Pub Date : 2019-08-01DOI: 10.1109/FiCloud.2019.00047
Marcin Bajer
Building automation systems have been already around for many years. Unfortunately, the still high cost of smart building installation is difficult to justify for many noncommercial applications such as residential buildings and houses. The ongoing IoT revolution and popularization of low-cost ubiquitous networking changes drastically the situation. Nowadays, using off-the-shelf hardware and cloud based computing, it is easier to provide to the end user the intelligent solution which can be easily deployed and do not require significant building refurbishment. Even partial implementation of smart building concept will result in increase of energy efficiency as well as comfort of building occupants. In this paper, the solution for controlling and monitoring energy consumption in medium size rent building (12 flats) is presented. The idea of the project was to use ready-made, commercially available hardware and extend its functionalities with custom software. In addition, the Elasticsearch database was used to store energy usage data.
{"title":"Building Advanced Metering Infrastructure using Elasticsearch Database and IEC 62056-21 Protocol","authors":"Marcin Bajer","doi":"10.1109/FiCloud.2019.00047","DOIUrl":"https://doi.org/10.1109/FiCloud.2019.00047","url":null,"abstract":"Building automation systems have been already around for many years. Unfortunately, the still high cost of smart building installation is difficult to justify for many noncommercial applications such as residential buildings and houses. The ongoing IoT revolution and popularization of low-cost ubiquitous networking changes drastically the situation. Nowadays, using off-the-shelf hardware and cloud based computing, it is easier to provide to the end user the intelligent solution which can be easily deployed and do not require significant building refurbishment. Even partial implementation of smart building concept will result in increase of energy efficiency as well as comfort of building occupants. In this paper, the solution for controlling and monitoring energy consumption in medium size rent building (12 flats) is presented. The idea of the project was to use ready-made, commercially available hardware and extend its functionalities with custom software. In addition, the Elasticsearch database was used to store energy usage data.","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125256373","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 : 2019-08-01DOI: 10.1109/FiCloud.2019.00018
Yue Li, Tomasz Osiński, Abdulhalim Dandoush
BGP/MPLS IP VPN is a traditional L3 tunneling and inter-sites routing solution and it can be used for the intra Data Center (DC) network. With the emergence of Software Defined Networking (SDN) scheme, BGP/MPLS IP VPN can be extended via the Extensible Messaging and Presence Protocol (XMPP) to provide a multi-tenants isolation solution for Software-Defined cloud networks. In this work, we propose and implement a multi-tenants isolation solution using the Open Networking Operating System (ONOS) framework which is a very popular open source SDN controller maintained by the Open Networking Foundation (ONF). We use XMPP protocol as its southbound interface. We show how this solution can be deployed and used in both real and emulated environments. A performance comparison between the XMPP and the OpenFlow-based SBIs is provided via experimentation results. The results demonstrate the efficiency and the scalability of the XMPP-based solution. Our work is modular and easily extensible, which enables new use cases based on ONOS.
BGP/MPLS IP VPN是一种传统的三层隧道和跨站路由解决方案，适用于数据中心内部网络。随着SDN (Software Defined Networking)方案的出现，BGP/MPLS IP VPN可以通过XMPP (Extensible Messaging and Presence Protocol)协议进行扩展，为软件定义云网络提供多租户隔离解决方案。在这项工作中，我们使用开放网络操作系统(ONOS)框架提出并实现了一个多租户隔离解决方案，该框架是一个非常流行的开源SDN控制器，由开放网络基金会(ONF)维护。我们使用XMPP协议作为其南向接口。我们将展示如何在真实环境和模拟环境中部署和使用此解决方案。通过实验结果比较了XMPP和基于openflow的sbi之间的性能。结果证明了基于xmpp的解决方案的效率和可扩展性。我们的工作是模块化的，易于扩展，这使得基于ONOS的新用例成为可能。
{"title":"Enabling Multi-Tenants Isolation for Software-Defined Cloud Networks via XMPP and BGP: Implementation and Evaluation","authors":"Yue Li, Tomasz Osiński, Abdulhalim Dandoush","doi":"10.1109/FiCloud.2019.00018","DOIUrl":"https://doi.org/10.1109/FiCloud.2019.00018","url":null,"abstract":"BGP/MPLS IP VPN is a traditional L3 tunneling and inter-sites routing solution and it can be used for the intra Data Center (DC) network. With the emergence of Software Defined Networking (SDN) scheme, BGP/MPLS IP VPN can be extended via the Extensible Messaging and Presence Protocol (XMPP) to provide a multi-tenants isolation solution for Software-Defined cloud networks. In this work, we propose and implement a multi-tenants isolation solution using the Open Networking Operating System (ONOS) framework which is a very popular open source SDN controller maintained by the Open Networking Foundation (ONF). We use XMPP protocol as its southbound interface. We show how this solution can be deployed and used in both real and emulated environments. A performance comparison between the XMPP and the OpenFlow-based SBIs is provided via experimentation results. The results demonstrate the efficiency and the scalability of the XMPP-based solution. Our work is modular and easily extensible, which enables new use cases based on ONOS.","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122279937","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 : 2019-08-01DOI: 10.1109/FiCloud.2019.00024
M. Barati, O. Rana, George Theodorakopoulos, P. Burnap
Understanding how cloud providers support the European General Data Protection Regulation (GDPR) remains an imporant challenge for new providers emerging on the market. GDPR influences access to, storage, processing and tranmission of data, requiring these operations to be exposed to a user to seek explicit consent. A privacy-aware cloud architecture is proposed that improves transparency and enables the audit trail of providers who accessed the user data to be recorded. The architecture not only supports GDPR compliance by imposing several data protection requirements on cloud providers, but also benefits from a blockchain network that securely stores the providers' operations on the user data. A blockchainbased tracking approach based on a shared privacy agreement implemented as a smart contract is described - providers who violate GDPR rules are automatically reported through a voting mechanism.
{"title":"Privacy-Aware Cloud Ecosystems and GDPR Compliance","authors":"M. Barati, O. Rana, George Theodorakopoulos, P. Burnap","doi":"10.1109/FiCloud.2019.00024","DOIUrl":"https://doi.org/10.1109/FiCloud.2019.00024","url":null,"abstract":"Understanding how cloud providers support the European General Data Protection Regulation (GDPR) remains an imporant challenge for new providers emerging on the market. GDPR influences access to, storage, processing and tranmission of data, requiring these operations to be exposed to a user to seek explicit consent. A privacy-aware cloud architecture is proposed that improves transparency and enables the audit trail of providers who accessed the user data to be recorded. The architecture not only supports GDPR compliance by imposing several data protection requirements on cloud providers, but also benefits from a blockchain network that securely stores the providers' operations on the user data. A blockchainbased tracking approach based on a shared privacy agreement implemented as a smart contract is described - providers who violate GDPR rules are automatically reported through a voting mechanism.","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128452963","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 : 2019-08-01DOI: 10.1109/FiCloud.2019.00056
Ibrahim Alper Koc, T. Serif, Sezer Gören, G. Ghinea
Location-based services are becoming an important part of life and there is an increasing demand for indoor positioning. Combination of GPS and mobile cellular networks has solved the problem for outdoor environments. However, the same level of precision has not been achieved for indoor location estimation. The problem of locating an indoor environment has been studied only recently. Much research contributed to the innovative concept of an indoor positioning system. Considering the cost and the effort involved in the existing location estimation approaches, Augmented Reality (AR) based positioning method is one of the most promising methods to determine the location of a mobile device. Accordingly, in this paper, we propose, implement, and evaluate an AR-based location estimation smartphone application that can be used indoors. The evaluation results show indicate that the proposed application can estimate the location in small areas with an error-rate of 0.31 meters and in large areas with error-rate of 7.8 meters.)
{"title":"Indoor Mapping and Positioning using Augmented Reality","authors":"Ibrahim Alper Koc, T. Serif, Sezer Gören, G. Ghinea","doi":"10.1109/FiCloud.2019.00056","DOIUrl":"https://doi.org/10.1109/FiCloud.2019.00056","url":null,"abstract":"Location-based services are becoming an important part of life and there is an increasing demand for indoor positioning. Combination of GPS and mobile cellular networks has solved the problem for outdoor environments. However, the same level of precision has not been achieved for indoor location estimation. The problem of locating an indoor environment has been studied only recently. Much research contributed to the innovative concept of an indoor positioning system. Considering the cost and the effort involved in the existing location estimation approaches, Augmented Reality (AR) based positioning method is one of the most promising methods to determine the location of a mobile device. Accordingly, in this paper, we propose, implement, and evaluate an AR-based location estimation smartphone application that can be used indoors. The evaluation results show indicate that the proposed application can estimate the location in small areas with an error-rate of 0.31 meters and in large areas with error-rate of 7.8 meters.)","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127439948","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 : 2019-08-01DOI: 10.1109/ficloud.2019.00002
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Pub Date : 2019-08-01DOI: 10.1109/ficloud.2019.00001
{"title":"[Title page i]","authors":"","doi":"10.1109/ficloud.2019.00001","DOIUrl":"https://doi.org/10.1109/ficloud.2019.00001","url":null,"abstract":"","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115201787","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 : 2019-08-01DOI: 10.1109/FiCloud.2019.00045
Kaumudi Singh, K. NitheshNayak, Anup A. Kedilaya, T. V. Prabhakar, J. Kuri
Battery-less sensor networks, that harvest energy from the ambient, have attracted much attention in the last few years due to the promise of low maintenance and untethered perpetual operation. However, the major challenge in such networks is that the availability of nodes in the network depends on the energy profile of their harvesting sources. This might affect network reliability. In this work, we study the suitability of Energy Harvesting Sensor (EHS) nodes, powered using light and vibrations, for a simple temperature monitoring application. We evaluate whether such an EHS node-based system can sustain itself and compare its performance with that of a traditional battery-based system. To economize on energy expenditure in the EHS system, we implement an Autoregressive (AR) model based adaptive sampling algorithm on the EHS nodes. After thorough experimental investigations, we conclude that the EHS node-based system fares quite well. Results show that adaptive sampling helps achieve energy savings of 62.12% and a 52.33% reduction in the amount of sampled data.
{"title":"Systems that Sustain Themselves: Energy Harvesting Sensor Nodes for Monitoring the Environment","authors":"Kaumudi Singh, K. NitheshNayak, Anup A. Kedilaya, T. V. Prabhakar, J. Kuri","doi":"10.1109/FiCloud.2019.00045","DOIUrl":"https://doi.org/10.1109/FiCloud.2019.00045","url":null,"abstract":"Battery-less sensor networks, that harvest energy from the ambient, have attracted much attention in the last few years due to the promise of low maintenance and untethered perpetual operation. However, the major challenge in such networks is that the availability of nodes in the network depends on the energy profile of their harvesting sources. This might affect network reliability. In this work, we study the suitability of Energy Harvesting Sensor (EHS) nodes, powered using light and vibrations, for a simple temperature monitoring application. We evaluate whether such an EHS node-based system can sustain itself and compare its performance with that of a traditional battery-based system. To economize on energy expenditure in the EHS system, we implement an Autoregressive (AR) model based adaptive sampling algorithm on the EHS nodes. After thorough experimental investigations, we conclude that the EHS node-based system fares quite well. Results show that adaptive sampling helps achieve energy savings of 62.12% and a 52.33% reduction in the amount of sampled data.","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114751397","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}
User interaction with smart devices is challenging when there are multiple devices that can perform the required task. Disambiguating between similar devices is a common problem that user faces when controlling devices from an app or from voice enabled smart assistants, because of the time required to interact. Moreover user command might be incomplete in case of smart assistants, leading to further challenges in identifying the user intended device. To predict the user intended device, we propose a machine learning based device disambiguation service using XGBoost algorithm. The predictions are based out of historical usage pattern of smart home users and is personalized for them. The machine learning model is optimized using random search over hyper-parameters in a completely automated fashion, which ensures optimum user experience. The solution addresses the important problem of identifying the device intended by the user and is a suitable platform for further improvements in voice assistant enabled smart home experience.
{"title":"Intelligent Device Disambiguation for Smart Home Control","authors":"Siddharth Chaudhary, Shalabh Singh, Vijaya Kumar Tukka, Vinisha Parwal, Siddhartha Sinha","doi":"10.1109/FiCloud.2019.00050","DOIUrl":"https://doi.org/10.1109/FiCloud.2019.00050","url":null,"abstract":"User interaction with smart devices is challenging when there are multiple devices that can perform the required task. Disambiguating between similar devices is a common problem that user faces when controlling devices from an app or from voice enabled smart assistants, because of the time required to interact. Moreover user command might be incomplete in case of smart assistants, leading to further challenges in identifying the user intended device. To predict the user intended device, we propose a machine learning based device disambiguation service using XGBoost algorithm. The predictions are based out of historical usage pattern of smart home users and is personalized for them. The machine learning model is optimized using random search over hyper-parameters in a completely automated fashion, which ensures optimum user experience. The solution addresses the important problem of identifying the device intended by the user and is a suitable platform for further improvements in voice assistant enabled smart home experience.","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114757233","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 : 2019-08-01DOI: 10.1109/ficloud.2019.00005
On behalf of the organizing committee, we welcome you to the 7th International Conference on Future Internet of Things and Cloud (FiCloud-2019), IEEE CS-TCI, which is held during 26-28 August 2019, in Istanbul, Turkey. Istanbul is one of the major cities in Turkey wherein Europe and Asia meets across the Bosphorus Strait. Istanbul attracts a large number of visitors from different countries due to a combination of magnificent attractions such as centuries-old mosques, churches, traditional markets and modern restaurants and galleries. Alongside the attractions of Istanbul, we are delighted to see that FiCloud has become an established conference in the area of cloud computing and IoT and it is attracting an increasing number of participants every year. We are also pleased that the program committee has put together an interesting technical program which comprises a number of sessions that includes keynote, industrial talks and technical papers. We believe that the conference will provide useful opportunity to the participants for sharing ideas and establishing research network with colleagues from different countries across the world. The FiCloud 2019 focuses on new and emerging topics in the area of cloud and IoT which have been established as major modern IT platforms. Cloud and IoT have been used in various domains such as smart cities, home and office automation, healthcare services, weather and environment, transportation and so on. This year call-for-papers has generated significant interest in the research and development community and has attracted a large number of submissions from authors across different countries of the world. All the submitted papers went through a rigorous review process. Based on the reviews, 57 papers were accepted for the conference, which include, regular and short papers. The acceptance rate for the regular papers is 29%. Accepted papers have been organized into different technical sessions which span the three days of the conference. Technical sessions are related to various aspects of Cloud Computing and IoT such as security and privacy, smart environment, data and knowledge management, software-define network, fog and edge computing, energy efficiency, multimedia data and advanced networks. The success of the FiCloud conference involves contributions from many people in planning and organizing the technical program, social events and local arrangements. We are very grateful of the Local Organizing Chairs, Perin Unal (Teknopar, Turkey), Tacha Serif and Sezer Gören Uğurdağ (Yeditepe University, Turkey). We would like to thank Vincenzo Piuri, (General Co-Chair), Filipe Portela (Workshop Coordinator), Joyce El Haddad (Publicity Chair), Lin Guan, (Journal Special Issue Coordinator) and Barbara Masucci (Publication Chair). We thank members of the Program Committee for helping in the review process and for providing timely and constructive feedback to the authors. We are deeply indebted to the track chairs, Antonio
我们代表组委会欢迎您参加于2019年8月26日至28日在土耳其伊斯坦布尔举行的第七届未来物联网与云国际会议(FiCloud-2019)， IEEE CS-TCI。伊斯坦布尔是土耳其的主要城市之一，欧洲和亚洲横跨博斯普鲁斯海峡。伊斯坦布尔吸引了大量来自不同国家的游客，因为它有许多宏伟的景点，比如有几百年历史的清真寺、教堂、传统市场和现代餐馆和画廊。除了伊斯坦布尔的吸引力，我们很高兴看到FiCloud已经成为云计算和物联网领域的成熟会议，每年吸引越来越多的参与者。我们也很高兴项目委员会组织了一个有趣的技术项目，其中包括主题演讲、工业会谈和技术论文。我们相信，这次会议将为与会者提供一个与来自世界不同国家的同事交流思想和建立研究网络的有益机会。FiCloud 2019专注于云计算和物联网领域的新兴主题，这些领域已成为主要的现代IT平台。云和物联网已被应用于智能城市、家庭和办公自动化、医疗服务、天气和环境、交通等各个领域。今年的论文征集引起了研发界的极大兴趣，并吸引了来自世界各国作者的大量投稿。所有提交的论文都经过了严格的审查程序。根据评审结果，本次会议共接收了57篇论文，其中包括常规论文和短篇论文。普通论文的接受率是29%。被接受的论文被组织成不同的技术会议，这些会议跨越三天的会议。技术会议涉及云计算和物联网的各个方面，如安全与隐私、智能环境、数据和知识管理、软件定义网络、雾和边缘计算、能源效率、多媒体数据和先进网络。FiCloud会议的成功离不开许多人在规划和组织技术项目、社交活动和当地安排方面的贡献。我们非常感谢当地组织主席Perin Unal(土耳其Teknopar)、Tacha Serif和Sezer Gören Uğurdağ(土耳其Yeditepe大学)。我们要感谢Vincenzo Piuri(总联合主席)、Filipe Portela(研讨会协调员)、Joyce El Haddad(宣传主席)、Lin Guan(期刊特刊协调员)和Barbara Masucci(出版主席)。我们感谢项目委员会成员在审查过程中的帮助，并向作者提供及时和建设性的反馈。我们深深感谢田径主席Antonio Celesti、Edmundo Madeira、Helen Karatza、Joyce El Haddad、Khaled Aloufe、Luiz Fernando Bittencourt、Madihah Mohd Saudi、Marcin Bajer、Marisa Catalan Cid、Marwan Hassani、Natalia Kryvinska、Patience anita Namanya、Jules Pagna Disso、Rafael Angarita、Ron Austin、R. Venkatesha Prasad、Tacha Serif、Tuna Tuğcu、Ella Pereira、Vijay S. Rao和a.s.m. Kayes的出色工作和支持。我们对所有向会议提交论文以及在会议期间进行论文展示和讨论的作者表示感谢。我们感谢主讲人和行业发言人Pierangela Samarati(意大利米兰大学)、Soumya Kanti Datta(法国EURECOM)和Gökhan Büyükdığan(土耳其arelik a.s.)的精彩演讲。FiCloud 2019有许多相关的专题讨论会和研讨会，重点关注特定主题。这些包括MobiApp, AIRS2, SoNet, ICI, PMECT, DS4IDS, CSW和AWMA。我们高度赞赏组委会和技术委员会为组织如此宝贵的专题讨论会和讲习班所付出的努力和辛勤工作。我们非常感谢FiCloud国际咨询委员会成员提供的帮助和指导。我们衷心感谢IEEE CS互联网技术委员会(IEEE-CS TCI)对FiCloud 2019技术协办的支持。
{"title":"Message from the FiCloud-2019 Chairs","authors":"","doi":"10.1109/ficloud.2019.00005","DOIUrl":"https://doi.org/10.1109/ficloud.2019.00005","url":null,"abstract":"On behalf of the organizing committee, we welcome you to the 7th International Conference on Future Internet of Things and Cloud (FiCloud-2019), IEEE CS-TCI, which is held during 26-28 August 2019, in Istanbul, Turkey. Istanbul is one of the major cities in Turkey wherein Europe and Asia meets across the Bosphorus Strait. Istanbul attracts a large number of visitors from different countries due to a combination of magnificent attractions such as centuries-old mosques, churches, traditional markets and modern restaurants and galleries. Alongside the attractions of Istanbul, we are delighted to see that FiCloud has become an established conference in the area of cloud computing and IoT and it is attracting an increasing number of participants every year. We are also pleased that the program committee has put together an interesting technical program which comprises a number of sessions that includes keynote, industrial talks and technical papers. We believe that the conference will provide useful opportunity to the participants for sharing ideas and establishing research network with colleagues from different countries across the world. The FiCloud 2019 focuses on new and emerging topics in the area of cloud and IoT which have been established as major modern IT platforms. Cloud and IoT have been used in various domains such as smart cities, home and office automation, healthcare services, weather and environment, transportation and so on. This year call-for-papers has generated significant interest in the research and development community and has attracted a large number of submissions from authors across different countries of the world. All the submitted papers went through a rigorous review process. Based on the reviews, 57 papers were accepted for the conference, which include, regular and short papers. The acceptance rate for the regular papers is 29%. Accepted papers have been organized into different technical sessions which span the three days of the conference. Technical sessions are related to various aspects of Cloud Computing and IoT such as security and privacy, smart environment, data and knowledge management, software-define network, fog and edge computing, energy efficiency, multimedia data and advanced networks. The success of the FiCloud conference involves contributions from many people in planning and organizing the technical program, social events and local arrangements. We are very grateful of the Local Organizing Chairs, Perin Unal (Teknopar, Turkey), Tacha Serif and Sezer Gören Uğurdağ (Yeditepe University, Turkey). We would like to thank Vincenzo Piuri, (General Co-Chair), Filipe Portela (Workshop Coordinator), Joyce El Haddad (Publicity Chair), Lin Guan, (Journal Special Issue Coordinator) and Barbara Masucci (Publication Chair). We thank members of the Program Committee for helping in the review process and for providing timely and constructive feedback to the authors. We are deeply indebted to the track chairs, Antonio","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114892263","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 : 2019-08-01DOI: 10.1109/ficloud.2019.00006
{"title":"FiCloud-2019 Organizing Committee","authors":"","doi":"10.1109/ficloud.2019.00006","DOIUrl":"https://doi.org/10.1109/ficloud.2019.00006","url":null,"abstract":"","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121217356","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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