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.2019.00045
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}
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.2019.00033
O. Makinde, A. Sangodoyin, Bashir Mohammed, D. Neagu, Umaru Adamu
Distributed network behaviour is increasingly attracting huge attention both in academics and industrial initiatives, and most recently machine learning has been used in every possible field, leveraging its advantages.Typically, a distributed networking allows for the execution of distributed applications which results in complex behaviours among connected systems. This complexity in itself can create grey areas and vulnerabilities in the securities of these networks, therefore predicting the behaviour of these systems both at the macro and micro level has become essential. In the past most researchers have predicted network behaviour and network attack patterns by using aggregated data, but in this paper we focus on the application of machine learning at the individual user level such that the prediction of the individual network user behaviour pattern at the micro level becomes a substasive tool in creating a realistic agent based simulation of the whole distributed network, which in turn can serve as a test bed for predicting what-if scenarios such as network attacks on the target system or exposing vulnerabilities within the target system. The simulation result was validated by comparing the simulated interaction within the simulated network to the data logged in the server logs within the real life network system. This produced a correlation above 0.8, indicating a realistic model.
{"title":"Distributed Network Behaviour Prediction Using Machine Learning and Agent-Based Micro Simulation","authors":"O. Makinde, A. Sangodoyin, Bashir Mohammed, D. Neagu, Umaru Adamu","doi":"10.1109/FiCloud.2019.00033","DOIUrl":"https://doi.org/10.1109/FiCloud.2019.00033","url":null,"abstract":"Distributed network behaviour is increasingly attracting huge attention both in academics and industrial initiatives, and most recently machine learning has been used in every possible field, leveraging its advantages.Typically, a distributed networking allows for the execution of distributed applications which results in complex behaviours among connected systems. This complexity in itself can create grey areas and vulnerabilities in the securities of these networks, therefore predicting the behaviour of these systems both at the macro and micro level has become essential. In the past most researchers have predicted network behaviour and network attack patterns by using aggregated data, but in this paper we focus on the application of machine learning at the individual user level such that the prediction of the individual network user behaviour pattern at the micro level becomes a substasive tool in creating a realistic agent based simulation of the whole distributed network, which in turn can serve as a test bed for predicting what-if scenarios such as network attacks on the target system or exposing vulnerabilities within the target system. The simulation result was validated by comparing the simulated interaction within the simulated network to the data logged in the server logs within the real life network system. This produced a correlation above 0.8, indicating a realistic model.","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"11 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":"115963760","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.2019.00019
A. Sangodoyin, Bashir Mohammed, S. Moyo, I. Awan, Jules Pagna Disso
Software Defined Network is an evolving and promising architecture which allows greater control over network entities by centralising the control plane. Although on the surface SDN provides a simple framework for network programmability and monitoring, few has been said about security measures to make it more robust to hitherto security flaws. Among the identified security flaws, DDoS flooding attack continue to be one of the major security concerns as attack volumes are increasing year on year. In this paper, we developed and implement the feasibility of spoofing and flooding DDoS attack on data plane devices using Mininet emulator, floodlight and network performance testing tools. We further developed a mitigation mechanism to counter these attacks by pushing reactive flow through the controller to the attacking switch port. Our result shows that pushing flows through the controller mitigates the flooding attack with low performance overheads, and requires no change to the controllers mode of operation for deployment, which indicates a good performance of our model.
{"title":"A Framework for Distributed Denial of Service Attack Detection and Reactive Countermeasure in Software Defined Network","authors":"A. Sangodoyin, Bashir Mohammed, S. Moyo, I. Awan, Jules Pagna Disso","doi":"10.1109/FiCloud.2019.00019","DOIUrl":"https://doi.org/10.1109/FiCloud.2019.00019","url":null,"abstract":"Software Defined Network is an evolving and promising architecture which allows greater control over network entities by centralising the control plane. Although on the surface SDN provides a simple framework for network programmability and monitoring, few has been said about security measures to make it more robust to hitherto security flaws. Among the identified security flaws, DDoS flooding attack continue to be one of the major security concerns as attack volumes are increasing year on year. In this paper, we developed and implement the feasibility of spoofing and flooding DDoS attack on data plane devices using Mininet emulator, floodlight and network performance testing tools. We further developed a mitigation mechanism to counter these attacks by pushing reactive flow through the controller to the attacking switch port. Our result shows that pushing flows through the controller mitigates the flooding attack with low performance overheads, and requires no change to the controllers mode of operation for deployment, which indicates a good performance of our model.","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"46 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":"114631282","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.2019.00040
Cristian Lai, Francesco Boi, Alberto Buschettu, Renato Caboni
In this paper, we will illustrate how microservice architectures can be adopted to build Internet of Things services for multimobility in a smart city. Traditional centralized architectures are built as monolithic solutions, which lack the flexibility required to deal with heterogeneous devices efficiently. Microservice architectures implement small features bounded within a running process; independent microservices can be deployed separately in a distributed system. We have proposed a draft of architecture for general-purpose Internet of Things applications. Thanks to the choice of the microservice paradigm, the architecture is capable of interfacing with a wide range of heterogeneous IoT devices while implementing scalability by design. On this basis, a web application has been developed bearing in mind a set of real case scenarios mobility services for citizens multimobility in a smart city.
{"title":"IoT and Microservice Architecture for Multimobility in a Smart City","authors":"Cristian Lai, Francesco Boi, Alberto Buschettu, Renato Caboni","doi":"10.1109/FiCloud.2019.00040","DOIUrl":"https://doi.org/10.1109/FiCloud.2019.00040","url":null,"abstract":"In this paper, we will illustrate how microservice architectures can be adopted to build Internet of Things services for multimobility in a smart city. Traditional centralized architectures are built as monolithic solutions, which lack the flexibility required to deal with heterogeneous devices efficiently. Microservice architectures implement small features bounded within a running process; independent microservices can be deployed separately in a distributed system. We have proposed a draft of architecture for general-purpose Internet of Things applications. Thanks to the choice of the microservice paradigm, the architecture is capable of interfacing with a wide range of heterogeneous IoT devices while implementing scalability by design. On this basis, a web application has been developed bearing in mind a set of real case scenarios mobility services for citizens multimobility in a smart city.","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":"128520375","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.2019.00046
M. Aleksy, F. Dai, Nima Enayati, P. Rost, Guillermo Pocovi
Sensor-based real-time control is being used in robotics for different purposes. The trend is to develop intelligent robots that can understand and react on environmental situations. This leads to the integration of more complex algorithms and involving multiple sensors and mobile assets for a more flexible and intelligent motion control. The requirement on computing power becomes often higher than it could be performed on the robot controller itself. Using an external computer introduces, nowadays, significant communication delays that make real-time control difficult or even impossible. Furthermore, to integrate mobile assets in a motion control scenario wired communication cannot be employed. A 5G network / local factory cloud may bridge this gap. In this paper we describe why 5G technology can make a significant contribution to enable new types of industrial robotics applications. Moreover, we present various use cases and discuss simulation results of a 5G-based robotics application in an industrial environment.
{"title":"Utilizing 5G in Industrial Robotic Applications","authors":"M. Aleksy, F. Dai, Nima Enayati, P. Rost, Guillermo Pocovi","doi":"10.1109/FiCloud.2019.00046","DOIUrl":"https://doi.org/10.1109/FiCloud.2019.00046","url":null,"abstract":"Sensor-based real-time control is being used in robotics for different purposes. The trend is to develop intelligent robots that can understand and react on environmental situations. This leads to the integration of more complex algorithms and involving multiple sensors and mobile assets for a more flexible and intelligent motion control. The requirement on computing power becomes often higher than it could be performed on the robot controller itself. Using an external computer introduces, nowadays, significant communication delays that make real-time control difficult or even impossible. Furthermore, to integrate mobile assets in a motion control scenario wired communication cannot be employed. A 5G network / local factory cloud may bridge this gap. In this paper we describe why 5G technology can make a significant contribution to enable new types of industrial robotics applications. Moreover, we present various use cases and discuss simulation results of a 5G-based robotics application in an industrial environment.","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"105 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":"132410763","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.2019.00059
J. Casademont, Elena López-Aguilera, J. Aspas
Cooperative-Intelligent Transport systems are new applications developed on top of communications between vehicles and between vehicles and fixed infrastructure. Their architecture envisages devices deployed along the routes and streets, transmitting and receiving different kind of messages belonging to different services. Quite often, these devices will be located in isolated places with very low number of vehicles passing nearby. Being in isolated places, these devices will require to be feed with rechargeable batteries and alternative power sources, the usage of which need to be very efficient. The fact of continuously transmitting messages whenever there is no vehicle to receive them demands a solution. In this paper, we propose to use a well-known saving power strategy already used in Internet of Things, the Wake-up Radio systems. As vehicular communications are based on IEEE 802.11 standard, we propose to use a Wake-up Radio system based on this standard as well, being thus no additional hardware needed for the wake-up transmitter. The paper analyses the feasibility of using this solution on several vehicular applications.
{"title":"Wake-Up Radio Systems for Cooperative-Intelligent Transport Systems Architecture","authors":"J. Casademont, Elena López-Aguilera, J. Aspas","doi":"10.1109/FiCloud.2019.00059","DOIUrl":"https://doi.org/10.1109/FiCloud.2019.00059","url":null,"abstract":"Cooperative-Intelligent Transport systems are new applications developed on top of communications between vehicles and between vehicles and fixed infrastructure. Their architecture envisages devices deployed along the routes and streets, transmitting and receiving different kind of messages belonging to different services. Quite often, these devices will be located in isolated places with very low number of vehicles passing nearby. Being in isolated places, these devices will require to be feed with rechargeable batteries and alternative power sources, the usage of which need to be very efficient. The fact of continuously transmitting messages whenever there is no vehicle to receive them demands a solution. In this paper, we propose to use a well-known saving power strategy already used in Internet of Things, the Wake-up Radio systems. As vehicular communications are based on IEEE 802.11 standard, we propose to use a Wake-up Radio system based on this standard as well, being thus no additional hardware needed for the wake-up transmitter. The paper analyses the feasibility of using this solution on several vehicular applications.","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"56 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":"131312413","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}
5th Generation (5G) mobile networks is anticipated to serve large number of devices with multiple services in the single network. Due to heterogeneous service demand in a single network, 5G is presumed to be service based amalgamated with network slicing. The network will create a dedicated slice with dedicated resources and network elements based on the requested service. With so many devices and services under one umbrella of 5G, mobility becomes one of the crucial aspect, which can further have lot of impact on 5G NR (New Radio) requirements such as, radio resource optimization, seamless connectivity, minimal handovers and Quality of Experience (QoE). MAS5G (Move Smartly in 5G) explores the avenues of mobility management, wherein we consider three main services of 5G i.e. (1) enhanced Mobile Broadband (eMBB), (2) Ultra Reliable Low Latency Communications (URLLC) and (3) massive Machine Type Communications (mMTC). Unlike considering single mobility policy for all type of services (in the current networks), we propose MAS5G Central Mobility Manager (CMM), which will create dedicated schema for each service based on the network slice. With the help of User Equipment (UE) capability if network slice subscribed by subscriber is having skewed features and mobility requirement, MAS5G CMM creates schema as per the requirements of a particular network slice. It can help Access and Mobility Management Function (AMF) to provide dedicated attributes of Access and Mobility applied to devices based on predefined schemas. Through our simulation experiment, based on real time mMTC and eMBB traffic traces, we show that MAS5G is able to curtail the number of handovers, thus, saving the energy at UE significantly, which further helps to boost the QoE.
第五代(5G)移动网络预计将在单个网络中为大量设备提供多种服务。由于单个网络的业务需求是异构的，因此5G被认为是基于业务和网络切片的融合。网络将根据请求的服务创建一个包含专用资源和网络元素的专用切片。由于5G拥有如此多的设备和服务，移动性成为关键方面之一，这可能进一步对5G NR(新无线电)需求产生很大影响，例如无线电资源优化、无缝连接、最小切换和体验质量(QoE)。MAS5G (Move smart in 5G)探索了移动管理的途径，其中我们考虑了5G的三种主要服务，即(1)增强型移动宽带(eMBB)，(2)超可靠低延迟通信(URLLC)和(3)大规模机器类型通信(mMTC)。与考虑所有类型服务(在当前网络中)的单一移动策略不同，我们提出MAS5G中央移动管理器(CMM)，它将基于网络片为每个服务创建专用模式。如果用户订阅的网络片具有倾斜的特性和移动性需求，MAS5G CMM可以根据特定网络片的需求创建模式。它可以帮助AMF (Access and Mobility Management Function)根据预定义的模式提供应用于设备的Access和Mobility的专用属性。通过我们的仿真实验，基于实时mMTC和eMBB流量轨迹，我们表明MAS5G能够减少切换次数，从而显着节省UE的能量，从而进一步有助于提高QoE。
{"title":"MAS5G: Move Around Smartly in 5G","authors":"Shylendra Kumar, Rahul Banerji, Naman Gupta, Suman Kumar, Sukhdeep Singh, Avinash Bhat, Seungil Yoon, Shatarupa Dash","doi":"10.1109/FiCloud.2019.00037","DOIUrl":"https://doi.org/10.1109/FiCloud.2019.00037","url":null,"abstract":"5th Generation (5G) mobile networks is anticipated to serve large number of devices with multiple services in the single network. Due to heterogeneous service demand in a single network, 5G is presumed to be service based amalgamated with network slicing. The network will create a dedicated slice with dedicated resources and network elements based on the requested service. With so many devices and services under one umbrella of 5G, mobility becomes one of the crucial aspect, which can further have lot of impact on 5G NR (New Radio) requirements such as, radio resource optimization, seamless connectivity, minimal handovers and Quality of Experience (QoE). MAS5G (Move Smartly in 5G) explores the avenues of mobility management, wherein we consider three main services of 5G i.e. (1) enhanced Mobile Broadband (eMBB), (2) Ultra Reliable Low Latency Communications (URLLC) and (3) massive Machine Type Communications (mMTC). Unlike considering single mobility policy for all type of services (in the current networks), we propose MAS5G Central Mobility Manager (CMM), which will create dedicated schema for each service based on the network slice. With the help of User Equipment (UE) capability if network slice subscribed by subscriber is having skewed features and mobility requirement, MAS5G CMM creates schema as per the requirements of a particular network slice. It can help Access and Mobility Management Function (AMF) to provide dedicated attributes of Access and Mobility applied to devices based on predefined schemas. Through our simulation experiment, based on real time mMTC and eMBB traffic traces, we show that MAS5G is able to curtail the number of handovers, thus, saving the energy at UE significantly, which further helps to boost the QoE.","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"24 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":"123978253","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.2019.00063
Oba Zubair Mustapha, Mohammed Ali, Yim-Fun Hu, R. Abd‐Alhameed
This paper presents Packets Processing Algorithm (PPA) in an Internet Protocol/Multiprotocol Label Switching (IP/MPLS) based networks. Mainly involved label distribution using Label Distribution Protocol and packet forwarding. Fuzzy based Packet Scheduling Algorithm (FPSA) would be incorporated with PPA in order to provide intelligent performance to the MPLS core networks. Previously, many research has been proposed on the MPLS Traffic Engineering. However, there is still a need to further research on MPLS simulator using different mechanisms such as the analytical model of MPLS, expert-based packet scheduling algorithm for MPLS QoS support. Since MPLS is not able to provide intelligent routing, it is necessary to propose an intelligent expert system of FPSA combined with PPA together with an analytical model of packet forwarding in the MPLS network. This will be able to justify the control of traffic congestion and reliable services. Furthermore, the network model created using NS2, which carries application such as File Transfer Protocol (FTP) will be used. Performance metrics of throughput and end-to-end delay are considered with the results obtained from trace files. Then, trace files are interpreted and used for the calculations of the aforementioned metrics by AWK script.
{"title":"Fuzzy Based Packet Scheduling Scheme using Non-Real Time Traffic in IP/MPLS Networks","authors":"Oba Zubair Mustapha, Mohammed Ali, Yim-Fun Hu, R. Abd‐Alhameed","doi":"10.1109/FiCloud.2019.00063","DOIUrl":"https://doi.org/10.1109/FiCloud.2019.00063","url":null,"abstract":"This paper presents Packets Processing Algorithm (PPA) in an Internet Protocol/Multiprotocol Label Switching (IP/MPLS) based networks. Mainly involved label distribution using Label Distribution Protocol and packet forwarding. Fuzzy based Packet Scheduling Algorithm (FPSA) would be incorporated with PPA in order to provide intelligent performance to the MPLS core networks. Previously, many research has been proposed on the MPLS Traffic Engineering. However, there is still a need to further research on MPLS simulator using different mechanisms such as the analytical model of MPLS, expert-based packet scheduling algorithm for MPLS QoS support. Since MPLS is not able to provide intelligent routing, it is necessary to propose an intelligent expert system of FPSA combined with PPA together with an analytical model of packet forwarding in the MPLS network. This will be able to justify the control of traffic congestion and reliable services. Furthermore, the network model created using NS2, which carries application such as File Transfer Protocol (FTP) will be used. Performance metrics of throughput and end-to-end delay are considered with the results obtained from trace files. Then, trace files are interpreted and used for the calculations of the aforementioned metrics by AWK script.","PeriodicalId":268882,"journal":{"name":"2019 7th International Conference on Future Internet of Things and Cloud (FiCloud)","volume":"16 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":"124347010","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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