Deep Learning Approaches for Information Centric Network and Internet of Thingsijtsrd
Technologies are rapidly increasing with additions to them every single day. Cloud Computing and the Internet of Things IoT have become two very closely associated with future internet technologies. One provides a platform to the other for success, the benefits of which could be from computing to processing and analyzing the information to reduce latency for real time applications. However, there are a few IoT devices that do not support on device processing. An alternate solution of this is Edge Computing, where the consumers can witness a close call with the computation and services. In this work, we will be to studying and discussing the application of combining Deep Learning with IoT and Information Centric Networking. A Convolutional Neural Network CNN model, a Deep Learning model, can make the most reliable data available from the complex IoT environment. Additionally, some Deep Learning models such as Recurrent Neural Network RNN and Reinforcement Learning have also integrated with IoT, which can also collect the information from real time applications. Aashay Pawar "Deep Learning Approaches for Information - Centric Network and Internet of Things" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33346.pdf Paper Url: https://www.ijtsrd.com/engineering/computer-engineering/33346/deep-learning-approaches-for-information--centric-network-and-internet-of-things/aashay-pawar
A MIDDLEWARE FOR THE INTERNET OF THINGSIJCNCJournal
The Internet of Things (IoT) connects everyday objects including a vast array of sensors, actuators, and smart devices, referred to as “things” to the Internet, in an intelligent and pervasive fashion. This connectivity gives rise to the possibility of using the tracking capabilities of things to impinge on the location privacy of users. Most of the existing management and location privacy protection solutions do not consider the low-cost and low-power requirements of things; or, they do not account for the heterogeneity, scalability, or autonomy of communications supported in the IoT. Moreover, these traditional solutions do not consider the case where a user wishes to control the granularity of the disclosed information based on
the context of their use (e.g. based on the time or the current location of the user). To fill this gap, a middleware, referred to as the Internet of Things Management Platform (IoT-MP) is proposed in this paper.
THE ROLE OF EDGE COMPUTING IN INTERNET OF THINGSsuthi
Edge computing refers to the enabling technologies allowing computation to be performed at the edge of the network, on downstream data on behalf of cloud services and upstream data on behalf of IoT services. Here we define “edge” as any computing and network resources along the path between data sources and cloud data centers. For example, a smart phone is the edge between body things and cloud, a gateway in a smart home is the edge between home things and cloud, a micro data center and a cloudlet is the edge between a mobile device and cloud. The rationale of edge computing is that computing should happen at the proximity of data sources. From our point of view, edge computing is interchangeable with fog computing, but edge computing focus more toward the things side, while fog computing focus more on the infrastructure side. Edge computing could have as big an impact on our society as has the cloud computing.
As the internet changes our life, cloud of things will change our life again This new technology cloud of things Emerging the following technology(iot-cloud-5g-nano tech-Hci-context awareness-natural interaction) that change the concept from love things and use people to love people and use things •we all specially developing countries /Africa
must catch the cloud of everything (thing-people-process-data)train to address
the 17 SDG Goals but if any one miss it will no hope at all
•The cloud of things technology, helping elderly and handicapped people and holds the promise of fixing the millennium-old human problems of poverty, disease, violence, and poor leadership in Africa and all the world
At a time when all the world are worried about the fast spreading Zika virus, it is figured out that a wearable device could be an effective tool for preventing it, "You can compute the genome of a human being in less than seven days," "One day we will have the genome sequence of all our patients and we are then in the position to compare [that] data on a regular base with reference data."
This allows clinicians to easily identify defects in the genome and can also be used to compute the chance that someone will get a type of cancer
. A true success comes when you help others be successful leaders create leader not followers. s. It is estimated that approximately 50 billion things will be connected to each other through the communication network by 2020. A massive set of data will be created
Or by 2030 for Africa…it will be good for 10 years difference so we can fix all Africa and developing countries problems in 2030 for developed countries in 2020
The IOT will create new services based on real-time physical world data and will transform businesses, industries, and the daily life of people. Smart cities (connected communities), smart planet (green environment), smart building (building, smart homes), smart industry (industrial environment), smart energy (electric grid), smart transport (intelligent transport system), smart living (entertainment, leisure), smart health (health care system) are examples of the Internet of things.
a true success comes when you help others be successful and this true success comes in case of universal adoption of cloud of things in Africa and all the world.
“If cloud of things opportunity does not knock, build a door for it” the only impossible cloud of things journey is the one you never begin
https://onedrive.live.com/?id=94B6ABA85272A3A5%21443&cid=94B6ABA85272A3A5&group=0
http://globecom2015.ieee-globecom.org/program/industry-program/posters
http://www.ijird.com/index.php/ijird/issue/view/6167
https://www.slideshare.net
search by :assem abdl hamied moussa/assem abdel hamed mousa/assem moussa/assem mousa
http://www.ipoareview.org/wp-content/uploads/2016/05/Statement-by-Dr.Assem-Abdel-Hamied-Mousa-President-of-the-Association-of-Scientists-Developers-and-FacultiesASDF.pdf
SIMA AZ: Emerging Information Technology Innovations & Trends 11/15/17Mark Goldstein
Mark Goldstein, International Research Center presented a big overview of Emerging Information Technology Innovations & Trends to the Society for Information Management Arizona Chapter (SIM AZ) on 11/15/17 showcasing the latest and greatest emerging technologies and novel tech innovations, highlighting the market and societal transformations underway or anticipated. It covered Advances in Computer Power and Pervasiveness; Internet of Things (IoT) Overview and Ecosystem; Mobility, Augmented Reality and Virtual Reality (AR/VR); Medical Advances Through Informatics; Artificial Intelligence (AI) and Robotics; Big Data, Its Applications and Implications; and Onward into the Future…
Deep Learning Approaches for Information Centric Network and Internet of Thingsijtsrd
Technologies are rapidly increasing with additions to them every single day. Cloud Computing and the Internet of Things IoT have become two very closely associated with future internet technologies. One provides a platform to the other for success, the benefits of which could be from computing to processing and analyzing the information to reduce latency for real time applications. However, there are a few IoT devices that do not support on device processing. An alternate solution of this is Edge Computing, where the consumers can witness a close call with the computation and services. In this work, we will be to studying and discussing the application of combining Deep Learning with IoT and Information Centric Networking. A Convolutional Neural Network CNN model, a Deep Learning model, can make the most reliable data available from the complex IoT environment. Additionally, some Deep Learning models such as Recurrent Neural Network RNN and Reinforcement Learning have also integrated with IoT, which can also collect the information from real time applications. Aashay Pawar "Deep Learning Approaches for Information - Centric Network and Internet of Things" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33346.pdf Paper Url: https://www.ijtsrd.com/engineering/computer-engineering/33346/deep-learning-approaches-for-information--centric-network-and-internet-of-things/aashay-pawar
A MIDDLEWARE FOR THE INTERNET OF THINGSIJCNCJournal
The Internet of Things (IoT) connects everyday objects including a vast array of sensors, actuators, and smart devices, referred to as “things” to the Internet, in an intelligent and pervasive fashion. This connectivity gives rise to the possibility of using the tracking capabilities of things to impinge on the location privacy of users. Most of the existing management and location privacy protection solutions do not consider the low-cost and low-power requirements of things; or, they do not account for the heterogeneity, scalability, or autonomy of communications supported in the IoT. Moreover, these traditional solutions do not consider the case where a user wishes to control the granularity of the disclosed information based on
the context of their use (e.g. based on the time or the current location of the user). To fill this gap, a middleware, referred to as the Internet of Things Management Platform (IoT-MP) is proposed in this paper.
THE ROLE OF EDGE COMPUTING IN INTERNET OF THINGSsuthi
Edge computing refers to the enabling technologies allowing computation to be performed at the edge of the network, on downstream data on behalf of cloud services and upstream data on behalf of IoT services. Here we define “edge” as any computing and network resources along the path between data sources and cloud data centers. For example, a smart phone is the edge between body things and cloud, a gateway in a smart home is the edge between home things and cloud, a micro data center and a cloudlet is the edge between a mobile device and cloud. The rationale of edge computing is that computing should happen at the proximity of data sources. From our point of view, edge computing is interchangeable with fog computing, but edge computing focus more toward the things side, while fog computing focus more on the infrastructure side. Edge computing could have as big an impact on our society as has the cloud computing.
As the internet changes our life, cloud of things will change our life again This new technology cloud of things Emerging the following technology(iot-cloud-5g-nano tech-Hci-context awareness-natural interaction) that change the concept from love things and use people to love people and use things •we all specially developing countries /Africa
must catch the cloud of everything (thing-people-process-data)train to address
the 17 SDG Goals but if any one miss it will no hope at all
•The cloud of things technology, helping elderly and handicapped people and holds the promise of fixing the millennium-old human problems of poverty, disease, violence, and poor leadership in Africa and all the world
At a time when all the world are worried about the fast spreading Zika virus, it is figured out that a wearable device could be an effective tool for preventing it, "You can compute the genome of a human being in less than seven days," "One day we will have the genome sequence of all our patients and we are then in the position to compare [that] data on a regular base with reference data."
This allows clinicians to easily identify defects in the genome and can also be used to compute the chance that someone will get a type of cancer
. A true success comes when you help others be successful leaders create leader not followers. s. It is estimated that approximately 50 billion things will be connected to each other through the communication network by 2020. A massive set of data will be created
Or by 2030 for Africa…it will be good for 10 years difference so we can fix all Africa and developing countries problems in 2030 for developed countries in 2020
The IOT will create new services based on real-time physical world data and will transform businesses, industries, and the daily life of people. Smart cities (connected communities), smart planet (green environment), smart building (building, smart homes), smart industry (industrial environment), smart energy (electric grid), smart transport (intelligent transport system), smart living (entertainment, leisure), smart health (health care system) are examples of the Internet of things.
a true success comes when you help others be successful and this true success comes in case of universal adoption of cloud of things in Africa and all the world.
“If cloud of things opportunity does not knock, build a door for it” the only impossible cloud of things journey is the one you never begin
https://onedrive.live.com/?id=94B6ABA85272A3A5%21443&cid=94B6ABA85272A3A5&group=0
http://globecom2015.ieee-globecom.org/program/industry-program/posters
http://www.ijird.com/index.php/ijird/issue/view/6167
https://www.slideshare.net
search by :assem abdl hamied moussa/assem abdel hamed mousa/assem moussa/assem mousa
http://www.ipoareview.org/wp-content/uploads/2016/05/Statement-by-Dr.Assem-Abdel-Hamied-Mousa-President-of-the-Association-of-Scientists-Developers-and-FacultiesASDF.pdf
SIMA AZ: Emerging Information Technology Innovations & Trends 11/15/17Mark Goldstein
Mark Goldstein, International Research Center presented a big overview of Emerging Information Technology Innovations & Trends to the Society for Information Management Arizona Chapter (SIM AZ) on 11/15/17 showcasing the latest and greatest emerging technologies and novel tech innovations, highlighting the market and societal transformations underway or anticipated. It covered Advances in Computer Power and Pervasiveness; Internet of Things (IoT) Overview and Ecosystem; Mobility, Augmented Reality and Virtual Reality (AR/VR); Medical Advances Through Informatics; Artificial Intelligence (AI) and Robotics; Big Data, Its Applications and Implications; and Onward into the Future…
Wireless and Mobile Computing Build Secure and Maintain Wireless SolutionsYogeshIJTSRD
Today’s fast growing world needs faster communication. Technology is making rapid progress and is making many things easier. The innovative idea’s that have been emerged from the tender minds of young scientists led to the evolution of many techniques where our present topic -˜MOBILE COMPUTING’ fits in. “MOBILE COMPUTING- and COMMUNICATIONS is a major part of wireless communication technology. Mobile computing in means computing done by intermittently connected users who access network resources. It requires a wireless medium such as cellular radio, radio nets and low orbit satellites. It incorporates wireless adapters using cellular telephone technology to connect portable computers with the cabled network. Mobile voice communication is widely established throughout the world and had a very rapid increase in the number of subscribers to the various cellular networks over the last few years. An extension of this technology is the ability to send and receive data across these cellular networks. This is the principle of mobile computing. Mobile data communication has become a very important and rapidly evolving technology as it allows users to transmit data from remote locations to other remote or fixed locations. This proves to be the solution to the biggest problem of business people on the move mobility. We in this paper describes about the Mobility Services Architecture which supports applications by a middleware stub. Mobile Computing evolved during the last few years as a result of shrinking portables and growing wireless networks. It enlarges the usability of computers, but raises demanding challenges. The paper describes about the methodology, problems in wireless industry, and how J2SE is used in this technology .The paper concludes with the pros and cons of this mobile computing and its future. Akhilesh Bholanath Patel "Wireless and Mobile Computing: Build Secure and Maintain Wireless Solutions" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd43757.pdf Paper URL: https://www.ijtsrd.com/management/other/43757/wireless-and-mobile-computing-build-secure-and-maintain-wireless-solutions/akhilesh-bholanath-patel
IEEE CS Phoenix - Internet of Things Innovations & Megatrends UpdateMark Goldstein
Mark Goldstein, President of International Research Center explored the next Internet wave, the Internet of Things (IoT), expected to connect tens of billions of new sensors and devices in the coming years. Waves of change will roll through home, business, government, industrial, medical, transportation, and other complex ecosystems. Mark examined how IoT will be implemented and monetized creating new business models from pervasive sensor deployments and data gathering, accompanied by new privacy and security risks. Explore IoT’s roadblocks and operational challenges, emerging standards and protocols, gateway and wireless integration, and big data strategies and opportunities in this presentation.
Semantic Web Methodologies, Best Practices and Ontology Engineering Applied t...Ghislain ATEMEZING
This talk presents some best practices and ontology engineering applied to internet of things. The talk was presented during the 2nd IEEE World Forum on Internet of Things held in Milan, from December 14th to December 16th, 2015.
A Survey on Security and Privacy Issues in Edge Computing-Assisted Internet o...DESMOND YUEN
Internet of Things (IoT) is an innovative paradigm
envisioned to provide massive applications that are now part of
our daily lives. Millions of smart devices are deployed within
complex networks to provide vibrant functionalities including
communications, monitoring, and controlling of critical infrastructures. However, this massive growth of IoT devices and the corresponding huge data traffic generated at the edge of the network created additional burdens on the state-of-the-art
centralized cloud computing paradigm due to the bandwidth and
resources scarcity. Hence, edge computing (EC) is emerging as
an innovative strategy that brings data processing and storage
near to the end users, leading to what is called EC-assisted IoT.
Although this paradigm provides unique features and enhanced
quality of service (QoS), it also introduces huge risks in data security and privacy aspects. This paper conducts a comprehensive survey on security and privacy issues in the context of EC-assisted IoT. In particular, we first present an overview of EC-assisted IoT including definitions, applications, architecture, advantages, and challenges. Second, we define security and privacy in the context of EC-assisted IoT. Then, we extensively discuss the major classifications of attacks in EC-assisted IoT and provide possible solutions and countermeasures along with the related research efforts. After that, we further classify some security and privacy issues as discussed in the literature based on security services and based on security objectives and functions. Finally, several open challenges and future research directions for secure EC-assisted IoT paradigm are also extensively provided.
Data Modelling and Knowledge Engineering for the Internet of ThingsCory Andrew Henson
Tutorial on Data Modelling and Knowledge Engineering for the Internet of Things, presented at EKAW 2012, Galway City, Ireland, October 8-12, 2012
http://knoesis.org/iot-tutorial-ekaw2012/
In this seminar you will listen to in depth explanation of the hottest technologies in 2019 and beyond. Prof. Banafa will discuss each technology its applications and challenges with real life cases. The interaction among all the four technology will be explored with focus on future trends in each of technology. As all technologies can be summarized in one word IBAC (IoT, Blockchain, AI, Cybersecurity) they can be explained with the following words: IoT: senses, Blockchain: remembers, AI: thinks, and Cybersecurity: protects.
Fog Computing – between IoT Devices and The Cloud presentation covers following topics:
- Edge, Fog, Mist & Cloud Computing
- Fog domains and fog federation, wireless sensor networks, - multi-layer IoT architecture
- Fog computing standards and specifications
- Practical use-case scenarios & advantages of fog
- Fog analytics and intelligence on the edge
- Technologies for distributed asynchronous event processing - and analytics in real time
- Lambda architecture – Spark, Storm, Kafka, Apex, Beam, Spring - Reactor & WebFlux
- Eclipse IoT platform
Secure and Smart IoT using Blockchain and AIAhmed Banafa
The first 29 pages of my book "Secure and Smart IoT Using Blockchain and AI " Including Forward, Preface, Table of Contents , list of Figures, and Chapter 1. https://www.amazon.com/Secure-Smart-Internet-Things-IoT/dp/8770220301/
invited talk at iPHEM16, Innovation in Pre-hospital Emergency Medicine, Kent Surrey and Sussex Air Ambulance Trust, July 2016, Brighton, United Kingdom
Although all of this may come soon, we still need to understand the myriad behind-the-scenes technology that makes dreams a reality. Without them, dreams will never be realized.
Survey on Digital Video Watermarking Techniques, Attacks and ApplicationsYogeshIJTSRD
Digital watermarking is a method of identifying the rightful owner of digital data by embedding a known message in the data. These methods can be applied to a wide range of digital material, including still images, videos, and music. To safeguard the copyright of digital media, digital watermarking techniques have been created. This study seeks to provide a comprehensive overview and background on the definition, idea, and major accomplishments in the subject of watermarking. It starts with a broad review of digital watermarking, then moves on to assaults, applications, and eventually a detailed examination of existing and new watermarking systems. We classify the techniques according various categories such as host signal, perceptivity, and robustness, and watermark type, necessary data for extraction, processing domain, and applications. Preeti Sondhi | Soufia Gull "Survey on Digital Video Watermarking Techniques, Attacks and Applications" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd43776.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/43776/survey-on-digital-video-watermarking-techniques-attacks-and-applications/preeti-sondhi
The following list of predictions (Figure 1) explores the state of IoT in 2019 and covering IoT impact on many aspects business and technology including Digital Transformation, Blockchain, AI, and 5G.
Making Actionable Decisions at the Network's EdgeCognizant
With the vast analytical power unleashed by the Internet of Things (IoT) ecosystem, IT organizations must be able to apply both cloud analytics and edge analytics - cloud for strategic decision-making and edge for more instantaneous response based on local sensors and other technology.
Wireless and Mobile Computing Build Secure and Maintain Wireless SolutionsYogeshIJTSRD
Today’s fast growing world needs faster communication. Technology is making rapid progress and is making many things easier. The innovative idea’s that have been emerged from the tender minds of young scientists led to the evolution of many techniques where our present topic -˜MOBILE COMPUTING’ fits in. “MOBILE COMPUTING- and COMMUNICATIONS is a major part of wireless communication technology. Mobile computing in means computing done by intermittently connected users who access network resources. It requires a wireless medium such as cellular radio, radio nets and low orbit satellites. It incorporates wireless adapters using cellular telephone technology to connect portable computers with the cabled network. Mobile voice communication is widely established throughout the world and had a very rapid increase in the number of subscribers to the various cellular networks over the last few years. An extension of this technology is the ability to send and receive data across these cellular networks. This is the principle of mobile computing. Mobile data communication has become a very important and rapidly evolving technology as it allows users to transmit data from remote locations to other remote or fixed locations. This proves to be the solution to the biggest problem of business people on the move mobility. We in this paper describes about the Mobility Services Architecture which supports applications by a middleware stub. Mobile Computing evolved during the last few years as a result of shrinking portables and growing wireless networks. It enlarges the usability of computers, but raises demanding challenges. The paper describes about the methodology, problems in wireless industry, and how J2SE is used in this technology .The paper concludes with the pros and cons of this mobile computing and its future. Akhilesh Bholanath Patel "Wireless and Mobile Computing: Build Secure and Maintain Wireless Solutions" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd43757.pdf Paper URL: https://www.ijtsrd.com/management/other/43757/wireless-and-mobile-computing-build-secure-and-maintain-wireless-solutions/akhilesh-bholanath-patel
IEEE CS Phoenix - Internet of Things Innovations & Megatrends UpdateMark Goldstein
Mark Goldstein, President of International Research Center explored the next Internet wave, the Internet of Things (IoT), expected to connect tens of billions of new sensors and devices in the coming years. Waves of change will roll through home, business, government, industrial, medical, transportation, and other complex ecosystems. Mark examined how IoT will be implemented and monetized creating new business models from pervasive sensor deployments and data gathering, accompanied by new privacy and security risks. Explore IoT’s roadblocks and operational challenges, emerging standards and protocols, gateway and wireless integration, and big data strategies and opportunities in this presentation.
Semantic Web Methodologies, Best Practices and Ontology Engineering Applied t...Ghislain ATEMEZING
This talk presents some best practices and ontology engineering applied to internet of things. The talk was presented during the 2nd IEEE World Forum on Internet of Things held in Milan, from December 14th to December 16th, 2015.
A Survey on Security and Privacy Issues in Edge Computing-Assisted Internet o...DESMOND YUEN
Internet of Things (IoT) is an innovative paradigm
envisioned to provide massive applications that are now part of
our daily lives. Millions of smart devices are deployed within
complex networks to provide vibrant functionalities including
communications, monitoring, and controlling of critical infrastructures. However, this massive growth of IoT devices and the corresponding huge data traffic generated at the edge of the network created additional burdens on the state-of-the-art
centralized cloud computing paradigm due to the bandwidth and
resources scarcity. Hence, edge computing (EC) is emerging as
an innovative strategy that brings data processing and storage
near to the end users, leading to what is called EC-assisted IoT.
Although this paradigm provides unique features and enhanced
quality of service (QoS), it also introduces huge risks in data security and privacy aspects. This paper conducts a comprehensive survey on security and privacy issues in the context of EC-assisted IoT. In particular, we first present an overview of EC-assisted IoT including definitions, applications, architecture, advantages, and challenges. Second, we define security and privacy in the context of EC-assisted IoT. Then, we extensively discuss the major classifications of attacks in EC-assisted IoT and provide possible solutions and countermeasures along with the related research efforts. After that, we further classify some security and privacy issues as discussed in the literature based on security services and based on security objectives and functions. Finally, several open challenges and future research directions for secure EC-assisted IoT paradigm are also extensively provided.
Data Modelling and Knowledge Engineering for the Internet of ThingsCory Andrew Henson
Tutorial on Data Modelling and Knowledge Engineering for the Internet of Things, presented at EKAW 2012, Galway City, Ireland, October 8-12, 2012
http://knoesis.org/iot-tutorial-ekaw2012/
In this seminar you will listen to in depth explanation of the hottest technologies in 2019 and beyond. Prof. Banafa will discuss each technology its applications and challenges with real life cases. The interaction among all the four technology will be explored with focus on future trends in each of technology. As all technologies can be summarized in one word IBAC (IoT, Blockchain, AI, Cybersecurity) they can be explained with the following words: IoT: senses, Blockchain: remembers, AI: thinks, and Cybersecurity: protects.
Fog Computing – between IoT Devices and The Cloud presentation covers following topics:
- Edge, Fog, Mist & Cloud Computing
- Fog domains and fog federation, wireless sensor networks, - multi-layer IoT architecture
- Fog computing standards and specifications
- Practical use-case scenarios & advantages of fog
- Fog analytics and intelligence on the edge
- Technologies for distributed asynchronous event processing - and analytics in real time
- Lambda architecture – Spark, Storm, Kafka, Apex, Beam, Spring - Reactor & WebFlux
- Eclipse IoT platform
Secure and Smart IoT using Blockchain and AIAhmed Banafa
The first 29 pages of my book "Secure and Smart IoT Using Blockchain and AI " Including Forward, Preface, Table of Contents , list of Figures, and Chapter 1. https://www.amazon.com/Secure-Smart-Internet-Things-IoT/dp/8770220301/
invited talk at iPHEM16, Innovation in Pre-hospital Emergency Medicine, Kent Surrey and Sussex Air Ambulance Trust, July 2016, Brighton, United Kingdom
Although all of this may come soon, we still need to understand the myriad behind-the-scenes technology that makes dreams a reality. Without them, dreams will never be realized.
Survey on Digital Video Watermarking Techniques, Attacks and ApplicationsYogeshIJTSRD
Digital watermarking is a method of identifying the rightful owner of digital data by embedding a known message in the data. These methods can be applied to a wide range of digital material, including still images, videos, and music. To safeguard the copyright of digital media, digital watermarking techniques have been created. This study seeks to provide a comprehensive overview and background on the definition, idea, and major accomplishments in the subject of watermarking. It starts with a broad review of digital watermarking, then moves on to assaults, applications, and eventually a detailed examination of existing and new watermarking systems. We classify the techniques according various categories such as host signal, perceptivity, and robustness, and watermark type, necessary data for extraction, processing domain, and applications. Preeti Sondhi | Soufia Gull "Survey on Digital Video Watermarking Techniques, Attacks and Applications" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd43776.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/43776/survey-on-digital-video-watermarking-techniques-attacks-and-applications/preeti-sondhi
The following list of predictions (Figure 1) explores the state of IoT in 2019 and covering IoT impact on many aspects business and technology including Digital Transformation, Blockchain, AI, and 5G.
Making Actionable Decisions at the Network's EdgeCognizant
With the vast analytical power unleashed by the Internet of Things (IoT) ecosystem, IT organizations must be able to apply both cloud analytics and edge analytics - cloud for strategic decision-making and edge for more instantaneous response based on local sensors and other technology.
The proliferation of Internet of Things (IoT) and the success of rich cloud services have pushed the horizon of a new computing paradigm, edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. In this paper, we introduce the definition of edge computing, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge computing. Finally, we present several challenges and opportunities in the field of edge computing, and hope this paper will gain attention from the community and inspire more research in this direction.
Edge computing refers to the enabling technologies allowing computation to be performed at the edge of the network, on downstream data on behalf of cloud services and upstream data on behalf of IoT services. Here we define “edge” as any computing and network resources along the path between data sources and cloud data centers. For example, a smart phone is the edge between body things and cloud, a gateway in a smart home is the edge between home things and cloud, a micro data center and a cloudlet is the edge between a mobile device and cloud. The rationale of edge computing is that computing should happen at the proximity of data sources. From our point of view, edge computing is interchangeable with fog computing, but edge computing focus more toward the things side, while fog computing focus more on the infrastructure side. Edge computing could have as big an impact on our society as has the cloud computing.
Fog Computing: A Platform for Internet of Things and AnalyticsHarshitParkar6677
Internet of Things (IoT) brings more than an explosive proliferation of
endpoints. It is disruptive in several ways. In this chapter we examine those disruptions,
and propose a hierarchical distributed architecture that extends from the edge
of the network to the core nicknamed Fog Computing. In particular, we pay attention
to a new dimension that IoT adds to Big Data and Analytics: a massively distributed
number of sources at the edge.
Edge computing allows data produced by internet of things (IoT) devices to be processed closer to where it is created instead of sending it across long routes to data centers or clouds.
Doing this computing closer to the edge of the network lets organizations analyze important data in near real-time – a need of organizations across many industries, including manufacturing, health care, telecommunications and finance.Edge computing deployments are ideal in a variety of circumstances. One is when IoT devices have poor connectivity and it’s not efficient for IoT devices to be constantly connected to a central cloud.
Other use cases have to do with latency-sensitive processing of information. Edge computing reduces latency because data does not have to traverse over a network to a data center or cloud for processing. This is ideal for situations where latencies of milliseconds can be untenable, such as in financial services or manufacturing.
Consumidores Digitais: The Executive's Guide to the Internet of Things (ZD Net)Consumidores Digitais
A Internet das Coisas, ou Machine-to-Machine (M2M), é um dos temas mais atuais na tecnologia. Neste guia está o que os líderes empresariais precisam saber para potencializar seus benefícios.
Intelligence in the Internet of Things (IoT)Mychal McCabe
This infographic illustrates a generalized topology for the Internet of Things (IoT) and contextualizes the topology with examples of IoT devices ranging from cars to robots, from smart homes to latest turbofans for aircraft. The complexity of this systems-of-systems, and the volume of data that will flow through the topology will require intelligence at each tier.
The Internet of Things arrived last decade when the number of devices (that can connect) outnumbered the world population. We have now entered a new age. The evolution from #virtualization to #cloud to #IoT and #BigData a consequence of the Moore Nielsen prediction and the rise of Fog Computing. The role of #OpenSource and #OpenStandards and the importance of the new trend: Open Data as the only way to keep sanity in Big Data. This is my presentation at the IEEE International Conference on Cloud Engineering in Boston on Pi Day 2014
The Internet of Things (IoT) is one of the hottest mega-trends in technology – and for good reason , IoT deals with all the components of what we consider web 3.0 including Big Data Analytics, Cloud Computing and Mobile Computing .
ISSA-UK - Securing the Internet of Things - CIO Seminar 13 May 2014Adrian Wright
Embracing & Securing the Internet of Things
A briefing for CIOs at the CIO Dialogue 9 Oxford. May 2014
Presenter: Adrian Wright
VP of Research - Information Systems Security Association
CEO of Secoda Risk Management
Intelligent Data Processing for the Internet of Things
Roberto minerva 20181130
1. Towards a Data-Driven Society
Challenges and research perspectives for a Next Generation
Internet integrating networking, data management and computing
Roberto MINERVA
2. Outline
The «context» for Next Generation Internet: the Data Quest
New Perspectives on Networks and the current Choke Points
IoT Flood
Data Centricity and the User Data
A Change of Interaction Paradigms ?
1
2
4
5
6
Edge Computing3
2
Into a transactional World7
RECAP8
3. The Quest for Data
Source: Cisco VNI forecasts
278 EB per month of IP traffic by 2021 Global devices and connections growth 25 B by 2021
Video Traffic will dominate
3 Towards a Data-Driven Society
4. Mobile traffic by Category
4 Towards a Data-Driven Society
Source: http://elenaneira.com/market-report/report-
to-forecast-5g-market/#.W_wjt-Io82w
Voice Still a huge market, but slowly increasing
5. 4G vs. 5G vs. 6G
5 Towards a Data-Driven Society
GSMA view
6G features
• Trend 1: More Bits, More Spectrum
• Trend 2: Increased Emphasis on Spatial
Bandwidth
• Trend 3: New Technologies
• E.g., Antennas technologies, AI, Distributed
computing, …
• Trend 4: New Applications (e.g., IoT)
Source: IEEE What 6G will be
https://www.comsoc.org/ctn/what-will-6g-be
6. ■ Multimedia hunger
● Multimedia devices generate more traffic (e.g., smartphone, TV and game
consoles)
■ M2M pervasiveness
● IoT devices (around 13 B) are a bit less that previously predicted (30 B – 50
B of devices)
● They produce a smaller amount of traffic (2% to 5 %)
● Can we define it a Massive Machine type of communications?
■ Voice is still a substantial business source, but we have
definitively entered into the DATA Network AGE
■ 5G has a long way to go and so 6G
Some observations on Data Quest
6
Towards a Data-Driven Society
7. What does it mean to be in a DATA Network AGE
Two important perspectives!!!
SW viewUSER view
7 Towards a Data-Driven Society
This Photo by
Unknown Author
is licensed
under CC BY
This Photo by Unknown Author is
licensed under CC BY-ND
8. The DATA QUEST with USER EYES: three flows of
data
Access Network
Core Network Data Centers
“Network”
PERSONAL DATA
Environmental DATA
CONTENT/SERVICE DATA
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9. Network Choke points
9 Towards a Data-Driven Society
Access Network
Core Network Data Centers
“Network”
New Battlefield Terminals + Services / Applications = closed ecosystems
Definition: A CHOKE POINT IS ANY narrow passage
that restricts traffic. It literally connotes a location where
the flow could be choked off.
Source: http://geography.name/choke-point/
10. Importance of Choke points:
US Navy blocking China
10 Towards a Data-Driven Society
Source: https://medium.com/@Rutgersson/naval-chokepoints-the-chinese-conundrum-2a4ee563cab0
11. ■ Why there are not open hw terminals?
■ Why Cloud won over grid?
■ Choke points are technical or business issues?
■ Some challenges for the Next Generation Internet could be:
● Can we build a flat network without choke points?
● Who should be in charge for it?
● Should the role of Users and Society be considered?
Some considerations
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Towards a Data-Driven Society
12. But there are more (choke points) !!!
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EDGE COMPUTING
This Photo by Unknown Author is
licensed under CC BY-SA
13. Edge Computing Instantiations
Access Network
FOG
GTW
MOBILE
EDGE
WHY ?
To provide local processing (Technical)
To introduce new choke (ops sorry) control
points (Business)
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14. FOGging the data
Aazam, Mohammad & Zeadally, Sherali & A. Harras, Khaled. (2018).
Fog Computing Architecture, Evaluation, and Future Research
Directions. IEEE Communications Magazine. 56. 46-52.
10.1109/MCOM.2018.1700707.
Why
• Local Data Analysis
• Data Storage and Data Recomposition
• Security
… but
• Preprocessed data may lose their value. We
may need raw data to identify patterns
• What services will be provided by FOG?
On the other side
• Fog computing is very close to highly
distributed processing, peer to peer
• Highly disruptive if well used
14 Towards a Data-Driven Society
15. CLOUD:
Separate Administrative
Domains
(made out of homogeneous
resources)
Edge computing vs. cloud
EDGE:
Cooperating heterogeneous
nodes pertaining to different
administrative domains
Openness comes with a
Price: Complexity
15 Towards a Data-Driven Society
16. Edge vs. Cloud Computing
Capacity (Adaptive System) = (bi, si,
fi, pi)
Where:
bi = bandwidth of node i
si = storage of node i
fi = files of node i
pi = processing of node i
Capacity (Client-Server System) =
{bS, sS, fS, pS}
Where:
bS = bandwidth of the Server System
sS = storage of the Server System
fS = files stored in the Server System
pS = processing in the Server System
Optimization is
a problem
Optimization is
a function of
a business model
16 Towards a Data-Driven Society
17. ■ Some issues and challenges
● How much processing / storage in the edge?
● What services and applications at the edge?
● What advantages for the USER?
● Is there a possibility to be an alternative to other networks?
■ It is not only a technical matter of how to optimize the distribution of processing,
storage, communications and sensing: Edge is another Choke Point
● Depending on the winners, the edge will be more or less integrated with the Cloud
● Its implementations will be more or less open and programmable
■ It is hopeful to have an open APIs based approach for EDGE definition in order to
progress towards a full programmable network
Edge vs. Cloud Computing
17
Towards a Data-Driven Society
18. The IoT Flood
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Initially the worry was … will IoT generate a deluge of data?
Is it the case?
How much data for IoT?
What types of data ?
The role of edge and gateways?
This Photo by Unknown Author is licensed under CC
BY-SA
19. A simple Communication Perspective
Sensors
Gateway /
Mediation
Servers
Low Range
Technologies
Wide Area Network
Technologies
How much bandwidth for IoT ?
How many Sensors ?
How many Gateways ?
(or how many edge networks?)
How many Messages?
How large?
19 Towards a Data-Driven Society
20. ■ Data Sources
● Sensor data rate generation strongly depends on the sensor and the specific application. When the number of sensors grows the
aggregate data generation rate grows
● Data load increases with the size of the payload (some sensors can generate small amount of data with a high rate)
● Multimedia sensors (e.g., cameras) tends to generate large streams of data
● When the Dt between two messages 0 then the sensor/gateway generates a stream of data
● Streams of sensor data can exhibit similar patterns as multimedia data, but sometimes they have different requirements
● Number of «streaming IoT devices» can have a huge impact on network
■ Mediation
● When many sensors are mediated by a Gateway, then
− Messages may be processed and reduced in quantity (aggregation)
− The rate of outgoing messages from GW to Server may be high and may generate a stream
■ Sensor behaviour
● Some IoT systems exhibit impulsive behaviours
− A Container Ship with M2M devices entering in a harbor generates a spike of signalling and data
− An alarm generated by several sensors in a specific are
− Malfunctioning: a sensor that generates many messaging and stresses the nearby resources
■ Data Collection (data sinks)
● Data generated by sensor may be stored and processed locally (edge computing) or transfered as raw data over the network
● Data sets of raw data can be very useful to study particular phenomena, but transfer them to cloud systems could be «expensive»
or against the logic of Edge
The Gateway Effect
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21. Bytes per Object (Sensor) per Day
in Gbyte in Mbyte Mbytes per day
Western Europe 1,9 1900 63,33333333
USA 3,7 3700 123,3333333
Source Ericsson: https://www.ericsson.com/res/docs/2016/ericsson-mobility-report-2016.pdf
Peer to peer Video Streaming
Smartphone average data consumption
Message length in Bytes
Messages per day 1 8 64 128 256 512 1000
1 per day 1 1 8 64 128 256 512 1000
1 per H 24 24 192 1536 3072 6144 12288 24000
1 per min 1440 1440 11520 92160 184320 368640 737280 1440000
1 per sec 86400 86400 691200 5529600 11059200 22118400 44236800 86400000
1per 500
ms 172800 172800 1382400 11059200 22118400 44236800 88473600 172800000
1 per ms 86400000 86400000 691200000 5529600000 11059200000 22118400000 44236800000 86400000000
in Mbytes 86,4 691,2 5529,6 11059,2 22118,4 44236,8 86400
in Mbps 0,008 0,064 0,512 1,024 2,048 4,096 8
21 Towards a Data-Driven Society
22. The IoT Flood
■ Need to learn how IoT Systems will generate, handle, mix or even limit,
cut, reduce streams of data
■ Raw data vs. pre-processed data
● Do we need raw data ? If yes how can we get those in an economical way? Can
fog systems pre-process the data but also keep the raw data? When to transfer the
raw data for back-end processing?
■ How much IoT data will be too much?
● Can we lose alarms?
● Can we limit the data flow from sensors to the cloud with Digital Twins?
● Who is the owner of these streams of data?
22 Towards a Data-Driven Society
23. Data Centricity and the User Data
23 Towards a Data-Driven Society
Users are not only received and sent data
Or personal profiles
Networks are now strongly associated to
personal behaviour and social aspects
This Photo by Unknown Author is licensed under CC BY-SA-NC
24. Let’s go back to the three data flows
PERSONAL DATA
Environmental DATA
CONTENT DATAUser profiling
and
consuming
characteristics
Behavioural
Analysis
Environment based
profiling and consuming
characteristics
Artificial Intelligence and Machine Learning!!!
24 Towards a Data-Driven Society
25. IoT Data and … Identity of Things
Things have Identities (and Owners) People have Identities and use Things
Me
“My” Smart Thing
Identity Relation
Functional Relations
(events and commands)
Personal
Profiling
Who, Where, When, What, Why, …
Sensors
Identity Relation
Service Provider
25 Towards a Data-Driven Society
26. Aggregating Data per Identity …
“OUR”SmartThings
Raw data to be
transformed into
Info
Personal
Profiling
Functional
Profiling
Who, Where, When, What, Why, …
+
Events and commands
* = Bigger
DATA
• Who is the Owner
of all these Data ?
• Who has the right
to extract info ?
50 B Devices *
(Average Aggregated Traffic of M2M Devices)
~ 2MB/day = ~ 88.81 petabytes
/day
26 Towards a Data-Driven Society
27. The Bank of User Data
27 Towards a Data-Driven Society
User
Data Space
Bank of User Data (BUD)
Service
ProviderApplication
Provider
E-Gov
owns
manages
accesses
accesses
provides
apps
provides apps
provides
apps
• Access to data under
Contracts between Users
and Providers
• Transactional activities
• User is the only owner of
his/her data
28. User Data Centric vs. User Centric
■ Behaviour of people can be “measured”
● Statistically or by means of AI / Machine Learning
● Dunbar Number and identification of meaningful relationships
■ People can be induced to do things
● From buying stuff because of advertising to donate or cooperate
● Ohtsuki, Hisashi, et al. "A simple rule for the evolution of cooperation on graphs
and social networks." Nature 441.7092 (2006): 502.
■ Analysis and mining of personal data is a major social issue
● Regulations (e.g., GDPR)
● Behavioral science
● Psychology
■ But fewer (compared to the mainstream) research is devoted to User
Centricity from the user perspective ( )
28 Towards a Data-Driven Society
29. Interaction paradigms
END TO END PRINCIPLE FOR IP NETWORKS:
“mechanisms should not be enforced in the network if
they can be deployed at end nodes, and that the core of
the network should provide general services, not those
tailored to specific applications”
Saltzer, Clark, …
29 Towards a Data-Driven Society
This Photo by Unknown Author is licensed under CC BY-SA
30. How Smart Objects communicate
Network Intelligence (e.g., IMS) is a hierarchical model
based on the assumption that control has to be exerted by
a few specialized control nodes
Client – Server model disregards the network
aspects and can lead to a tragedy of commons
(misuse of common networking resources)
Other mechanisms (message
based like PubSub) can be more
attractive for IoT
This is a reason for different protocols …
Is it there a single communication
paradigm for NGI ?
30 Towards a Data-Driven Society
31. Softwarization of everything: physical and logical
Objects
Emerging Behavior
Programmable world (APIs) • Each Virtual Object should come with
autonomic properties, i.e., self
management
• Each individual object could be
controlled procedurally
• Each object can be extended
• Each object comes with its history
• Each Object can be replicated and
supported as many as possible
applications (slicing / personalization)
• The System can be programmed in
the large
• Additional research Topic: can the
Virtual Continuum be used to predict
behavior of large systems?
APPs
Commands Events
Sensing/Actuator Nodes
Service/Control Nodes
External Env External Env External Env
Events
System of systems
Commands
Sensing/Actuator Nodes
Service/Control Nodes
Commands
APIs
31 Towards a Data-Driven Society
A new paradigm of interaction?
32. Next Generation Internet and PubSub
Sensor 1
Ingress
Queue A
Aggregator a
Aggregator b
Aggregator c
Ingress
Queue B
Events
Events
Security
Monitoring
In aggregation
nodes at the
edge of the 5G
Nework
Egress
Queue Y
Egress
Queue Z
Policing
Control and Management
Sensor 2
Sensor 3
Sensor n
Sensor n+1
Sensor n+2
Sensor n+3
Sensor
n+m
Aggregator d
Aggregator e
Aggregator f
• Intelligent Routing of Events
and Messages thanks to SDN
• Transaction Management
• R.T. extraction of Knowledge
Data Flow
Events
Events
Control Layer
We need to bring Intelligence at the Edge of the Network
5G NetworkEDGE EDGE
32 Towards a Data-Driven Society
33. ■ “Client – Server” is not only an interaction paradigm, it is also a
Business Model (leading to massive data centers)
■ Other interactions will be needed in order to better support
services and applications (and at the end the User)
■ Also the concept of what is in the network and what is not is going
to change
■ Extensive Softwarization and Servitization may need different
paradigms (e.g., entanglement) and related protocols and means
■ Virtualization of objects leads at first to deal with spime (i.e., to
locate objects in space and time) and then to the history of the
objects and eventually to predict their future behaviour
Interactions Paradigm
33
Towards a Data-Driven Society
34. Need for transactional interactions for
empowering the Users
34 Towards a Data-Driven Society
Securely and privately interaction with others
Effective and protected and guarantee
transactions between users and merchants
Proved collection of activities and logs if Internet
actions
This Photo by Unknown Author is licensed under CC BY-NC-ND
35. Servitization is the capability of creating a link between a (physical)
product and a set of services and enriched functionalities that extend,
complement, and add value to the product itself
Each Product will be Servitized
35 Towards a Data-Driven Society
36. Each Product will be Softwarized
Product
Local
Services
Virtualization
in the “Net”
Interface
Global
Services
Extended
Functions /Interface
Product
API
API
• Each Physical Resource /
Product is representable by its
digital twin
• Each Physical Resource
becomes programmable
• Each Physical Resource can be
functionally augmented
• Physical and Logical Resources
must be entangled
• Users can interact with the
physical and logical resource
Strong entanglement
36 Towards a Data-Driven Society
37. Transactions For Important Exchange of Data
(a Receipt for every User)
transactions
• Users need to collect “receipts”, proof of their Interactions with Services, Resources and Functions
• Transactions should be stored and should contain relevant information about the data and the scope and
results of the transaction
• The transaction should be carried out within guaranteed QoS parameters
• Security and privacy will be absolute requirement
• Possible usage of decentralized DB or blockchain (e.g., to be investigated in order to reduce complexity and
time response)
transaction
37 Towards a Data-Driven Society
38. Recap
• Challenges of Next Generation Internet are Technological, but essentially
Business and Social
• Focus on Users
• User, Citizen or Customer? A great difference
• How to create a user centered network? Because what we are working on
is not User centered (It is old business centered)
• Who will own data and infrastructures?
• NGI as a container for all
• Entanglement, contextualization and prediction of objects’ behaviour and
their relationships over time (past, present and future) will lead to very
complex systems
• Multidisciplinarity is a need (Behavioural science, Economics, History, … )
• The Next generation Internet will be essentially a software network, can it be:
• Open source
• Open hardware for choking points
• Is it or will it be possible to use open technologies to create a low cost
open and free access network? Is edge computing potentially disruptive?
38 Towards a Data-Driven Society
39. Network Intelligence: The Past
Intelligent
Terminals
FullyFledgedNetworkYesterday
Transport
Control
Servers’
Network
Internet
Fn Fn Fn Fn Fn Fi Fj Fi Fi Fi
S S S S S S S S SS
S
S
S
S2S1 SiSi
Network Services
(Local)
• More Intelligent Terminals
• Fully Fledged Network (Many functions in the net)
• Development of Globally accessible Services at the edge of networks in an Internet
fashion
• Bypass of advanced or rich Network Services (e.g., QoS)
• Lack of cooperation between Service and Control/Transport mechanisms at the
Internet level
Global Services
39 Towards a Data-Driven Society
40. Resources Programming Layer
Resources Virtualization Layer
Network Intelligence: the Grand Plan (e.g., 5G)
Resources Overlays
S
SS
S S
S
S S
S
S
S
S
S
Services
Network 1 Network N Servers’ NetworksTerminals & Smart
Objects Nets
…
S
S
S
S
A Network of Networks
• Terminals as Network Elements
• Functionally Rich Networks with strong integration of ICT functions
• Programmable Resources and Networks
• Virtualized and Aggregated Resources in Overlays
• Development of Global services and functions
• Harmonization between Services and Resources Layers
40 Towards a Data-Driven Society
41. Resources Programming
Layer
Resources Virtualization
Layer
Resources Programming
Layer
Resources Virtualization
Layer
The New Network: a Software Network with
intelligence at the edge
Resources Programming
Layer
Resources Virtualization
Layer
Service Layer
S
S
S
S
S S
Network 1 Network N Servers’ NetworksTerminals & Smart
Objects Networks
…
S
A Network of Networks
made out of processing, storage, communications and sensing resources
Resources Programming
Layer
Resources Virtualization
Layer
Service Layer
S
S
S
S
S
S
S
Services
S
S
S
Services
The core Network is fast / flat / simple
41 Towards a Data-Driven Society