2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)最新文献_第4页

Practical Enhancement and Evaluation of a Low-Latency Network Model Using Mobile Edge Computing 使用移动边缘计算的低延迟网络模型的实际增强和评估

2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC) Pub Date : 2017-07-04 DOI: 10.1109/COMPSAC.2017.190

Krittin Intharawijitr, K. Iida, H. Koga, K. Yamaoka

{"title":"Practical Enhancement and Evaluation of a Low-Latency Network Model Using Mobile Edge Computing","authors":"Krittin Intharawijitr, K. Iida, H. Koga, K. Yamaoka","doi":"10.1109/COMPSAC.2017.190","DOIUrl":"https://doi.org/10.1109/COMPSAC.2017.190","url":null,"abstract":"Most of latency-sensitive mobile applications require computational resources provided through a cloud computing service. The problem of relying on cloud computing is that, sometimes, the physical locations of cloud servers are distant from mobile users and the communication latency is long. As a result, the concept of distributed cloud service, called mobile edge computing (MEC), is being introduced in the 5G network. However, MEC can reduce only the communication latency. The computing latency in MEC must also be considered to satisfy the required total latency of services. In this research, we study the impact of both latencies in MEC architecture with regard to latency-sensitive services. We also consider a centralized model, in which we use a controller to manage flows between users and mobile edge resources to analyze MEC in a practical architecture. The simulation results show that the controller interval and hop delay lead some blocking and error in the system. However the permissive system which relaxes latency constrains and chooses an edge server by the lowest total latency can improve the system performance impressively.","PeriodicalId":6556,"journal":{"name":"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)","volume":"63 1","pages":"567-574"},"PeriodicalIF":0.0,"publicationDate":"2017-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87152763","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}

引用次数: 17

Efficient Worker Selection Through History-Based Learning in Crowdsourcing 基于历史学习的众包高效工人选择

2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC) Pub Date : 2017-07-04 DOI: 10.1109/COMPSAC.2017.275

T. Awwad, N. Bennani, Konstantin Ziegler, V. Rehn-Sonigo, L. Brunie, H. Kosch

引用次数: 7

Enhancing Breeder Document Long-Term Security Using Blockchain Technology 使用区块链技术增强育种者文件的长期安全性

2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC) Pub Date : 2017-07-04 DOI: 10.1109/COMPSAC.2017.119

Nicolas Buchmann, C. Rathgeb, Harald Baier, C. Busch, Marian Margraf

引用次数: 28

Applying Feature Selection to Software Defect Prediction Using Multi-objective Optimization 特征选择在多目标优化软件缺陷预测中的应用

2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC) Pub Date : 2017-07-04 DOI: 10.1109/COMPSAC.2017.65

Xiang Chen, Yuxiang Shen, Zhanqi Cui, Xiaolin Ju

引用次数: 27

Building Energy Modelling and Monitoring by Integration of IoT Devices and Building Information Models 物联网设备与建筑信息模型集成的建筑能源建模与监测

2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC) Pub Date : 2017-07-04 DOI: 10.1109/COMPSAC.2017.75

Lorenzo Bottaccioli, Alessandro Aliberti, F. Ugliotti, E. Patti, A. Osello, E. Macii, A. Acquaviva

{"title":"Building Energy Modelling and Monitoring by Integration of IoT Devices and Building Information Models","authors":"Lorenzo Bottaccioli, Alessandro Aliberti, F. Ugliotti, E. Patti, A. Osello, E. Macii, A. Acquaviva","doi":"10.1109/COMPSAC.2017.75","DOIUrl":"https://doi.org/10.1109/COMPSAC.2017.75","url":null,"abstract":"In recent years, the research about energy waste and CO2 emission reduction has gained a strong momentum, also pushed by European and national funding initiatives. The main purpose of this large effort is to reduce the effects of greenhouse emission, climate change to head for a sustainable society. In this scenario, Information and Communication Technologies (ICT) play a key role. From one side, advances in physical and environmental information sensing, communication and processing, enabled the monitoring of energy behaviour of buildings in real-time. The access to this information has been made easy and ubiquitous thank to Internet-of-Things (IoT) devices and protocols. From the other side, the creation of digital repositories of buildings and districts (i.e. Building Information Models - BIM) enabled the development of complex and rich energy models that can be used for simulation and prediction purposes. As such, an opportunity is emerging of mixing these two information categories to either create better models and to detect unwanted or inefficient energy behaviours. In this paper, we present a software architecture for management and simulation of energy behaviours in buildings that integrates heterogeneous data such as BIM, IoT, GIS (Geographical Information System) and meteorological services. This integration allows: i) (near-) real-time visualisation of energy consumption information in the building context and ii) building performance evaluation through energy modelling and simulation exploiting data from the field and real weather conditions. Finally, we discuss the experimental results obtained in a real-world case-study.","PeriodicalId":6556,"journal":{"name":"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)","volume":"24 1","pages":"914-922"},"PeriodicalIF":0.0,"publicationDate":"2017-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91163801","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}

引用次数: 68

A Study of Machine Learning in Healthcare 医疗保健中的机器学习研究

2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC) Pub Date : 2017-07-04 DOI: 10.1109/COMPSAC.2017.164

Rohan Bhardwaj, Ankita R. Nambiar, Debojyoti Dutta

引用次数: 124

FeSCH: A Feature Selection Method using Clusters of Hybrid-data for Cross-Project Defect Prediction FeSCH:一种基于混合数据簇的跨项目缺陷预测特征选择方法

2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC) Pub Date : 2017-07-04 DOI: 10.1109/COMPSAC.2017.127

Chao Ni, Wangshu Liu, Qing Gu, Xiang Chen, Daoxu Chen

{"title":"FeSCH: A Feature Selection Method using Clusters of Hybrid-data for Cross-Project Defect Prediction","authors":"Chao Ni, Wangshu Liu, Qing Gu, Xiang Chen, Daoxu Chen","doi":"10.1109/COMPSAC.2017.127","DOIUrl":"https://doi.org/10.1109/COMPSAC.2017.127","url":null,"abstract":"Cross project defect prediction (CPDP) is a challenging task since the predictor built on the source projects can hardly generalize well to the target project. Previous studies have shown that both feature mapping and feature selection can alleviate the differences between the source and target projects. In this paper, we propose a novel method FeSCH (Feature Selection using Clusters of Hybrid-data). In particular it includes two phases. The first is the feature clustering phase, which uses a density-based clustering method DPC to group highly co-related features into clusters. The second is the feature selection phase, which selects beneficial features from each cluster. We design three ranking strategies to choose appropriate features. During the empirical studies, we design experiments based on real-world software projects, and evaluate the prediction performance of FeSCH by analyzing the influence of ranking strategies. The experimental results show that FeSCH can outperform three baseline methods (i.e., WPDP, ALL, and TCA+) in most cases, and its performance is independent of the used classifiers.","PeriodicalId":6556,"journal":{"name":"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)","volume":"3 1","pages":"51-56"},"PeriodicalIF":0.0,"publicationDate":"2017-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75551963","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}

引用次数: 24

Cybersecurity of Wearable Devices: An Experimental Analysis and a Vulnerability Assessment Method 可穿戴设备网络安全:实验分析与漏洞评估方法

2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC) Pub Date : 2017-07-04 DOI: 10.1109/COMPSAC.2017.96

Matteo Langone, R. Setola, Javier López

引用次数: 14

A Constraint-Pattern Based Method for Reachability Determination 基于约束模式的可达性确定方法

2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC) Pub Date : 2017-07-04 DOI: 10.1109/COMPSAC.2017.12

Yuexing Wang, Zuxing Gu, Xi Cheng, Min Zhou, Xiaoyu Song, M. Gu, Jiaguang Sun

{"title":"A Constraint-Pattern Based Method for Reachability Determination","authors":"Yuexing Wang, Zuxing Gu, Xi Cheng, Min Zhou, Xiaoyu Song, M. Gu, Jiaguang Sun","doi":"10.1109/COMPSAC.2017.12","DOIUrl":"https://doi.org/10.1109/COMPSAC.2017.12","url":null,"abstract":"When analyzing programs using static program analysis, we need to determine the reachability of each possible execution path of the programs. Many static analysis tools collect constraints of each path and use SMT solvers to determine the satisfiability of these constraints. The accumulated computing time can be long if we use SMT solvers too many times. In this paper, we propose a constraint-pattern based method for reachability determination to address the limitation of current approaches. We define some constraint-patterns. For each pattern, a carefully designed constraints solving algorithm is presented. Our method contains two steps. Firstly, we collect some information about the constraints in the program to be analyzed. Then we choose the most suitable algorithm for reachability determination based on the information. Secondly, we apply the algorithm in analysis process to speed up satisfiability checking of path constraints. We implement our method based on CPAchecker, a famous software verification tool. The experimental results on some well-known benchmarks show that, with a moderate accuracy, our method is more efficient in comparison with some state-of-the-art SMT solvers.","PeriodicalId":6556,"journal":{"name":"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)","volume":"7 1","pages":"85-90"},"PeriodicalIF":0.0,"publicationDate":"2017-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83914137","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}

引用次数: 1

On the Deployment of Healthcare Applications over Fog Computing Infrastructure 在雾计算基础设施上部署医疗保健应用程序

2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC) Pub Date : 2017-07-04 DOI: 10.1109/COMPSAC.2017.178

O. Akribopoulos, I. Chatzigiannakis, C. Tselios, A. Antoniou

{"title":"On the Deployment of Healthcare Applications over Fog Computing Infrastructure","authors":"O. Akribopoulos, I. Chatzigiannakis, C. Tselios, A. Antoniou","doi":"10.1109/COMPSAC.2017.178","DOIUrl":"https://doi.org/10.1109/COMPSAC.2017.178","url":null,"abstract":"Fog computing is considered as the most promising enhancement of the traditional cloud computing paradigm in order to handle potential issues introduced by the emerging Interned of Things (IoT) framework at the network edge. The heterogeneous nature, the extensive distribution and the hefty number of deployed IoT nodes will disrupt existing functional models, creating confusion. However, IoT will facilitate the rise of new applications, with automated healthcare monitoring platforms being amongst them. This paper presents the pillars of design for such applications, along with the evaluation of a working prototype that collects ECG traces from a tailor-made device and utilizes the patient's smartphone as a Fog gateway for securely sharing them to other authorized entities. This prototype will allow patients to share information to their physicians, monitor their health status independently and notify the authorities rapidly in emergency situations. Historical data will also be available for further analysis, towards identifying patterns that may improve medical diagnoses in the foreseeable future.","PeriodicalId":6556,"journal":{"name":"2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)","volume":"69 1","pages":"288-293"},"PeriodicalIF":0.0,"publicationDate":"2017-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84282566","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}

引用次数: 70