problems that required juxtaposing large volumes of information in ultra high-resolution. We have developed SAGE2, as a complete redesign and implementation of SAGE, using cloud-based and web browser technologies in order to enhance data intensive co-located and remote collaboration. This paper provides an overview of SAGE2's infrastructure, the technical design challenges, and the afforded benefits to data intensive collaboration. Lastly, we provide insight on how future collaborative applications can be developed to support large displays and demonstrate the power and flexibility that SAGE2 offers in collaborative scenarios through a series of use cases.
{"title":"SAGE2: A new approach for data intensive collaboration using Scalable Resolution Shared Displays","authors":"T. Marrinan, Jillian Aurisano, Arthur Nishimoto, Krishna Bharadwaj, V. Mateevitsi, L. Renambot, Lance Long, Andrew E. Johnson, J. Leigh","doi":"10.4108/ICST.COLLABORATECOM.2014.257337","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257337","url":null,"abstract":"Current web-based collaboration systems, such as Google Hangouts, WebEx, and Skype, primarily enable single users to work with remote collaborators through video conferencing and desktop mirroring. The original SAGE software, developed in 2004 and adopted at over one hundred international sites, was designed to enable groups to work in front of large shared displays in order to solve problems that required juxtaposing large volumes of information in ultra high-resolution. We have developed SAGE2, as a complete redesign and implementation of SAGE, using cloud-based and web browser technologies in order to enhance data intensive co-located and remote collaboration. This paper provides an overview of SAGE2's infrastructure, the technical design challenges, and the afforded benefits to data intensive collaboration. Lastly, we provide insight on how future collaborative applications can be developed to support large displays and demonstrate the power and flexibility that SAGE2 offers in collaborative scenarios through a series of use cases.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116460271","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257335
M. Esbensen, Paolo Tell, J. Bardram
Companies are increasingly organizing work in globally distributed teams. A core challenge to these distributed teams is, however, to maintain social relationships due to limited opportunities and tools for social engagement. In this paper we present SIDEBAR: a videoconferencing system that enhances virtual meetings by enabling social engagement. Through image analysis of the conference video feed, SIDEBAR tracks meeting participants in real-time. A personal tablet then allows each participant to identify and track other participants, to look up information about them and their local work context, and to engage in peer-to-peer chat conversations. We describe the motivation, design and implementation of SIDEBAR and report results from a preliminary evaluation, which shows that participants found SIDEBAR useful and easy to use. The paper concludes by providing three design guidelines for collaborative technologies supporting social engagement.
{"title":"SideBar: Videoconferencing system supporting social engagement","authors":"M. Esbensen, Paolo Tell, J. Bardram","doi":"10.4108/ICST.COLLABORATECOM.2014.257335","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257335","url":null,"abstract":"Companies are increasingly organizing work in globally distributed teams. A core challenge to these distributed teams is, however, to maintain social relationships due to limited opportunities and tools for social engagement. In this paper we present SIDEBAR: a videoconferencing system that enhances virtual meetings by enabling social engagement. Through image analysis of the conference video feed, SIDEBAR tracks meeting participants in real-time. A personal tablet then allows each participant to identify and track other participants, to look up information about them and their local work context, and to engage in peer-to-peer chat conversations. We describe the motivation, design and implementation of SIDEBAR and report results from a preliminary evaluation, which shows that participants found SIDEBAR useful and easy to use. The paper concludes by providing three design guidelines for collaborative technologies supporting social engagement.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127891552","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257329
Andrew Ghobrial, Jacob W. Bartel, P. Dewan
Users' contacts often need to be grouped into equivalence classes for various purposes such as easily sending a message to all members of the group. Several approaches have been recently developed to make such predictions (a) for both ephemeral and persistent groups (b) in both email and social networks systems. However, no research has attempted to compare these approaches or compose them by using ideas of one in another. We have taken a step in this direction. We have developed and compared multiple approaches to predicting persistent contact groups in email. These approaches compose an algorithm that generates friend lists in Facebook from a social graph with different techniques for generating the social graph. One of these techniques is based on a scoring algorithm used by Google to predict ephemeral groups incrementally. To compare the approaches we ran a user study involving 19 participants and used two simple metrics that calculated the average percentage difference between a predicted group and the group of addresses in a future message. The evaluation showed that using the Google score was the best approach though it offered very small improvements over all but one of the simpler methods.
{"title":"Towards composable prediction of contact groups","authors":"Andrew Ghobrial, Jacob W. Bartel, P. Dewan","doi":"10.4108/ICST.COLLABORATECOM.2014.257329","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257329","url":null,"abstract":"Users' contacts often need to be grouped into equivalence classes for various purposes such as easily sending a message to all members of the group. Several approaches have been recently developed to make such predictions (a) for both ephemeral and persistent groups (b) in both email and social networks systems. However, no research has attempted to compare these approaches or compose them by using ideas of one in another. We have taken a step in this direction. We have developed and compared multiple approaches to predicting persistent contact groups in email. These approaches compose an algorithm that generates friend lists in Facebook from a social graph with different techniques for generating the social graph. One of these techniques is based on a scoring algorithm used by Google to predict ephemeral groups incrementally. To compare the approaches we ran a user study involving 19 participants and used two simple metrics that calculated the average percentage difference between a predicted group and the group of addresses in a future message. The evaluation showed that using the Google score was the best approach though it offered very small improvements over all but one of the simpler methods.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129082371","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 : 2014-11-11DOI: 10.4108/ICST.COLLABORATECOM.2014.257620
Rajesh Vargheese, Prashant Prabhudesai
Video based telehealth is emerging as an important technology for effective and efficient collaboration between providers and patients. The advantages of receiving care at source not only account for convenience and cost effectiveness but also enable faster access to care. It brings access, experience and efficiencies in the care process. While there are multiple models of telehealth, in this work, we will focus on an on demand telehealth appointment between a provider and a patient. Given that the patient might not have a previous care relationship with the provider, it is extremely important to ensure that the patient is assured that the provider that he is communicating with is verified by a trusted third-party verification service. Today, basic methods such as authentication and authorization are used to verify the identity of the provider at entry. In this work, we take this model further by proposing a real-time in-session provider identity verification service. This leverages video stream analytics and computer vision models to validate the person involved in the session by a third-party verification service. We propose an architecture and method for enabling such a service, which will enhance the trust model - a critical factor in the adoption of on-demand telehealth.
{"title":"A real time provider identity verification service for a trusted telehealth video collaboration","authors":"Rajesh Vargheese, Prashant Prabhudesai","doi":"10.4108/ICST.COLLABORATECOM.2014.257620","DOIUrl":"https://doi.org/10.4108/ICST.COLLABORATECOM.2014.257620","url":null,"abstract":"Video based telehealth is emerging as an important technology for effective and efficient collaboration between providers and patients. The advantages of receiving care at source not only account for convenience and cost effectiveness but also enable faster access to care. It brings access, experience and efficiencies in the care process. While there are multiple models of telehealth, in this work, we will focus on an on demand telehealth appointment between a provider and a patient. Given that the patient might not have a previous care relationship with the provider, it is extremely important to ensure that the patient is assured that the provider that he is communicating with is verified by a trusted third-party verification service. Today, basic methods such as authentication and authorization are used to verify the identity of the provider at entry. In this work, we take this model further by proposing a real-time in-session provider identity verification service. This leverages video stream analytics and computer vision models to validate the person involved in the session by a third-party verification service. We propose an architecture and method for enabling such a service, which will enhance the trust model - a critical factor in the adoption of on-demand telehealth.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129266678","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 : 2014-11-11DOI: 10.5194/ISPRSANNALS-II-4-W2-51-2015
Qiulei Guo, Balaji Palanisamy, H. Karimi
The proliferation of data acquisition devices like 3D laser scanners had led to the burst of large-scale spatial terrain data which imposes many challenges to spatial data analysis and computation. With the advent of several emerging collaborative cloud technologies, a natural and cost-effective approach to managing such large-scale data is to store and share such datasets in a publicly hosted cloud service and process the data within the cloud itself using modern distributed computing paradigms such as MapReduce. For several key spatial data analysis and computation problems, polygon retrieval is a fundamental operation which is often computed under real-time constraints. However, existing sequential algorithms fail to meet this demand effectively given that terrain data in recent years have witnessed an unprecedented growth in both volume and rate. In this work, we develop a MapReduce-based parallel polygon retrieval algorithm which aims at minimizing the IO and CPU loads of the map and reduce tasks during spatial data processing. The results of the preliminary experiments on a Hadoop cluster demonstrate that the proposed techniques are scalable and lead to more than 35% reduction in execution time of the polygon retrieval operation over existing distributed algorithms.
{"title":"A distributed polygon retrieval algorithm using MapReduce","authors":"Qiulei Guo, Balaji Palanisamy, H. Karimi","doi":"10.5194/ISPRSANNALS-II-4-W2-51-2015","DOIUrl":"https://doi.org/10.5194/ISPRSANNALS-II-4-W2-51-2015","url":null,"abstract":"The proliferation of data acquisition devices like 3D laser scanners had led to the burst of large-scale spatial terrain data which imposes many challenges to spatial data analysis and computation. With the advent of several emerging collaborative cloud technologies, a natural and cost-effective approach to managing such large-scale data is to store and share such datasets in a publicly hosted cloud service and process the data within the cloud itself using modern distributed computing paradigms such as MapReduce. For several key spatial data analysis and computation problems, polygon retrieval is a fundamental operation which is often computed under real-time constraints. However, existing sequential algorithms fail to meet this demand effectively given that terrain data in recent years have witnessed an unprecedented growth in both volume and rate. In this work, we develop a MapReduce-based parallel polygon retrieval algorithm which aims at minimizing the IO and CPU loads of the map and reduce tasks during spatial data processing. The results of the preliminary experiments on a Hadoop cluster demonstrate that the proposed techniques are scalable and lead to more than 35% reduction in execution time of the polygon retrieval operation over existing distributed algorithms.","PeriodicalId":432345,"journal":{"name":"10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"80 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131258719","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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