Pub Date : 2017-12-18DOI: 10.1109/PDCAT.2017.00079
F. Loulergue
Skeletal parallelism offers a good trade-off between programming productivity and execution efficiency. In this style of parallelism, an application is a composition of algorithmic skeletons. An algorithmic skeleton captures a pattern of parallel algorithm on a distributed data structure, and is also often associated with a sequential algorithm on a sequential data structure that is the counterpart of the parallel data structure. The algorithmic skeleton approach has been inspired by functional programming. It is therefore very natural to embed algorithmic skeletons in a functional programming language. In this paper we present a new algorithmic skeleton library for the statically typed functional language OCaml, and illustrate its use on some applications. This functional skeletal parallel programming library is implemented using the Bulk Synchronous Parallel ML parallel programming library for OCaml.
{"title":"Implementing Algorithmic Skeletons with Bulk Synchronous Parallel ML","authors":"F. Loulergue","doi":"10.1109/PDCAT.2017.00079","DOIUrl":"https://doi.org/10.1109/PDCAT.2017.00079","url":null,"abstract":"Skeletal parallelism offers a good trade-off between programming productivity and execution efficiency. In this style of parallelism, an application is a composition of algorithmic skeletons. An algorithmic skeleton captures a pattern of parallel algorithm on a distributed data structure, and is also often associated with a sequential algorithm on a sequential data structure that is the counterpart of the parallel data structure. The algorithmic skeleton approach has been inspired by functional programming. It is therefore very natural to embed algorithmic skeletons in a functional programming language. In this paper we present a new algorithmic skeleton library for the statically typed functional language OCaml, and illustrate its use on some applications. This functional skeletal parallel programming library is implemented using the Bulk Synchronous Parallel ML parallel programming library for OCaml.","PeriodicalId":119197,"journal":{"name":"2017 18th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133083162","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 : 2017-12-01DOI: 10.1109/PDCAT.2017.00041
S. Moulik, R. Devaraj, A. Sarkar, Arijit Shaw
Real-time systems are increasingly being implemented on heterogeneous multi-core platforms to efficiently cater to their diverse and high computation demands. Over the years, researchers have developed mechanisms to efficiently schedule tasks on homogeneous multi-cores such that all tasks meet their execution and deadline requirements. However, devising an efficient scheduling strategy for real-time tasks on heterogeneous platforms has proved to be a challenging as well as computationally expensive problem. Today, there is a severe dearth of low-overhead techniques towards real-time scheduling on heterogeneous platforms. Hence, we propose an effective low-overhead heuristic approach for scheduling a set of periodic tasks executing on a heterogeneous multi-core platform. Employing the concept of deadline partitioning to obtain a set of discrete time slices, we propose a scheme to efficiently schedule tasks over these time slices while incurring low and bounded number of migrations. Conducted experiments have shown promising results and indicate to the practical efficacy of our approach.
{"title":"A Deadline-Partition Oriented Heterogeneous Multi-Core Scheduler for Periodic Tasks","authors":"S. Moulik, R. Devaraj, A. Sarkar, Arijit Shaw","doi":"10.1109/PDCAT.2017.00041","DOIUrl":"https://doi.org/10.1109/PDCAT.2017.00041","url":null,"abstract":"Real-time systems are increasingly being implemented on heterogeneous multi-core platforms to efficiently cater to their diverse and high computation demands. Over the years, researchers have developed mechanisms to efficiently schedule tasks on homogeneous multi-cores such that all tasks meet their execution and deadline requirements. However, devising an efficient scheduling strategy for real-time tasks on heterogeneous platforms has proved to be a challenging as well as computationally expensive problem. Today, there is a severe dearth of low-overhead techniques towards real-time scheduling on heterogeneous platforms. Hence, we propose an effective low-overhead heuristic approach for scheduling a set of periodic tasks executing on a heterogeneous multi-core platform. Employing the concept of deadline partitioning to obtain a set of discrete time slices, we propose a scheme to efficiently schedule tasks over these time slices while incurring low and bounded number of migrations. Conducted experiments have shown promising results and indicate to the practical efficacy of our approach.","PeriodicalId":119197,"journal":{"name":"2017 18th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115251952","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 : 2017-12-01DOI: 10.1109/PDCAT.2017.00071
S. Shankar, Pinxing Lin, A. Herkersdorf, Thomas Wild
Member State Bitmask Technique (MSBT) is a hardware oriented transition compression technique which can compress the redundant transitions in a finite automaton. While the compressed automaton is stored in on-chip memories; a dedicated hardware accelerator performs signature matching by comparing the network streams against the compressed automaton at line rate. The MSBT consists of three functional steps which include the intra-state transition compression, state grouping and the inter-state transition compression. The state grouping algorithm which is currently used in MSBT is not compression aware and results in sub-optimal transition compression. To address this weakness, a compression aware Divide and Conquer state grouping method is proposed in this paper, which can efficiently group states that improves the transition compression in MSBT. Experimental evaluation of the proposed state grouping method, results in a reduced on-chip memory usage of the order of 10-30%. The reduction in the memory usage allows to accommodate more signatures in on-chip memories and perform signature matching with them at line rate.
{"title":"A Divide and Conquer State Grouping Method for Bitmap Based Transition Compression","authors":"S. Shankar, Pinxing Lin, A. Herkersdorf, Thomas Wild","doi":"10.1109/PDCAT.2017.00071","DOIUrl":"https://doi.org/10.1109/PDCAT.2017.00071","url":null,"abstract":"Member State Bitmask Technique (MSBT) is a hardware oriented transition compression technique which can compress the redundant transitions in a finite automaton. While the compressed automaton is stored in on-chip memories; a dedicated hardware accelerator performs signature matching by comparing the network streams against the compressed automaton at line rate. The MSBT consists of three functional steps which include the intra-state transition compression, state grouping and the inter-state transition compression. The state grouping algorithm which is currently used in MSBT is not compression aware and results in sub-optimal transition compression. To address this weakness, a compression aware Divide and Conquer state grouping method is proposed in this paper, which can efficiently group states that improves the transition compression in MSBT. Experimental evaluation of the proposed state grouping method, results in a reduced on-chip memory usage of the order of 10-30%. The reduction in the memory usage allows to accommodate more signatures in on-chip memories and perform signature matching with them at line rate.","PeriodicalId":119197,"journal":{"name":"2017 18th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115342022","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 : 2017-12-01DOI: 10.1109/PDCAT.2017.00016
Yaru Dong, Yidong Li, Wenhua Liu, Jun Wu
Behavior detection is an important research field in pattern recognition and it can be applied to control the traffic safety. The mobile phones becomes a potential security when the pedestrians unconsciously use the phones during the crossing of the street. To avoid the traffic accidents, this paper proposes a new algorithm of the pedestrian behavior detection for the people unconsciously using phones. Firstly, the method that pedestrian detection based on gradient and texture feature integration is used to find the position of pedestrian. Secondly, Selective search is used to get the position of sensitive parts. We choose the arms as the sensitive parts in this algorithm. Finally, we extract and classify sensitive parts. Currently, fewer people are studying this topic. Therefore, we construct a new pedestrian image set that contains 2.5G images called PWUM (Pedestrian Who use mobile phone) set for verifying the effectiveness of our algorithm. Experimental results show that the proposed algorithm can efficiently detect pedestrian who is using mobile phone on PWUM dataset.
行为检测是模式识别中的一个重要研究领域，可以应用于交通安全控制。当行人在过马路时不自觉地使用手机时，手机就成为了潜在的安全隐患。为了避免交通事故的发生，本文提出了一种针对无意识使用手机人群的行人行为检测新算法。首先，采用基于梯度和纹理特征融合的行人检测方法寻找行人的位置;其次，采用选择性搜索得到敏感部位的位置;在该算法中，我们选择臂作为敏感部位。最后对敏感部位进行提取和分类。目前，很少有人研究这个话题。因此，我们构建了一个包含2.5G图像的新的行人图像集，称为PWUM (pedestrian Who use mobile phone)集，用于验证算法的有效性。实验结果表明，该算法可以有效地检测出在PWUM数据集上使用手机的行人。
{"title":"Unconscious Behavior Detection for Pedestrian Safety Based on Gesture Features","authors":"Yaru Dong, Yidong Li, Wenhua Liu, Jun Wu","doi":"10.1109/PDCAT.2017.00016","DOIUrl":"https://doi.org/10.1109/PDCAT.2017.00016","url":null,"abstract":"Behavior detection is an important research field in pattern recognition and it can be applied to control the traffic safety. The mobile phones becomes a potential security when the pedestrians unconsciously use the phones during the crossing of the street. To avoid the traffic accidents, this paper proposes a new algorithm of the pedestrian behavior detection for the people unconsciously using phones. Firstly, the method that pedestrian detection based on gradient and texture feature integration is used to find the position of pedestrian. Secondly, Selective search is used to get the position of sensitive parts. We choose the arms as the sensitive parts in this algorithm. Finally, we extract and classify sensitive parts. Currently, fewer people are studying this topic. Therefore, we construct a new pedestrian image set that contains 2.5G images called PWUM (Pedestrian Who use mobile phone) set for verifying the effectiveness of our algorithm. Experimental results show that the proposed algorithm can efficiently detect pedestrian who is using mobile phone on PWUM dataset.","PeriodicalId":119197,"journal":{"name":"2017 18th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117302626","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 : 2017-12-01DOI: 10.1109/PDCAT.2017.00049
Virginia Niculescu, F. Loulergue, Darius Bufnea, Adrian Sterca
Parallel programs based on the Divide&Conquer paradigm could be successfully defined in a simple way using powerlists. These parallel recursive data structures and their algebraic theories offer both a methodology to design parallel algorithms and parallel programming abstractions to ease the development of parallel applications. The paper presents how programs based on powerlists can be implemented in Java using the JPLF framework we developed. The design of this framework is based on powerlists theory, but in the same time follows the object-oriented design principles that provide flexibility and maintainability. Examples are given and performance experiments are conducted. The results emphasize the utility and the efficiency of the framework.
{"title":"A Java Framework for High Level Parallel Programming Using Powerlists","authors":"Virginia Niculescu, F. Loulergue, Darius Bufnea, Adrian Sterca","doi":"10.1109/PDCAT.2017.00049","DOIUrl":"https://doi.org/10.1109/PDCAT.2017.00049","url":null,"abstract":"Parallel programs based on the Divide&Conquer paradigm could be successfully defined in a simple way using powerlists. These parallel recursive data structures and their algebraic theories offer both a methodology to design parallel algorithms and parallel programming abstractions to ease the development of parallel applications. The paper presents how programs based on powerlists can be implemented in Java using the JPLF framework we developed. The design of this framework is based on powerlists theory, but in the same time follows the object-oriented design principles that provide flexibility and maintainability. Examples are given and performance experiments are conducted. The results emphasize the utility and the efficiency of the framework.","PeriodicalId":119197,"journal":{"name":"2017 18th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128421021","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 : 2017-12-01DOI: 10.1109/PDCAT.2017.00078
Lena Feinbube, Lukas Pirl, Peter Tröger, A. Polze
Modern distributed systems have reached a level of complexity where software bugs and hardware failures are no longer exceptional, but a permanent operational threat. This holds especially for cloud infrastructures, which need to deliver resources to their customers under well-defined service-level agreements. Dependability need to be assessed carefully. This article presents a structured approach for dependability stress testing in a cloud infrastructure. We automatically determine and inject the maximum amount of simultaneous non-fatal errors in different variations. This puts the existing resiliency mechanisms under heavy load, so that they are tested for their effectiveness in corner cases. The starting point is a failure space dependability model of the system. It includes the notion of fault tolerance dependencies, which encode fault-triggering relations between different software layers. From the model, our deterministic algorithm automatically derives fault injection campaigns that maximize dependability stress. The article demonstrates the feasibility of the approach with an assessment of a fault tolerant OpenStack cloud infrastructure deployment.
{"title":"Dependability Stress Testing of Cloud Infrastructures","authors":"Lena Feinbube, Lukas Pirl, Peter Tröger, A. Polze","doi":"10.1109/PDCAT.2017.00078","DOIUrl":"https://doi.org/10.1109/PDCAT.2017.00078","url":null,"abstract":"Modern distributed systems have reached a level of complexity where software bugs and hardware failures are no longer exceptional, but a permanent operational threat. This holds especially for cloud infrastructures, which need to deliver resources to their customers under well-defined service-level agreements. Dependability need to be assessed carefully. This article presents a structured approach for dependability stress testing in a cloud infrastructure. We automatically determine and inject the maximum amount of simultaneous non-fatal errors in different variations. This puts the existing resiliency mechanisms under heavy load, so that they are tested for their effectiveness in corner cases. The starting point is a failure space dependability model of the system. It includes the notion of fault tolerance dependencies, which encode fault-triggering relations between different software layers. From the model, our deterministic algorithm automatically derives fault injection campaigns that maximize dependability stress. The article demonstrates the feasibility of the approach with an assessment of a fault tolerant OpenStack cloud infrastructure deployment.","PeriodicalId":119197,"journal":{"name":"2017 18th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128692729","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 : 2017-12-01DOI: 10.1109/PDCAT.2017.00053
Hui Tian, Xiaoping Zhou, Jingtian Liu
With growth of networks, it’s demanding to predict the development of network traffic. In this paper, we analyze the network traffic based on the hybrid neural network model. The chaotic property of traffic data is verified by analyzing the chaos characteristics of the data. Based on the study of artificial neural network, wavelet transform theory and quantum genetic algorithm, we propose a neural network optimization method based on efficient global search capability of quantum genetic algorithm. The proposed quantum genetic artificial neural network model can predict the network traffic more accurately. The prediction results can be used to monitor the network anomaly in network security field, and improve the quality of service. The results will also benefit to search efficient network optimization solutions by predicting network behavior.
{"title":"A Hybrid Network Traffic Prediction Model Based on Optimized Neural Network","authors":"Hui Tian, Xiaoping Zhou, Jingtian Liu","doi":"10.1109/PDCAT.2017.00053","DOIUrl":"https://doi.org/10.1109/PDCAT.2017.00053","url":null,"abstract":"With growth of networks, it’s demanding to predict the development of network traffic. In this paper, we analyze the network traffic based on the hybrid neural network model. The chaotic property of traffic data is verified by analyzing the chaos characteristics of the data. Based on the study of artificial neural network, wavelet transform theory and quantum genetic algorithm, we propose a neural network optimization method based on efficient global search capability of quantum genetic algorithm. The proposed quantum genetic artificial neural network model can predict the network traffic more accurately. The prediction results can be used to monitor the network anomaly in network security field, and improve the quality of service. The results will also benefit to search efficient network optimization solutions by predicting network behavior.","PeriodicalId":119197,"journal":{"name":"2017 18th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128605825","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 : 2017-12-01DOI: 10.1109/PDCAT.2017.00072
Yu-Ching Lin
The information and communication technologies (ICT) integrate different types of wireless communication to provide IT-enabled services and applications. The great majority end devices are equipped with multiple network interfaces such as Wi-Fi and 4G. Our goal is to integrate the available network interfaces and technologies to enhance seamless communication efficiency and increase resources utilization. We proposed a heterogeneous network management algorithm which includes roaming and sharing functions. The roaming function provides the multiple network resources in physical and media access control layers. The sharing function supports multiple network resources allocation and the service handover process based on the Multipath TCP protocol. The simulation result also shows that the proposed scheme can increase the network bandwidth utilization effectively. The sharing system could be used in home, mobile and vehicular environments to realize ubiquitous social sharing networks.
{"title":"An Intelligent Network Sharing System Design with Multipath TCP","authors":"Yu-Ching Lin","doi":"10.1109/PDCAT.2017.00072","DOIUrl":"https://doi.org/10.1109/PDCAT.2017.00072","url":null,"abstract":"The information and communication technologies (ICT) integrate different types of wireless communication to provide IT-enabled services and applications. The great majority end devices are equipped with multiple network interfaces such as Wi-Fi and 4G. Our goal is to integrate the available network interfaces and technologies to enhance seamless communication efficiency and increase resources utilization. We proposed a heterogeneous network management algorithm which includes roaming and sharing functions. The roaming function provides the multiple network resources in physical and media access control layers. The sharing function supports multiple network resources allocation and the service handover process based on the Multipath TCP protocol. The simulation result also shows that the proposed scheme can increase the network bandwidth utilization effectively. The sharing system could be used in home, mobile and vehicular environments to realize ubiquitous social sharing networks.","PeriodicalId":119197,"journal":{"name":"2017 18th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121441224","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 : 2017-12-01DOI: 10.1109/PDCAT.2017.00020
Xue Zhang, Yibo Wang, Pin Lv
Bus body advertising planners have been plagued for a long time for formulating solutions effectively and comparing different solutions efficiently, because there is no such decision support system. In this study, we attempt to use the state-of-the-art data mining and visualization techniques to solve this problem. Using the traffic data, we design a visual analytics system named IBBAS (Intelligent Bus Body Advertising System). This system can deal with two main challenges of the problem: new brand promotion and target group advertising. First, we propose two algorithms: DivideT and EstimateT. DivideT is used for the bus frequency division and EsitimateT is used for the bus arrival time estimation. Then, based on LDA topic model, we design an optimization algorithm to generate bus body advertising solution based on multiple constraints. Finally, we use the visualization techniques to create a system. There are some functional modules used in the system: the heatmap changing with time displays the passenger flow volume of each bus station; the candidate panel allows users to expediently modify the original solution and forms a tailored solution; the compare panel clearly uncovers the differences among multiple solutions with a flexible ranking tool. This system has been demonstrated using case studies with a real-world dataset. We also collected feedback from domain experts and conducted a preliminary evaluation criteria.
长期以来，由于缺乏这样的决策支持系统，客车车身广告策划人员一直困扰着如何有效地制定方案，并对不同方案进行高效的比较。在本研究中，我们尝试使用最先进的数据挖掘和可视化技术来解决这个问题。利用交通数据，我们设计了一个可视化分析系统IBBAS (Intelligent Bus Body Advertising system，智能车身广告系统)。该系统可以处理两个主要挑战问题:新品牌推广和目标群体广告。首先，我们提出了两种算法:divide和EstimateT。divide用于总线频率划分，EsitimateT用于总线到达时间估计。然后，基于LDA主题模型，设计了一种基于多约束条件的车身广告生成优化算法。最后，我们使用可视化技术来创建一个系统。系统采用了几个功能模块:随时间变化的热图显示各公交站点的客流量;候选面板允许用户方便地修改原始解决方案并形成定制解决方案;比较面板通过灵活的排名工具清楚地揭示了多个解决方案之间的差异。该系统已通过实际数据集的案例研究进行了演示。我们还收集了领域专家的反馈，并进行了初步的评估标准。
{"title":"IBBAS: A Visual Analytics System of Large-Scale Traffic Data for Bus Body Advertising","authors":"Xue Zhang, Yibo Wang, Pin Lv","doi":"10.1109/PDCAT.2017.00020","DOIUrl":"https://doi.org/10.1109/PDCAT.2017.00020","url":null,"abstract":"Bus body advertising planners have been plagued for a long time for formulating solutions effectively and comparing different solutions efficiently, because there is no such decision support system. In this study, we attempt to use the state-of-the-art data mining and visualization techniques to solve this problem. Using the traffic data, we design a visual analytics system named IBBAS (Intelligent Bus Body Advertising System). This system can deal with two main challenges of the problem: new brand promotion and target group advertising. First, we propose two algorithms: DivideT and EstimateT. DivideT is used for the bus frequency division and EsitimateT is used for the bus arrival time estimation. Then, based on LDA topic model, we design an optimization algorithm to generate bus body advertising solution based on multiple constraints. Finally, we use the visualization techniques to create a system. There are some functional modules used in the system: the heatmap changing with time displays the passenger flow volume of each bus station; the candidate panel allows users to expediently modify the original solution and forms a tailored solution; the compare panel clearly uncovers the differences among multiple solutions with a flexible ranking tool. This system has been demonstrated using case studies with a real-world dataset. We also collected feedback from domain experts and conducted a preliminary evaluation criteria.","PeriodicalId":119197,"journal":{"name":"2017 18th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115949891","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 : 2017-12-01DOI: 10.1109/PDCAT.2017.00045
Emna Ammar El Hadj Amour, Sonia Ayachi Ghannouchi
Organizations need to continually improve and review their critical business processes. In addition, it is crucial not only to track the business process (BP) behavior and to derive key performance indicators (KPIs) but also to understand all necessary concepts and incorporate domain knowledge of the field. The purpose of this paper is to gain a deeper understanding of the interrelationships between all concepts and performance measurement raw data to extract their real meaning. In order to meet these challenges, first, we explore several qualitative and quantitative indicators for measuring the performance of BPs. Second, we develop a new ontology for the representation of these performance indicators. Then, we are based on data mining techniques to extract the most important information from data measurement and to discover all necessary relationships between indicators.
{"title":"Applying Data Mining Techniques to Discover KPIs Relationships in Business Process Context","authors":"Emna Ammar El Hadj Amour, Sonia Ayachi Ghannouchi","doi":"10.1109/PDCAT.2017.00045","DOIUrl":"https://doi.org/10.1109/PDCAT.2017.00045","url":null,"abstract":"Organizations need to continually improve and review their critical business processes. In addition, it is crucial not only to track the business process (BP) behavior and to derive key performance indicators (KPIs) but also to understand all necessary concepts and incorporate domain knowledge of the field. The purpose of this paper is to gain a deeper understanding of the interrelationships between all concepts and performance measurement raw data to extract their real meaning. In order to meet these challenges, first, we explore several qualitative and quantitative indicators for measuring the performance of BPs. Second, we develop a new ontology for the representation of these performance indicators. Then, we are based on data mining techniques to extract the most important information from data measurement and to discover all necessary relationships between indicators.","PeriodicalId":119197,"journal":{"name":"2017 18th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124400690","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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