Internet of Things (IoT) refers to heterogeneous systems and devices (often referred to as smart objects) that connect to the internet, and is an emerging and active area of research with tremendous technological,
social, and economical value for a hyper-connected world. In this paper, we will discuss how billions of these internet connected devices and machines will change the future in which we shall live, communicate and do the business. The devices, which would be connected to the internet, could vary from simple systems on chip (SOC) without any Operating System (OS) to highly powerful processor with intelligent OS with widely varying processing capability and diverse protocol support. Many of these devices can also communicate with each other directly in a dynamic manner. A key challenge is: how to manage such a diverse set of devices of such massive scale in a secured and effective manner without breaching privacy. In this paper, we will discuss various management issues and challenges related to different communication
protocol support and models, device management, security, privacy, scalability, availability and analytic support, etc., in managing IoT. The key contribution of this paper is proposal of a reference management system architecture based on cloud technology in addressing various issues related to anagement of IoThaving billions of smart objects.
Application and Usefulness of Internet of Things in Information TechnologyDr. Amarjeet Singh
The Internet of Things (IoT) is a system of
interrelated computing devices, mechanical and digital
machines, objects, animals or people that are provided with
unique identifiers and the ability to transfer data over a
network without requiring human-to-human or human-tocomputer interaction. It is an ambiguous term, but it is fast
becoming a tangible technology that can be applied in data
centers to collect information on just about anything that
IT wants to control. IoT has evolved from the convergence
of wireless technologies, micro-electromechanical systems
(MEMS), microservices and the internet. The convergence
has helped tear down the silo walls between operational
technology (OT) and information technology (IT), allowing
unstructured machine-generated data to be analyzed for
insights that will drive improvements. The Internet of
Things (IoT) is essentially a system of machines or objects
outfitted with data-collecting technologies so that those
objects can communicate with one another. The machineto-machine (M2M) data that is generated has a wide range
of uses, but is commonly seen as a way to determine the
health and status of things -- inanimate or living.
The Internet of Things (IoT): An OverviewIJERA Editor
Information and Communications Technology (ICT) controls our daily behaviors. It becomes a main part of our
life critical infrastructure bringing interconnection of heterogeneous devices in different aspects. Personal
computing, sensing, surveillance, smart homes, entertainment, transportation and video streaming are examples,
to name a few. As a critical living entity, Internet is contentiously changing and evolving leading to emerging
new technologies, applications, protocols and algorithms. Acceleration of wireless communication trends brings
an ever growing innovation in Internet connectivity and mobile broadband. Infrastructureless communication
devices become ubiquitous, smart, powerful, connectible, smaller, cheaper, and easier to deploy and install. This
opens a new future direction in the society of ICT: the Internet of Things (IoT). Nowadays, the IoT, early
defined as Machine-to-Machine (M2M) communications, becomes a key concern of ICT world and research
communities. In this paper, we provide an overview study of the IoT paradigm, its concepts, principles and
potential benefits. Specifically, we focus on the IoT major technologies, emerging protocols, and widespread
applications. This overview can help those who start approaching the IoT world aiming to understand and
participate to its development.
Challenges and Opportunities of Internet of Things in Healthcare IJECEIAES
The Internet of Things (IoT) relies on physical objects interconnected between each other’s, creating a mesh of devices producing information and services. In this context, sensors and actuators are being continuously embedded in everyday objects (e.g., cars, home appliances, and smartphones) thus pervading our living environment. Among the plethora of application contexts, smart Healthcare is gaining momentum. Indeed IoT can revolutionize the healthcare industry by improving operational efficiency and clinical trials’ quality of monitoring, and by optimizing healthcare costs. This paper provides an overview of IoT, its applicability in healthcare, some insights about current trends and an outlook on future developments of healthcare systems.
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
The Internet of Things (IoT), also referred to as the Internet of Objects, will change everything—including ourselves. This may seem like a bold statement, but consider the impact the Internet already had on education, science, communication, business, government, and humanity. Clearly, the Internet is one of the most important and a powerful creation in all of human history. This paper discussesIOT architecture, IOT applications and limitations of IOT.
New Trends in Internet of Things, Applications, Challenges, and SolutionsTELKOMNIKA JOURNAL
Internet of things (IoT) refers to an innovation and advance field to introduce a new concept of
technologies with various potential advantages. In IoT, different types of diverse smart devices and
gadgets with smart communication interfaces are connected with each other and offers the plethora of
services in our daily life. IoT has gained attention in all fields of life like e-home, e-commerce, e-health,
smart grids, intelligent transportation systems, and e-governance. The objects in IoT increasing
preponderance of entities and transform objects into new and real-world objects. In this review paper, we
discuss the new trend in IoT, its applications and recent challenges and their solutions. In addition, the
paper also elaborates the existing systems, IoT architecture and technical aspects with future trends in the
field. This review will be helpful to new researchers to find the existing technologies and challenges in
order to continue their research in the field.
Application and Usefulness of Internet of Things in Information TechnologyDr. Amarjeet Singh
The Internet of Things (IoT) is a system of
interrelated computing devices, mechanical and digital
machines, objects, animals or people that are provided with
unique identifiers and the ability to transfer data over a
network without requiring human-to-human or human-tocomputer interaction. It is an ambiguous term, but it is fast
becoming a tangible technology that can be applied in data
centers to collect information on just about anything that
IT wants to control. IoT has evolved from the convergence
of wireless technologies, micro-electromechanical systems
(MEMS), microservices and the internet. The convergence
has helped tear down the silo walls between operational
technology (OT) and information technology (IT), allowing
unstructured machine-generated data to be analyzed for
insights that will drive improvements. The Internet of
Things (IoT) is essentially a system of machines or objects
outfitted with data-collecting technologies so that those
objects can communicate with one another. The machineto-machine (M2M) data that is generated has a wide range
of uses, but is commonly seen as a way to determine the
health and status of things -- inanimate or living.
The Internet of Things (IoT): An OverviewIJERA Editor
Information and Communications Technology (ICT) controls our daily behaviors. It becomes a main part of our
life critical infrastructure bringing interconnection of heterogeneous devices in different aspects. Personal
computing, sensing, surveillance, smart homes, entertainment, transportation and video streaming are examples,
to name a few. As a critical living entity, Internet is contentiously changing and evolving leading to emerging
new technologies, applications, protocols and algorithms. Acceleration of wireless communication trends brings
an ever growing innovation in Internet connectivity and mobile broadband. Infrastructureless communication
devices become ubiquitous, smart, powerful, connectible, smaller, cheaper, and easier to deploy and install. This
opens a new future direction in the society of ICT: the Internet of Things (IoT). Nowadays, the IoT, early
defined as Machine-to-Machine (M2M) communications, becomes a key concern of ICT world and research
communities. In this paper, we provide an overview study of the IoT paradigm, its concepts, principles and
potential benefits. Specifically, we focus on the IoT major technologies, emerging protocols, and widespread
applications. This overview can help those who start approaching the IoT world aiming to understand and
participate to its development.
Challenges and Opportunities of Internet of Things in Healthcare IJECEIAES
The Internet of Things (IoT) relies on physical objects interconnected between each other’s, creating a mesh of devices producing information and services. In this context, sensors and actuators are being continuously embedded in everyday objects (e.g., cars, home appliances, and smartphones) thus pervading our living environment. Among the plethora of application contexts, smart Healthcare is gaining momentum. Indeed IoT can revolutionize the healthcare industry by improving operational efficiency and clinical trials’ quality of monitoring, and by optimizing healthcare costs. This paper provides an overview of IoT, its applicability in healthcare, some insights about current trends and an outlook on future developments of healthcare systems.
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
The Internet of Things (IoT), also referred to as the Internet of Objects, will change everything—including ourselves. This may seem like a bold statement, but consider the impact the Internet already had on education, science, communication, business, government, and humanity. Clearly, the Internet is one of the most important and a powerful creation in all of human history. This paper discussesIOT architecture, IOT applications and limitations of IOT.
New Trends in Internet of Things, Applications, Challenges, and SolutionsTELKOMNIKA JOURNAL
Internet of things (IoT) refers to an innovation and advance field to introduce a new concept of
technologies with various potential advantages. In IoT, different types of diverse smart devices and
gadgets with smart communication interfaces are connected with each other and offers the plethora of
services in our daily life. IoT has gained attention in all fields of life like e-home, e-commerce, e-health,
smart grids, intelligent transportation systems, and e-governance. The objects in IoT increasing
preponderance of entities and transform objects into new and real-world objects. In this review paper, we
discuss the new trend in IoT, its applications and recent challenges and their solutions. In addition, the
paper also elaborates the existing systems, IoT architecture and technical aspects with future trends in the
field. This review will be helpful to new researchers to find the existing technologies and challenges in
order to continue their research in the field.
In this presentation, Chittrieta introduces the topic of IoT, current applications of IoT and associated trends. Chittrieta's interest lies in application of IoT on the shop floor in the manufacturing vertical.
Societal Change and Transformation by Internet of Things (IoT)CSCJournals
IoT has received much attention from scientists, industry and government all over the world for its potential in changing modern day living. IoT is envisioned as billions of sensors connected to the internet through wireless and other communication technologies. The sensors would generate large amount of data which needs to be analyzed, interpreted and utilized. Sensor will be context aware capturing device that enable modeling, interpreting and storing of sensor data which is linked to appropriate context variable dynamically. Building or home automation, social smart communication for enhancement of quality of life, that could be considered as one of the application of IoT where the sensors, actuators and controllers can be connected to internet and controlled. This paper introduces the concept of application for internet of things and with the discussion of social and governance issues that arise as the future vision of internet of things.
This paper addresses the internet of things (IoT) as the main enabling factor of promising paradigm for integration and comprehensive of several technologies for communication solution, Identification and integrating for tracking of technologies as wireless sector and actuators. This offers the capability to measure for understanding environment indicators
Internet of Things (IoT) integrates billions of the heterogeneous IoT things with the Internet in which the embedded systems such as sensors and actuators linked together to improve quality of life, and becomes the future of technologies in any field of human daily life. These IoT devices cooperate with each other and generate useful information to provide better services and applications to the governments and the society. Also, there is a need to store these data on Cloud for monitoring. This paper, surveys IoT applications, new challenges and issues arise in different fields and provides IoT architecture, focuses on explanation of IoT protocols and their operations and functionalities, presents different microcontroller types used by researchers. With the huge amount of data generated from IoT devices, the integrating Cloud and IoT may helpful, Therefore, a survey on open issues faced when these two concepts integrating together is discussed. The objective of this paper is to provide a survey for everything related to IoT and direct it to all beginners in this filed or academic researchers.
In recent years, the Internet of Things (IOT) has attracted many attentions. It allows a number of objects that have been embedded with wired or wireless communication interfaces to automatically communicate and interact with each other. The IOT is a system, combination of embedded controllers, sensors, software’s and network. After internet and mobile communication, IOT is regarded as the third wave of information because of its huge market prospects. The development of IOT can support a variety of applications including Intelligent Art, Intelligent Logistics, Intelligent Medicine & Healthcare, Intelligent Transportation, Intelligent Power, Smart Life etc. IOT Gateway plays an important role in IOT applications since it bridges between wireless sensor networks with traditional communication networks or internet. This paper includes an IOT Gateway system based on Zigbee and Wi-Fi protocols according to the presented data transmission between wireless sensor networks and mobile communication networks, typical IOT application scenarios and requirements from telecom operators, protocol conversion of different sensor network protocols, and control functionalities for sensor networks, and an implementation of prototyping system and system validation is given.
WIRELESS SENSORS INTEGRATION INTO INTERNET OF THINGS AND THE SECURITY PRIMITIVESIJCNCJournal
The common vision of smart systems today, is by and large associated with one single concept, the internet of things (IoT), where the whole physical infrastructure is linked with intelligent monitoring and communication technologies through the use of wireless sensors. In such an intelligent vibrant system, sensors are connected to send useful information and control instructions via distributed sensor networks. Wireless sensors have an easy deployment and better flexibility of devices contrary to wired setup. With the rapid technological development of sensors, wireless sensor networks (WSNs) will become the key technology for IoT and an invaluable resource for realizing the vision of Internet of things (IoT) paradigm.
It is also important to consider whether the sensors of a WSN should be completely integrated into IoT or not. New security challenges arise when heterogeneous sensors are integrated into the IoT. Security needs to be considered at a global perspective, not just at a local scale. This paper gives an overview of sensor integration into IoT, some major security challenges and also a number of security primitives that can be taken to protect their data over the internet.
In today’s emerging world of Internet, each and every thing is supposed to be in connected mode with the help of billions of smart devices. By connecting all the devises used in our day to day life, make our life trouble less and easy. We are incorporated in a world where we are used to have smart phones, smart cars, smart gadgets, smart homes and smart cities. Different institutes and researchers are working for creating a smart world for us but real question which we need to emphasis on is how to make dumb devises talk with uncommon hardware and communication technology. For the same what kind of mechanism to use with various protocols and less human interaction. The purpose is to provide the key area for application of IoT and a platform on which various devices having different mechanism and protocols can communicate with an integrated architecture.
Cyber physical systems: A smart city perspective IJECEIAES
Cyber-physical system (CPS) is a terminology used to describe multiple systems of existing infrastructure and manufacturing system that combines computing technologies (cyber space) into the physical space to integrate human interaction. This paper does a literature review of the work related to CPS in terms of its importance in today’s world. Further, this paper also looks at the importance of CPS and its relationship with internet of things (IoT). CPS is a very broad area and is used in variety of fields and some of these major fields are evaluated. Additionally, the implementation of CPS and IoT is major enabler for smart cities and various examples of such implementation in the context of Dubai and UAE are researched. Finally, security issues related to CPS in general are also reviewed.
As objects become embedded with sensors and gain the ability to communicate,
the new information networks promise to create new business models, improve
business processes, and reduce costs and risks. One such Model is the internet of
things. Sensors and actuators are embedded in physical objects from roadways to
pacemakers are linked through wired and wireless networks, often using the same Internet
Protocol (IP) that connects the Internet. Internet of Things has great potential to support
society, to improve energy efficiency and to optimize various kinds of mobility and
transport at the same time. However, the Internet of Things raises significant
challenges that could stand in the way of reaping its potential benefits. Pitfalls
concerning cyber security, theft and hacking of personal and financial data are the
ones that are making people agitated.
Electronic devices used at home, workplaces, in a neighbourhood or in a large
urban landscape are connected and provide data which is accumulated and analyzed
for the benefit of its users. The ability of a simple cell phone connecting to other
devices, sensors in public, to regulate traffic and other civic institutions, shows how
IoT has merged with data and analytics of data plays a key role and will continue to
do so in the future.
Internet of Things - Paradigm Shift of Future Internet Application for Specia...ijsrd.com
In the world more than 15% people are living with disability that also include children below age of 10 years. Due to lack of independent support services specially abled (handicap) people overly rely on other people for their basic needs, that excludes them from being financially and socially active. The Internet of Things (IoT) can give support system and a better quality of life as well as participation in routine and day to day life. For this purpose, the future solutions for current problems has been introduced in this paper. Daunting challenges have been considered as future research and glimpse of the IoT for specially abled person is given in the paper.
A Survey Report on : Security & Challenges in Internet of Thingsijsrd.com
In the era of computing technology, Internet of Things (IoT) devices are now popular in each and every domains like e-governance, e-Health, e-Home, e-Commerce, and e-Trafficking etc. Iot is spreading from small to large applications in all fields like Smart Cities, Smart Grids, Smart Transportation. As on one side IoT provide facilities and services for the society. On the other hand, IoT security is also a crucial issues.IoT security is an area which totally concerned for giving security to connected devices and networks in the IoT .As, IoT is vast area with usability, performance, security, and reliability as a major challenges in it. The growth of the IoT is exponentially increases as driven by market pressures, which proportionally increases the security threats involved in IoT The relationship between the security and billions of devices connecting to the Internet cannot be described with existing mathematical methods. In this paper, we explore the opportunities possible in the IoT with security threats and challenges associated with it.
Five Converging Forces that Are Driving Technological EvolutionCognizant
The digital era is catalyzing business, unleashing technological change that may appear chaotic on the surface but is resulting in massively powerful systems of intelligence that enable humans and machines to collaborate securely.
The vast network of devices connected to the Internet, including smart phones and tablets and almost anything with a sensor on it – cars, machines in production plants, jet engines, oil drills, wearable devices, and more. These “things” collect and exchange data.
Devices and objects with built in sensors are connected to an Internet of Things platform, which integrates data from the different devices and applies analytics to share the most valuable information with applications built to address specific needs.
In this presentation, Chittrieta introduces the topic of IoT, current applications of IoT and associated trends. Chittrieta's interest lies in application of IoT on the shop floor in the manufacturing vertical.
Societal Change and Transformation by Internet of Things (IoT)CSCJournals
IoT has received much attention from scientists, industry and government all over the world for its potential in changing modern day living. IoT is envisioned as billions of sensors connected to the internet through wireless and other communication technologies. The sensors would generate large amount of data which needs to be analyzed, interpreted and utilized. Sensor will be context aware capturing device that enable modeling, interpreting and storing of sensor data which is linked to appropriate context variable dynamically. Building or home automation, social smart communication for enhancement of quality of life, that could be considered as one of the application of IoT where the sensors, actuators and controllers can be connected to internet and controlled. This paper introduces the concept of application for internet of things and with the discussion of social and governance issues that arise as the future vision of internet of things.
This paper addresses the internet of things (IoT) as the main enabling factor of promising paradigm for integration and comprehensive of several technologies for communication solution, Identification and integrating for tracking of technologies as wireless sector and actuators. This offers the capability to measure for understanding environment indicators
Internet of Things (IoT) integrates billions of the heterogeneous IoT things with the Internet in which the embedded systems such as sensors and actuators linked together to improve quality of life, and becomes the future of technologies in any field of human daily life. These IoT devices cooperate with each other and generate useful information to provide better services and applications to the governments and the society. Also, there is a need to store these data on Cloud for monitoring. This paper, surveys IoT applications, new challenges and issues arise in different fields and provides IoT architecture, focuses on explanation of IoT protocols and their operations and functionalities, presents different microcontroller types used by researchers. With the huge amount of data generated from IoT devices, the integrating Cloud and IoT may helpful, Therefore, a survey on open issues faced when these two concepts integrating together is discussed. The objective of this paper is to provide a survey for everything related to IoT and direct it to all beginners in this filed or academic researchers.
In recent years, the Internet of Things (IOT) has attracted many attentions. It allows a number of objects that have been embedded with wired or wireless communication interfaces to automatically communicate and interact with each other. The IOT is a system, combination of embedded controllers, sensors, software’s and network. After internet and mobile communication, IOT is regarded as the third wave of information because of its huge market prospects. The development of IOT can support a variety of applications including Intelligent Art, Intelligent Logistics, Intelligent Medicine & Healthcare, Intelligent Transportation, Intelligent Power, Smart Life etc. IOT Gateway plays an important role in IOT applications since it bridges between wireless sensor networks with traditional communication networks or internet. This paper includes an IOT Gateway system based on Zigbee and Wi-Fi protocols according to the presented data transmission between wireless sensor networks and mobile communication networks, typical IOT application scenarios and requirements from telecom operators, protocol conversion of different sensor network protocols, and control functionalities for sensor networks, and an implementation of prototyping system and system validation is given.
WIRELESS SENSORS INTEGRATION INTO INTERNET OF THINGS AND THE SECURITY PRIMITIVESIJCNCJournal
The common vision of smart systems today, is by and large associated with one single concept, the internet of things (IoT), where the whole physical infrastructure is linked with intelligent monitoring and communication technologies through the use of wireless sensors. In such an intelligent vibrant system, sensors are connected to send useful information and control instructions via distributed sensor networks. Wireless sensors have an easy deployment and better flexibility of devices contrary to wired setup. With the rapid technological development of sensors, wireless sensor networks (WSNs) will become the key technology for IoT and an invaluable resource for realizing the vision of Internet of things (IoT) paradigm.
It is also important to consider whether the sensors of a WSN should be completely integrated into IoT or not. New security challenges arise when heterogeneous sensors are integrated into the IoT. Security needs to be considered at a global perspective, not just at a local scale. This paper gives an overview of sensor integration into IoT, some major security challenges and also a number of security primitives that can be taken to protect their data over the internet.
In today’s emerging world of Internet, each and every thing is supposed to be in connected mode with the help of billions of smart devices. By connecting all the devises used in our day to day life, make our life trouble less and easy. We are incorporated in a world where we are used to have smart phones, smart cars, smart gadgets, smart homes and smart cities. Different institutes and researchers are working for creating a smart world for us but real question which we need to emphasis on is how to make dumb devises talk with uncommon hardware and communication technology. For the same what kind of mechanism to use with various protocols and less human interaction. The purpose is to provide the key area for application of IoT and a platform on which various devices having different mechanism and protocols can communicate with an integrated architecture.
Cyber physical systems: A smart city perspective IJECEIAES
Cyber-physical system (CPS) is a terminology used to describe multiple systems of existing infrastructure and manufacturing system that combines computing technologies (cyber space) into the physical space to integrate human interaction. This paper does a literature review of the work related to CPS in terms of its importance in today’s world. Further, this paper also looks at the importance of CPS and its relationship with internet of things (IoT). CPS is a very broad area and is used in variety of fields and some of these major fields are evaluated. Additionally, the implementation of CPS and IoT is major enabler for smart cities and various examples of such implementation in the context of Dubai and UAE are researched. Finally, security issues related to CPS in general are also reviewed.
As objects become embedded with sensors and gain the ability to communicate,
the new information networks promise to create new business models, improve
business processes, and reduce costs and risks. One such Model is the internet of
things. Sensors and actuators are embedded in physical objects from roadways to
pacemakers are linked through wired and wireless networks, often using the same Internet
Protocol (IP) that connects the Internet. Internet of Things has great potential to support
society, to improve energy efficiency and to optimize various kinds of mobility and
transport at the same time. However, the Internet of Things raises significant
challenges that could stand in the way of reaping its potential benefits. Pitfalls
concerning cyber security, theft and hacking of personal and financial data are the
ones that are making people agitated.
Electronic devices used at home, workplaces, in a neighbourhood or in a large
urban landscape are connected and provide data which is accumulated and analyzed
for the benefit of its users. The ability of a simple cell phone connecting to other
devices, sensors in public, to regulate traffic and other civic institutions, shows how
IoT has merged with data and analytics of data plays a key role and will continue to
do so in the future.
Internet of Things - Paradigm Shift of Future Internet Application for Specia...ijsrd.com
In the world more than 15% people are living with disability that also include children below age of 10 years. Due to lack of independent support services specially abled (handicap) people overly rely on other people for their basic needs, that excludes them from being financially and socially active. The Internet of Things (IoT) can give support system and a better quality of life as well as participation in routine and day to day life. For this purpose, the future solutions for current problems has been introduced in this paper. Daunting challenges have been considered as future research and glimpse of the IoT for specially abled person is given in the paper.
A Survey Report on : Security & Challenges in Internet of Thingsijsrd.com
In the era of computing technology, Internet of Things (IoT) devices are now popular in each and every domains like e-governance, e-Health, e-Home, e-Commerce, and e-Trafficking etc. Iot is spreading from small to large applications in all fields like Smart Cities, Smart Grids, Smart Transportation. As on one side IoT provide facilities and services for the society. On the other hand, IoT security is also a crucial issues.IoT security is an area which totally concerned for giving security to connected devices and networks in the IoT .As, IoT is vast area with usability, performance, security, and reliability as a major challenges in it. The growth of the IoT is exponentially increases as driven by market pressures, which proportionally increases the security threats involved in IoT The relationship between the security and billions of devices connecting to the Internet cannot be described with existing mathematical methods. In this paper, we explore the opportunities possible in the IoT with security threats and challenges associated with it.
Five Converging Forces that Are Driving Technological EvolutionCognizant
The digital era is catalyzing business, unleashing technological change that may appear chaotic on the surface but is resulting in massively powerful systems of intelligence that enable humans and machines to collaborate securely.
The vast network of devices connected to the Internet, including smart phones and tablets and almost anything with a sensor on it – cars, machines in production plants, jet engines, oil drills, wearable devices, and more. These “things” collect and exchange data.
Devices and objects with built in sensors are connected to an Internet of Things platform, which integrates data from the different devices and applies analytics to share the most valuable information with applications built to address specific needs.
Tiempos de respuesta asistencial en Andalucía a 30 de junio de 2011saludand
Presentación sobre tiempos de respuesta asistencial para procedimientos quirúrgicos, primera consulta de especialista y pruebas diagnósticas. A 30 de junio de 2011
Школьный опыт бизнес-инициатив и развитие экспертного сообщества старшекласс...Школьная лига РОСНАНО
Леонид Илюшин, доктор пед. наук, проф. СПбГУ и НИУ ВШЭ
В рамках VII ежегодной межрегиональной научно-практической конференции по вопросам естественнонаучного, технологического и технопредпринимательского образования.
In this presentation, Ankit introduces IoT and associated trends. Ashish is interested in cloud computing as that enables the functioning of IoT devices. Ashish is also interested in analytics of consumer devices where he wants to design devices that adjust based on usage patterns.
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
WIRELESS SENSORS INTEGRATION INTO INTERNET OF THINGS AND THE SECURITY PRIMITIVEScsandit
The common vision of smart systems today, is by and large associated with one single concept,
the internet of things (IoT), where the whole physical infrastructure is linked with intelligent
monitoring and communication technologies through the use of wireless sensors. In such an
intelligent vibrant system, sensors are connected to send useful information and control
instructions via distributed sensor networks. Wireless sensors have an easy deployment and
better flexibility of devices contrary to wired setup. With the rapid technological development of
sensors, wireless sensor networks (WSNs) will become the key technology for IoT and an
invaluable resource for realizing the vision of Internet of things (IoT) paradigm. It is also
important to consider whether the sensors of a WSN should be completely integrated into IoT or
not. New security challenges arise when heterogeneous sensors are integrated into the IoT. Security needs to be considered at a global perspective, not just at a local scale. This paper gives an overview of sensor integration into IoT, some major security challenges and also a
number of security primitives that can be taken to protect their data over the internet.
In recent years, the Internet of Things (IOT) has attracted many attentions. It allows a number of objects that have been embedded with wired or wireless communication interfaces to automatically communicate and interact with each other. The IOT is a system, combination of embedded controllers, sensors, software’s and network. After internet and mobile communication, IOT is regarded as the third wave of information because of its huge market prospects. The development of IOT can support a variety of applications including Intelligent Art, Intelligent Logistics, Intelligent Medicine & Healthcare, Intelligent Transportation, Intelligent Power, Smart Life etc. IOT Gateway plays an important role in IOT applications since it bridges between wireless sensor networks with traditional communication networks or internet. This paper includes an IOT Gateway system based on Zigbee and Wi-Fi protocols according to the presented data transmission between wireless sensor networks and mobile communication networks, typical IOT application scenarios and requirements from telecom operators, protocol conversion of different sensor network protocols, and control functionalities for sensor networks, and an implementation of prototyping system and system validation is given.
Analysis of Energy Management Scheme in Smart City: A Reviewijtsrd
A brilliant city misuses feasible data and correspondence innovations to improve the quality and the presentation of urban administrations for natives and government, while decreasing assets utilization. Wise vitality control in structures is a significant viewpoint in this. The Internet of Things can give an answer. It means to associate various heterogeneous gadgets through the web, for which it needs an adaptable layered design where the things, the general population and the cloud administrations are consolidated to encourage an application task. Such adaptable IoT various leveled engineering model will be presented in this paper with a review of each key segment for astute vitality control in structures for keen urban communities. Manisha Kumari Singh | Prof. Avinash Sharma "Analysis of Energy Management Scheme in Smart City: A Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29446.pdfPaper URL: https://www.ijtsrd.com/other-scientific-research-area/other/29446/analysis-of-energy-management-scheme-in-smart-city-a-review/manisha-kumari-singh
The idea is to create a social network of sensors in which various sensors integrated to intel Galileo will send the data to the user.
Nowadays using various social networking sites like Facebook, twitter, google+ has become too main stream.
Now the idea is to integrate our home status to these social networking sites that is, creating a “Galileo link”.
Home status will be comprised of various readings taken by the sensors like IR sensor, LDR, temperature sensor.
Sensors send data to intel Galileo then Galileo acts as a client and sends that data to the social networking site.
For example in Facebook an account is created and that account is registered on Facebook developer. As soon as the account is registered on Facebook developer it creates an access token.
Access token is then included in python script running in the Galileo device.
Hence our data can be seen in our news feed and we just have to add the registered account as our friend
Vehicle Ad Hoc Networks (VANETs) have become a viable technology to improve traffic flow and safety on the roads. Due to its effectiveness and scalability, the Wingsuit Search-based Optimised Link State Routing Protocol (WS-OLSR) is frequently used for data distribution in VANETs. However, the selection of MultiPoint Relays (MPRs) plays a pivotal role in WS-OLSR's performance. This paper presents an improved MPR selection algorithm tailored to WS-OLSR, designed to enhance the overall routing efficiency and reduce overhead. The analysis found that the current OLSR protocol has problems such as redundancy of HELLO and TC message packets or failure to update routing information in time, so a WS-OLSR routing protocol based on improved-MPR selection algorithm was proposed. Firstly, factors such as node mobility and link changes are comprehensively considered to reflect network topology changes, and the broadcast cycle of node HELLO messages is controlled through topology changes. Secondly, a new MPR selection algorithm is proposed, considering link stability issues and nodes. Finally, evaluate its effectiveness in terms of packet delivery ratio, end-to-end delay, and control message overhead. Simulation results demonstrate the superior performance of our improved MR selection algorithm when compared to traditional approaches.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
May_2024 Top 10 Read Articles in Computer Networks & Communications.pdfIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
A Topology Control Algorithm Taking into Account Energy and Quality of Transm...IJCNCJournal
The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.
Multi-Server user Authentication Scheme for Privacy Preservation with Fuzzy C...IJCNCJournal
The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.
Advanced Privacy Scheme to Improve Road Safety in Smart Transportation SystemsIJCNCJournal
In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.
April 2024 - Top 10 Read Articles in Computer Networks & CommunicationsIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
DEF: Deep Ensemble Neural Network Classifier for Android Malware DetectionIJCNCJournal
Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.
High Performance NMF Based Intrusion Detection System for Big Data IOT TrafficIJCNCJournal
With the emergence of smart devices and the Internet of Things (IoT), millions of users connected to the network produce massive network traffic datasets. These vast datasets of network traffic, Big Data are challenging to store, deal with and analyse using a single computer. In this paper we developed parallel implementation using a High Performance Computer (HPC) for the Non-Negative Matrix Factorization technique as an engine for an Intrusion Detection System (HPC-NMF-IDS). The large IoT traffic datasets of order of millions samples are distributed evenly on all the computing cores for both storage and speedup purpose. The distribution of computing tasks involved in the Matrix Factorization takes into account the reduction of the communication cost between the computing cores. The experiments we conducted on the proposed HPC-IDS-NMF give better results than the traditional ML-based intrusion detection systems. We could train the HPC model with datasets of one million samples in only 31 seconds instead of the 40 minutes using one processor), that is a speed up of 87 times. Moreover, we have got an excellent detection accuracy rate of 98% for KDD dataset.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
A Topology Control Algorithm Taking into Account Energy and Quality of Transm...IJCNCJournal
The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.
Multi-Server user Authentication Scheme for Privacy Preservation with Fuzzy C...IJCNCJournal
The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.
Advanced Privacy Scheme to Improve Road Safety in Smart Transportation SystemsIJCNCJournal
In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.
DEF: Deep Ensemble Neural Network Classifier for Android Malware DetectionIJCNCJournal
Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.
High Performance NMF based Intrusion Detection System for Big Data IoT TrafficIJCNCJournal
With the emergence of smart devices and the Internet of Things (IoT), millions of users connected to the network produce massive network traffic datasets. These vast datasets of network traffic, Big Data are challenging to store, deal with and analyse using a single computer. In this paper we developed parallel implementation using a High Performance Computer (HPC) for the Non-Negative Matrix Factorization technique as an engine for an Intrusion Detection System (HPC-NMF-IDS). The large IoT traffic datasets of order of millions samples are distributed evenly on all the computing cores for both storage and speedup purpose. The distribution of computing tasks involved in the Matrix Factorization takes into account the reduction of the communication cost between the computing cores. The experiments we conducted on the proposed HPC-IDS-NMF give better results than the traditional ML-based intrusion detection systems. We could train the HPC model with datasets of one million samples in only 31 seconds instead of the 40 minutes using one processor), that is a speed up of 87 times. Moreover, we have got an excellent detection accuracy rate of 98% for KDD dataset.
IoT Guardian: A Novel Feature Discovery and Cooperative Game Theory Empowered...IJCNCJournal
Cyber intrusion attacks increasingly target the Internet of Things (IoT) ecosystem, exploiting vulnerable devices and networks. Malicious activities must be identified early to minimize damage and mitigate threats. Using actual benign and attack traffic from the CICIoT2023 dataset, this WORK aims to evaluate and benchmark machine-learning techniques for IoT intrusion detection. There are four main phases to the system. First, the CICIoT2023 dataset is refined to remove irrelevant features and clean up missing and duplicate data. The second phase employs statistical models and artificial intelligence to discover novel features. The most significant features are then selected in the third phase based on cooperative game theory. Using the original CICIoT2023 dataset and a dataset containing only novel features, we train and evaluate a variety of machine learning classifiers. On the original dataset, Random Forest achieved the highest accuracy of 99%. Still, with novel features, Random Forest's performance dropped only slightly (96%) while other models achieved significantly lower accuracy. As a whole, the work contributes substantial contributions to tailored feature engineering, feature selection, and rigorous benchmarking of IoT intrusion detection techniques. IoT networks and devices face continuously evolving threats, making it necessary to develop robust intrusion detection systems.
Enhancing Traffic Routing Inside a Network through IoT Technology & Network C...IJCNCJournal
IoT networking uses real items as stationary or mobile nodes. Mobile nodes complicate networking. Internet of Things (IoT) networks have a lot of control overhead messages because devices are mobile. These signals are generated by the constant flow of control data as such device identity, geographical positioning, node mobility, device configuration, and others. Network clustering is a popular overhead communication management method. Many cluster-based routing methods have been developed to address system restrictions. Node clustering based on the Internet of Things (IoT) protocol, may be used to cluster all network nodes according to predefined criteria. Each cluster will have a Smart Designated Node. SDN cluster management is efficient. Many intelligent nodes remain in the network. The network design spreads these signals. This paper presents an intelligent and responsive routing approach for clustered nodes in IoT networks. An existing method builds a new sub-area clustered topology. The Nodes Clustering Based on the Internet of Things (NCIoT) method improves message transmission between any two nodes. This will facilitate the secure and reliable interchange of healthcare data between professionals and patients. NCIoT is a system that organizes nodes in the Internet of Things (IoT) by grouping them together based on their proximity. It also picks SDN routes for these nodes. This approach involves selecting one option from a range of choices and preparing for likely outcomes problem addressing limitations on activities is a primary focus during the review process. Predictive inquiry employs the process of analyzing data to forecast and anticipate future events. This document provides an explanation of compact units. The Predictive Inquiry Small Packets (PISP) improved its backup system and partnered with SDN to establish a routing information table for each intelligent node, resulting in higher routing performance. Both principal and secondary roads are available for use. The simulation findings indicate that NCIoT algorithms outperform CBR protocols. Enhancements lead to a substantial 78% boost in network performance. In addition, the end-to-end latency dropped by 12.5%. The PISP methodology produces 5.9% more inquiry packets compared to alternative approaches. The algorithms are constructed and evaluated against academic ones.
IoT Guardian: A Novel Feature Discovery and Cooperative Game Theory Empowered...IJCNCJournal
Cyber intrusion attacks increasingly target the Internet of Things (IoT) ecosystem, exploiting vulnerable devices and networks. Malicious activities must be identified early to minimize damage and mitigate threats. Using actual benign and attack traffic from the CICIoT2023 dataset, this WORK aims to evaluate and benchmark machine-learning techniques for IoT intrusion detection. There are four main phases to the system. First, the CICIoT2023 dataset is refined to remove irrelevant features and clean up missing and duplicate data. The second phase employs statistical models and artificial intelligence to discover novel features. The most significant features are then selected in the third phase based on cooperative game theory. Using the original CICIoT2023 dataset and a dataset containing only novel features, we train and evaluate a variety of machine learning classifiers. On the original dataset, Random Forest achieved the highest accuracy of 99%. Still, with novel features, Random Forest's performance dropped only slightly (96%) while other models achieved significantly lower accuracy. As a whole, the work contributes substantial contributions to tailored feature engineering, feature selection, and rigorous benchmarking of IoT intrusion detection techniques. IoT networks and devices face continuously evolving threats, making it necessary to develop robust intrusion detection systems.
** Connect, Collaborate, And Innovate: IJCNC - Where Networking Futures Take ...IJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
Enhancing Traffic Routing Inside a Network through IoT Technology & Network C...IJCNCJournal
IoT networking uses real items as stationary or mobile nodes. Mobile nodes complicate networking. Internet of Things (IoT) networks have a lot of control overhead messages because devices are mobile. These signals are generated by the constant flow of control data as such device identity, geographical positioning, node mobility, device configuration, and others. Network clustering is a popular overhead communication management method. Many cluster-based routing methods have been developed to address system restrictions. Node clustering based on the Internet of Things (IoT) protocol, may be used to cluster all network nodes according to predefined criteria. Each cluster will have a Smart Designated Node. SDN cluster management is efficient. Many intelligent nodes remain in the network. The network design spreads these signals. This paper presents an intelligent and responsive routing approach for clustered nodes in IoT networks. An existing method builds a new sub-area clustered topology. The Nodes Clustering Based on the Internet of Things (NCIoT) method improves message transmission between any two nodes. This will facilitate the secure and reliable interchange of healthcare data between professionals and patients. NCIoT is a system that organizes nodes in the Internet of Things (IoT) by grouping them together based on their proximity. It also picks SDN routes for these nodes. This approach involves selecting one option from a range of choices and preparing for likely outcomes problem addressing limitations on activities is a primary focus during the review process. Predictive inquiry employs the process of analyzing data to forecast and anticipate future events. This document provides an explanation of compact units. The Predictive Inquiry Small Packets (PISP) improved its backup system and partnered with SDN to establish a routing information table for each intelligent node, resulting in higher routing performance. Both principal and secondary roads are available for use. The simulation findings indicate that NCIoT algorithms outperform CBR protocols. Enhancements lead to a substantial 78% boost in network performance. In addition, the end-to-end latency dropped by 12.5%. The PISP methodology produces 5.9% more inquiry packets compared to alternative approaches. The algorithms are constructed and evaluated against academic ones.
CW RADAR, FMCW RADAR, FMCW ALTIMETER, AND THEIR PARAMETERSveerababupersonal22
It consists of cw radar and fmcw radar ,range measurement,if amplifier and fmcw altimeterThe CW radar operates using continuous wave transmission, while the FMCW radar employs frequency-modulated continuous wave technology. Range measurement is a crucial aspect of radar systems, providing information about the distance to a target. The IF amplifier plays a key role in signal processing, amplifying intermediate frequency signals for further analysis. The FMCW altimeter utilizes frequency-modulated continuous wave technology to accurately measure altitude above a reference point.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
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Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
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A SOLUTION FRAMEWORK FOR MANAGING INTERNET OF THINGS (IOT)
1. International Journal of Computer Networks & Communications (IJCNC) Vol.8, No.6, November 2016
DOI: 10.5121/ijcnc.2016.8606 73
A SOLUTION FRAMEWORK FOR MANAGING
INTERNET OF THINGS (IOT)
Sukant K. Mohapatra1
, Jay N. Bhuyan2
, Pankaj Asundi1
, and Anand Singh3
1
Ericsson, Monroe, LA, USA
2
Dept. of Comp. Science, Tuskegee, AL, USA
3
CenturyLink, Monroe, LA, USA
ABSTRACT
Internet of Things (IoT) refers to heterogeneous systems and devices (often referred to as smart objects)
that connect to the internet, and is an emerging and active area of research with tremendous technological,
social, and economical value for a hyper-connected world. In this paper, we will discuss how billions of
these internet connected devices and machines will change the future in which we shall live, communicate
and do the business. The devices, which would be connected to the internet, could vary from simple systems
on chip (SOC) without any Operating System (OS) to highly powerful processor with intelligent OS with
widely varying processing capability and diverse protocol support. Many of these devices can also
communicate with each other directly in a dynamic manner. A key challenge is: how to manage such a
diverse set of devices of such massive scale in a secured and effective manner without breaching privacy. In
this paper, we will discuss various management issues and challenges related to different communication
protocol support and models, device management, security, privacy, scalability, availability and analytic
support, etc., in managing IoT. The key contribution of this paper is proposal of a reference management
system architecture based on cloud technology in addressing various issues related to management of
IoThaving billions of smart objects.
KEYWORDS
IoT, SOC, M2M, OMA, SOC, CSP, SLA, CoAP, REST
1. INTRODUCTION
Over the past few decades, there has been tremendous progress and technology innovation in the
field of computing and telecommunication. Although, in the past, telecommunication has been
more or less focused on human-to-human communication, now with advances and innovation,
machine-to-machine communication shall use same communication infrastructure and facilities in
a much greater scale. Billions of these smart machines/devices shall connect to the network and
significantly impact the way we live and do business. A market survey by Cisco predicts that, by
2020, about 50 billion of these smart devices shall be connected to the internet, far outpacing the
world population [1].
Smart devices have been used in various sectors such as the industry, offices, home, and
transportation, etc., for years. For example, many offices today have sensors to save energy in the
buildings [2], traffic light controller for traffic management [3]. Typically, sensor based smart
devices have been used in a closed system; for example, various sensors in an automobile mostly
work within the vehicle itself. In a smart home, safety related to fire, unauthorized intrusion, level
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of Carbon Monoxide (CO) in the house, etc., are managed by home monitoring
system/application. Thus it operates mostly in the Silo of Things (SoT) model with application
specific connected devices, with proprietary interconnection in a closed system. However,
connectivity of these devices in an open ecosystem, whether machine-to-machine and/or human-
to-machine communication, is already evolving and it would bring much greater value and create
a completely new generation of innovative services with tremendous socio-economic impact.
These smart devices, in an open ecosystem, shall help build smart homes, smart buildings, smart
automobiles, smart industries, and smart healthcare, etc., in a very synergetic manner in a hyper
connected world. For example, smart office shall not only conserve energy in the building but
also integrate with security, environmental conditionsin the office and their operational readiness
in a comprehensive manner. Individuals with smart wearables or bionic skins could provide
physiological and health information which could be used for enhanced wellbeing, health and
safety of the same individual while at home or working in an office.
As the use of smart devices proliferates with advanced sensors, actuators, processors, and
transceivers and get connected, many of the applications will also involve human and things
(human-to-machine) to operate synergistically. Human-in-the-loop model has tremendous
opportunity in various application verticals like smart healthcare and smart vehicles [4].
However, human-in-the-loop model has its own disadvantages, specifically complexity involved
in modelling human behaviour to work with smart devices in a synergetic and predictable way.
In this paper, we discuss various challenges in managing IoT in support of billions of smart
devices. We propose a solution framework to manage IoT ecosystem from enablement,
operational, and business application support point of view. The proposed architecture provides
an open model for development and integration of various innovative applications by 3rd
party in
supporting and enriching theIoT ecosystem. This will enable innovation and contribution from
many subject matter experts in evolving a rich IoT platform and ecosystem. The proposed
reference solution framework, which addresses various challenges faced by IoT management, is
the main contribution of this paper.
This paper is organized as follows:
Section II discusses transformation of silo of things to internet of things and related research
work. Section III highlights various requirement and challenges in managing smart objects that
are part of the IoT. Section IV provides a detailed view of referenced solution framework in
managing IoT and supporting its ecosystem. Section V describes how the referenced solution
framework meets various requirements and helps mitigate challenges, while section VI concludes
the paper with reference to potential future work in this area.
2. SILO OF THINGS TO INTERNET OF THINGS (IOT)
The current mode of operation in IoT space is very fragmented and silo based. Application
specific connected devices mostly have proprietary interconnection and work in a closed system.
For example, the alarm system in a smart home is operated by alarm and security companies with
dedicated servers and applications specifically to address security concerns of the home and alert
stakeholders in case of a security breach. Again, the same home is monitored for utility usage
often by different companies and applications (e.g. water, electricity, gas) in a very independent
and uncorrelated manner.
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Figure 1: Silo of Things to Internet of Things
IoT has been evolving to meet the challenges of growth of billions of interconnected smart
devices in an open system with standard based connectivity for varying capacity and models of
smart devices. In an open, non-silo based system, the huge volume of data obtained from smart
objects could be used in more intelligent and correlated manner with significant qualitative
impact on our daily life, health, communication, and work environment. For example, the food
habits of a person in a smart home with data from a smart refrigerator could be correlated with
his/her smart health wearable, predicting/inferring appropriate health guidance for the person.
Also an open IoT ecosystem shall bring subject matter experts from various domains to
effectively contribute and enrich the system. Figure 1 above depicts the transformation of Silo of
Things (SoT) to Internet of Things (IoT).
Internet of Things is a very active research area and significantresearch work and publications are
available: survey [5], security [6, 7, 8], communication protocols [9, 10], and various IoT vertical
domains [11, 12]. This paper focuses on solution framework for the platform in supporting
various IoT device management, communication protocols, application verticals, addressing
security issues in order to support IoT ecosystem. A solution framework addressing key
challenges in managing IoT ecosystems is the key contribution of this paper.
3. REQUIREMENTS AND CHALLENGES IN MANAGING IOT
IoT devices range from simple 8-bit System on Chip (SOC) to powerful 64-bit processor with
intelligent Operating Systems (OS), thus requiring support of varying communication protocols,
device management methods, pre-deployment testing and integration and monitoring during
operation, etc. In this section, we discuss various requirements and challenges while managing
IoT devices.
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3.1. Communication Protocols and Models
Figure 2presents a pictorial view of ETSI M2M reference architectural model [13].
Figure 2: ETSI M2M Reference Architectural Model
The ETSI reference model has three domains: Device and Gateway domain, Network domain,
and Application domain. The Device and Gateway domain includes smart devices such as
sensors. A gateway typically interconnects to the Communication Service Provider (CSP)
network supporting device inter-working and inter-connection. The M2M area network
supportsconnection between different smart devices and gateways. The Network domain provides
communication service between smart devices (including via Gateway) and servers in the
Application domain. It typically includes access and core network of a CSP, which could include
fixed as well as mobile networks. The Application domain supports various application services.
Application services are rendered by specific business-processing servers where data analysis,
various actions, alerts, and reports are handled.
M2M area networks for constrained IoT devices typically include personal area network
technologies, such as Bluetooth, Thread, ZigBee Pro, ZigBee SE, and NFC. Constrained devices
refer to devices using low power platform and wireless, limited computation and memory, low
bandwidth, etc. Constrained devices are expected to use 6LowPAN – UDP – DTLS – CoAP
protocols in higher layer. High performance IoT devices are expected to support Wi-Fi, Cellular
[2.5G/3G/4G (LTE)], and Ethernet technologies. High performance IoT devices are expected to
use IP v4/IP v6 – TCP/UDP – TLS – HTTP at higher layer. Figure 3 provides an overview of
protocol stacks for constraint and high performance IoT devices.
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Figure 3: A High Level view of Protocol Stack for IoT Devices
Industrial Internet Consortium document [14] provides detail on IIOT connectivity architecture,
stack model, and key system characteristics.
3.2. Device Management Requirements
Paper [15] describes lightweight framework for IoT device management whereas [16] describes
IoT device management in a smart home environment. In this section, we highlight the following
key device management functionality that a platform needs to support irrespective of different
protocol support, which are described in section 3.1.
• The ability to disconnect a rogue or stolen device
• The ability to update the software on a device
• Updating security credentials
• Remotely enabling or disabling certain hardware capabilities
• Remote configuration of device
• Remotely re-configuring network parameters for the device
3.3. Interoperability and Integration
Third party products/solutions have to be added to theIoT platform creating an open ecosystem.
This will ensure use of various applications and analytics developed by subject matter expert to
add value to the IoTecosystem. The platform must support easy integration mechanism for
incorporating such third party solutions by using an open application interface and tools.
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3.4. Analytics
In theIoT ecosystem, there will be a collection of vast amount of raw data from smart devices and
other systems. It is very important to use this raw data in an effective manner to derive usable
knowledge base and provide actionable alerts and intelligence to end user, both in a near real-time
as well as non-real-time basis. Action may happen in near real time, so there is a strong
requirement for real-time analytics. For example, in a smart home, when data related to level of
carbon monoxide in the house exceeds the threshold, the user must be alerted in real-time. In
addition, on different occasions, the device should be able to act on analyzed data in real-time.
However, in some cases, more powerful devices can also do event processing and action based on
embedded logic.
In addition to handling huge amounts of raw data, analytic solution will be able to handle various
types of data, varying from text to image, video, and voice in real physical world. The right data
model and database should be used for effective grid, stream, graph, big data, and in-memory
processing in a distributed environment. It is expected that analytics must have to deal with noisy
and sometimes incomplete data. New and advanced inference techniques, rules, and models have
to be used by the analytics system in order to deal with such noisy and incomplete data while
deriving any inference. In some domains, correlation of various data to derive meaningful
intelligence could be challenging.For example, in smart healthcare domain, raw sensor data from
an individual’s wearable and/or bionic skin patch must be correlated to semantically meaningful
activities of the individualand his/her habits.
It is also very critical to derive correct inference and/or predication by the analytics system while
dealing with noisy, incomplete data, unknown behaviours.Otherwise, it could lead to some
devastating consequences. For example, driving an actuator using wrong inference could create
serious safety issues. A probabilistic inference model with specific confidence level may be an
approach to address this issue. Analytic systems need to support various models to support
different use cases in various business domains. For example, some use case may need correlation
analysis, whereas another may need predictive analysis based on historical behaviour. An
adaptive model may be necessary to deal with evolving/adjusting behaviour of a smart device and
human behaviour specifically with human-in-the-loop environment, often referred as Internet of
Everything (IoE).
3.5. Security and Access Control
Security issue for IoT is very critical because smart device may have minimal capacity to comply
with complex security need and protocols, easy accessibility of device, and on-the-air
communication. Thus IoT devices are prone to security attacks [17]. There are many aspects of
security issues from information processing to transmission security [18].
IoT devices are often collecting highly personal data, and bringing the real world onto the Internet
(and vice-Versa). This brings following categories of security risks:
• Security risk unique to IoT device (specifically low-end devices)
• Security risk associated with protocol and data transmission by IoT devices
• Security risk inherent with internet
• Security risk ensuring safety of operation of devices like actuators
• Security risk due to incorrect inference
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• Security risk due to transient failure of the device
It is very likely that next generation smart devices with powerful processors [19] shall provide
enhanced security capability. However legacy devices supporting requisite security functionality
shall prove challenging.
It is expected that, IoT platform shall be used by a variety of users starting from system
administrator, various application users to 3rd
party vendors. It is extremely important that access
to the platform should be highly secured using various identification, authorization and
authentication techniques and roles based access control to accommodate different users with
varying roles and responsibilities [20]. In addition, the platform must be protected from potential
security attack and breach [21].
3.5. Privacy Considerations
Though IoThas evolved considerably and provides many potential benefits, it also creates an
opportunity for privacy violation of physical objects, individuals, or groups. The challenges are
that, unlike the situation where the data owners are an individual ora group, in IoT space privacy
for physical entities (things) like smart oven, smart room and its associated owners has to be
taken into consideration. Analysis of collected data from smart devices and various inferences
could breach privacy of individuals or groups. For example, identification specific ailment of an
individual based on smart wearable data could infringe the individual’s privacy and his/her health
insurance risk.
An effective privacy policy must be devised and enforced by the system. The solution must be
able to create and store various privacy policies based on consent of individual, legitimate owners
of smart devices, and applicable laws. Privacy policy could be updated dynamically by authorized
policy administrators. Once policy is configured, the system shall ensure against breach of any
privacy policy.
3.5. Scalability
It is expected that billions of smart devices shall be connected to the internet. It raises many
challenges with respect to scalability and reliability of platform in order to handle devices of such
massive scale. The solution framework must support various aspects such as access authorization
and authentication, connectivity, current and evolving communication protocols, monitoring,
control and associated applications while supporting billions of smart devices. The platform
architecture must scale, be secured and highly reliable to support potentially trillions of smart
objects.
4. REFERENCE IOT- ARCHITECTURE MODEL
This section describes in detail the generic architectural framework for managing IoT. First we
describe various components and their functionality and then realization of same in a cloud based
architecture ensuring high scalability and availability.
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Figure 4: A Reference Architectural Framework for Managing IoT
Figure 4 depicts an overall view of IoT ecosystems in general. Smart devices typically connect to
Application domain via a communication network. The communication network could be
wireless and/or fixed network generally supported by communication service providers (CSP).
Typically, constrained IoT devices shall be connected with communication network via gateway,
whereas high performance IoT devices could directly connect to communication network itself.
In Figure 4, IoT data refers to IoT device communication related data and IoT device usage
specific data. This data could be available from different sources. For example, device
communication related data could be available from different operation support systems of
communication service provider, whereas device usage specific data could be available from
application servers supported by application service providers (e.g., alarm/security service
providers for smart home/enterprise). Thus IoT data could be very large, varied data type (text,
video, message, etc.) and shall be available over different storage mechanisms (different type of
database, files, object storage, etc.).
The reference architecture for IoT solution framework is component based model, where various
components and sub-components can be added in plug-and-play mode. Also, components could
operate logically in centralized way in a distributed manner on a cloud based platform.
4.1. Enablement Solution
This section describes two key modules on device management, device connectivity and testing
domain. However, other similar functional blocks can be easily added in a plug-and-play mode.
Device Management: The device management module is responsible for communicating with
devices using various protocols, both for constrained and high performance IoT devices
9. International Journal of Computer Networks & Communications (IJCNC) Vol.8, No.6, November 2016
supporting protocols as shown in
this module include:
• Software Management –
• Device Configuration – including configuration of bearer and proxies
• Disconnect/Wipe stolen and rogue devices
from network. Remotely lock
• Remote enabling/disabling of device capabilities
device peripherals like cameras etc.
• Etc.
Among others, Open Mobile Alliance (OMA) specification define
Management Server to configure parameters in a smart device supporting OMA Device
Management client. This include support of management objects related to device management
[22]. The server and client communication model is depicted in
Figure 5: Open Mobile Alliance (OMA)
Device Test Management: It is critical that IoT devices be tested in pre
assuring that there are no major issues when it goes on
testing in post-deployment is necessary in order to diagnose and troubleshoot any problem with
device during operation. It is expected
location, so remote on-line testing is very critical f
view. The device test management module shall support functionality supporting bot
deployment and post-deployment testing of IoT devices. Open Mobile Alliance (OMA)
Diagnostics Monitoring Function Specifica
framework in supporting diagnostic and monitoring information [2
4.2. Operational Solutions
The Operational Solution layer covers many functional areas primarily supporting operational
management support aspect for IoT. It has many supporting software infrastructure components
such as data collection, event broker, policy management as well as operational functional
module supporting various analytics functions. Analytics solution also includes logic, algor
and framework to support rich analytics functions based on machine learning [2
intelligence [25], and natural language processing.
ernational Journal of Computer Networks & Communications (IJCNC) Vol.8, No.6, November 2016
supporting protocols as shown in Figure 3. Key device management functionality supported by
– installation and upgrade of device f/w and s/w
including configuration of bearer and proxies
Disconnect/Wipe stolen and rogue devices – Disconnect misbehaving (rouge) device
from network. Remotely lock-in and/or wipe-out of the device when it is stolen or lost.
enabling/disabling of device capabilities – allows to remotely enable and disable
device peripherals like cameras etc.
Among others, Open Mobile Alliance (OMA) specification defines protocols allowing a Device
Management Server to configure parameters in a smart device supporting OMA Device
Management client. This include support of management objects related to device management
]. The server and client communication model is depicted in Figure 5.
Figure 5: Open Mobile Alliance (OMA) – Client Server Model
It is critical that IoT devices be tested in pre-deployment
no major issues when it goes on-line. Similarly, mechanism for
deployment is necessary in order to diagnose and troubleshoot any problem with
device during operation. It is expected that many of the IoT devices shall be deployed in remote
line testing is very critical from the operational cost effectiveness point of
view. The device test management module shall support functionality supporting bot
deployment testing of IoT devices. Open Mobile Alliance (OMA)
Diagnostics Monitoring Function Specifications defines standardized management object
framework in supporting diagnostic and monitoring information [23].
Operational Solution layer covers many functional areas primarily supporting operational
spect for IoT. It has many supporting software infrastructure components
such as data collection, event broker, policy management as well as operational functional
module supporting various analytics functions. Analytics solution also includes logic, algor
and framework to support rich analytics functions based on machine learning [2
], and natural language processing.
ernational Journal of Computer Networks & Communications (IJCNC) Vol.8, No.6, November 2016
81
igure 3. Key device management functionality supported by
Disconnect misbehaving (rouge) device
out of the device when it is stolen or lost.
allows to remotely enable and disable
allowing a Device
Management Server to configure parameters in a smart device supporting OMA Device
Management client. This include support of management objects related to device management
deployment, thus
Similarly, mechanism for remote
deployment is necessary in order to diagnose and troubleshoot any problem with
many of the IoT devices shall be deployed in remote
operational cost effectiveness point of
view. The device test management module shall support functionality supporting both pre-
deployment testing of IoT devices. Open Mobile Alliance (OMA)
tions defines standardized management object
Operational Solution layer covers many functional areas primarily supporting operational
spect for IoT. It has many supporting software infrastructure components
such as data collection, event broker, policy management as well as operational functional
module supporting various analytics functions. Analytics solution also includes logic, algorithms,
and framework to support rich analytics functions based on machine learning [24], artificial
10. International Journal of Computer Networks & Communications (IJCNC) Vol.8, No.6, November 2016
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Data Collection, Transformation and Distribution:The Data Collection, Transformation and
Distribution Module supports data collection for IoT devices from varied sources, including data
from enablement management layer. Primary functionality supported by this module is in
collecting various types of data from the underlying systems/environment and making it available
to interested applications. Data type could be very varied such as text, video, voice clips, topology
graph, and GIS based data. The data would be related to connectivity, session records, flow
records of smart object as well as usage data, stats, and KPIs supported by smart devices. An
effective collection of all different data in real-time and near-real-time is key to run various
analytics functions supporting operation and intelligent inference for proactive management of
supported IoT systems. From an architectural perspective, although this module could logically
behave in a centralized manner, but couldbe deployed in distributed fashion using cloud
computing environment.
Event Broker: Event broker provides common mechanism for the receipt and distribution of
autonomous events; the events originating from the managed environment (e.g. state changes of
objects, etc.) or from various supported applications that detect events of interest (e.g. abnormal
behaviour of devices, connectivity failure, etc.). Events could drive various actions and activities
for the supported applications.
Policy Management: Policy Management enables rule-driven behavior of operational framework
based on configured/dynamic policy. Policy management also could enforce various rules
regarding security management, rules related specific data analysis, etc.
Device Analytics:The Device Analytics component supports all analytics functionality related to
smart devices. This includes device connectivity analysis and inferences/alerts related to device
communication failure, abnormal behaviour, fault, and SLA violation. Device analytics shall also
support device usage related analysis and inferences based on device usages data and its KPI.
This module also supports various analysis and intelligence inference with respect to pre-and
post-deployment device testing data.
Billing Analytics: Billing of IoT service would be very different from typical billing of voice,
video, and data services as supported by service providers. Typical communication service
providers may just provide communication services for smart devices, whereas application
owners could be different entity. Even 3rd
party connectivity service providers could provide
device connectivity service using infrastructure of multiple communication service providers
across various regions. IoT ecosystem platform could be shared by many vendors and specific
functionality can be serviced based on vendor’s need, rather than whole platform being owned
and operated by each vendor. Thus, the Billing Analytics module is expected to support billing
and invoicing models supporting various models and business use cases in a flexible and
configurable way.
Big Data Analytics: The big data analytics support analysis of collected data from various
sources for intelligence inferences related to specific business application support and
monetization. This is primarily non-real-time data analysis. For example, it could use various
application data such as energy consumption, water consumption, security data for a smart home
and use external data (e.g., weather data) to provide various useful information for resident of
home, security personnel, township, insurance company, etc. As an example, by using weather
chart, it could provide analysis such as excess water usage by sprinkler system at home, thus
enabling user to save on water usage bill. Based on security incidents in various home/offices in a
region, the security personnel (e.g., police) in township/county/community could devise a smart
11. International Journal of Computer Networks & Communications (IJCNC) Vol.8, No.6, November 2016
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policing plan. The algorithm, logic, and framework of this module could be applied for various
application domains such as smart city, smart transport, smart health, etc.
Data Lake: The data lake shown in the solution framework could include data in core and Edge
Lake. This component provides a persistence mechanism for both structured and unstructured
data that is collected and made available for application analysis. It will leverage some of the Big
Data technologies for performing various analytics at the edge (the Edge Lake) and
complementing the Big Data Core Lake.
4.3. Business Solution
At the business layer, the IoT ecosystems support total solutions covering applications in various
verticals, such as smart home, smart cities, smart grid, smart health, connected automotive, etc.,
and its use cases. Thus it provides complete solution for operating a specific vertical/domain in a
comprehensive manner. For example, a smart city may include many aspects such as smart
policing, traffic management, waste management, transportation, etc. Thus the smart city business
module supportsall the aspects in managing a smart city, so that the user (e.g., city authorities)
can use this business application to manage all major aspects of the city in a comprehensive and
intelligent way, thereby providing the best service to city residents in a cost effective and efficient
manner.
4.4. Security Framework
The security framework includes Operation, Administration and Management (OAM) and
Security Management that supports user administration, authentication, authorization, auditing,
and secured communication, etc. [26, 27] for operation personnel. The Security framework shall
also support overall security of IoT management framework ecosystem and supported application
against security risk and external security attack (such as denial of service attacks).
4.5. GUI Framework
The Web Server based GUI framework provides web-based access to IoT management ecosystem
from client workstation. The GUI framework also supports generation of various adhoc reports,
and enables communication with users of the system, both online or offline.
4.6. Open API/SDK
It is expected that IoT ecosystem would need expertise in many different domains to leverage the
true value of IoT deployment. For example, the domain expertise in smart health and smart city
area would be quite different. Thus an Open API/SDK is essential for people/organization with
different domain knowledge/expertise to contribute to IoT ecosystem. The Solution frame
supports an open API/SDK, so that 3rd
party application developer can contribute to IoT
ecosystem development and enhancement. The 3rd
party interface could be based on
Representational State Transfer (REST) Application Programming Interface (API) [28] for
interworking with IoT ecosystem. REST API can also be used for interfacing operational
application with business layer applications supporting integration.
The IoT platform needs an efficient, reliable, and scalable way to handle connectivity and
communication with large number of devices as well as storage, processing and analysis. Cloud
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based architecture for the IoT platform is most suitable, when it comes to storing, processing, and
analysing data, especially big data. [29], [30] describes platforms for building, testing, and
deploying applications for cloud computing.
5. MANAGING THE CHALLENGES OF IOT
It is evident that the proposed solution framework as described in section IV, meets all key
challenges in supporting and managing theIoT ecosystem.
The enablement layer of solution framework supports various communication protocols and
models using device management component. Device management modules also support key
functionality enabling various aspect of device management from software upgrade to handling
security related issues for stolen/lost IoT devices.
Open API/SDK module provides interoperability and integration mechanism for 3rd
party
applications. Flexible and open API enable easy integration with 3rd
party applications and using
SDK the external application developer could access various relevant object model in the system
and develop value added applications.
Security framework enables solution framework security. A rule based access control to the
system can be enforced by well-defined rules and policy via policy management component.
Various privacy constraints and consideration can also be enforced via policy management
module by defining associate rules and policy.
Scalability, high availability, and reliability of application framework is very critical in
supporting the IoT solution model. The proposed solution framework is expected to be
implemented in a cloud environment and applications can be hosted in a distributed computing
environment, which provides high availability and thus ensures reliability. The cloud based
implementation also supports the required scalability. IoT devices are expected to grow
exponentially over the years, thus the solution framework based on cloud computing paradigm
can support moderate to large number of smart devices as needed.
6. CONCLUSIONS
IoT will evolve over time with ever increasing advances and capability of smart devices such as
sensor, actuators, robust communication and harvesting knowledge and intelligence from arrays
of vast amount of data moving from an information age to intelligence age. This will change our
current mode of lifestyle and work habits in a significant and perhaps in a disruptive way.
There are several efforts in different standard organizations such asETSI, Open Mobile Alliance,
OneM2M, IEEE, ITU-T and forums are focused on various standard activities and architectural
aspects supporting IoT. It is expected that work in many of the overlapping areas could converge
in near future.
In this paper we focused on overall need of an IoT ecosystem and solution framework to support
it. In our future work, we expect to focus on the area of analytics, since it is the heart of providing
intelligent and high value add for IoT ecosystem.
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ACKNOWLEDGEMENTS
This research was supported in part by NSF Grant # 1614845.
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Authors
Sukant K. Mohapatracurrently works as a CTO in Ericsson, USA. He has a
Ph.D.degree in Computer Science with specialization in Telecommunications from
Stevens Institute of Technology, New Jersey. His work and research interest
includes: Next Generation Fixed and Mobile Network Architecture, Network
Planning, Design, Optimization, and Network Management,Network
Virtualization, Cloud Computing, and Internet of Things (IoT).He is recipient of
DMTS award at Bell Laboratories and a senior member of IEEE. He is the founder
chairman of National Institute of Science and Technology (NIST), India.
Jay N. Bhuyan is a professor in the Department of Computer Science at Tuskegee
University. His research and teaching interests include Telecom Software
Architecture and Development, Software and Network Security, Big Data
Analytics, and Parallel & Distributed Computing. He received a Ph.D. in Computer
Science from the University of Louisiana at Lafayette. He has over 25 years of full-
time and part-time teaching experience as well as over 15 years of research and
development experience in the Telecom industry. He is a member of IEEE and
IEEE Computer, IEEE Communications Societies.
Pankaj Asundi brings 30 years of systems and technology experience to Ericsson
in his position as Vice President Sales for IOT, Cloud and Media solutions. His
key responsibilities are to develop and manage new business. Before joining
Ericsson, Pankaj was a Software Development Manager for First Consulting
Group. He holds a Master of Science in Industrial Engineering from University
of Oklahoma.
15. International Journal of Computer Networks & Communications (IJCNC) Vol.8, No.6, November 2016
87
Anand Singh is currently working in CenturyLink as Vice President –
Architecture. He has over twenty-seven years of telecom industry experience
with technological, transformational and strategic leadership in Network,
OSS/BSS, and emerging technologies/services. In past he has worked as
DMTS, technology leader and executive director at AT&T and Bell
laboratories. He has PhD degree in Physics from Banaras Hindu University,
India, and worked as Research Scientist in Carnegie-Mellon University,
University of California Berkeley, and Naval Research Laboratories
WashingtonDC.