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Internet of things
What is IoT?
The Internet of Things (IoT) describes the network of physical objects—“things”—that are
embedded with sensors, software, and other technologies for the purpose of connecting and
exchanging data with other devices and systems over the Internet. These devices range from
ordinary household objects to sophisticated industrial tools. With more than 7 billion connected
IoT devices today, experts expect this number to grow to 10 billion by 2020 and 22 billion by
2025. Oracle has a network of device partners.
Why is the Internet of Things (IoT) so important?
Over the past few years, IoT has become one of the most critical technologies of the 21st
century. Now that we can connect everyday objects—kitchen appliances, cars, thermostats,
baby monitors—to the internet via embedded devices, seamless communication is possible
between people, processes, and things.
By means of low-cost computing, the cloud, big data, analytics, and mobile technologies,
physical things can share and collect data with minimal human intervention. In this
hyperconnected world, digital systems can record, monitor, and adjust each interaction between
connected things. The physical world meets the digital world—and they cooperate.
What technologies have made IoT possible?
While the idea of IoT has been in existence for a long time, a collection of recent advances in a
number of different technologies has made it practical.
​ Access to low-cost, low-power sensor technology. Affordable and reliable
sensors are making IoT technology possible for more manufacturers.
​ Connectivity. A host of network protocols for the internet has made it easy to
connect sensors to the cloud and to other “things” for efficient data transfer.
​ Cloud computing platforms. The increase in the availability of cloud platforms
enables both businesses and consumers to access the infrastructure they need to
scale up without actually having to manage it all.
​ Machine learning and analytics. With advances in machine learning and analytics,
along with access to varied and vast amounts of data stored in the cloud, businesses
can gather insights faster and more easily. The emergence of these allied
technologies continues to push the boundaries of IoT and the data produced by IoT
also feeds these technologies.
​ Conversational artificial intelligence (AI). Advances in neural networks have
brought natural-language processing (NLP) to IoT devices (such as digital personal
assistants Alexa, Cortana, and Siri) and made them appealing, affordable, and viable
for home use.
limitations of the Internet:
1) The quality of information resources might not always be reliable and accurate.
2) Searching for information can be very tedious. (It is definitely time-consuming)
3) Internet is definitely not 100% secure.
Internet Architecture
The Internet architecture, which is also sometimes called the TCP/IP architecture after its two
main protocols, is depicted in Figure 1.14. An alternative representation is given in Figure 1.15.
The Internet architecture evolved out of experiences with an earlier packet-switched network
called the ARPANET. Both the Internet and the ARPANET were funded by the Advanced
Research Projects Agency (ARPA), one of the research and development funding agencies of
the U.S. Department of Defense. The Internet and ARPANET were around before the OSI
architecture, and the experience gained from building them was a major influence on the OSI
reference model.
Delay and Rushing
Delay is a natural consequence of implementations of the Internet architecture. Datagrams from
a single connection typically transit a path across the Internet in bursts. This happens because
applications at the sender, when sending large messages, tend to send messages larger than a
single datagram. The transport layer partitions these messages into segments to fit the
maximum segment size along the path to the destination. The MAC tends to output all the
frames together as a single blast after it has accessed the medium. Therefore, routers with
many links can receive multiple datagram bursts at the same time. When this happens, a router
has to temporarily buffer the burst, since it can output only one frame conveying a datagram per
link at a time. Simultaneous arrival of bursts of datagrams is one source of congestion in
routers. This condition usually manifests itself at the application by slow communications time
over the Internet. Delay can also be intentionally introduced by routers, such as via traffic
shaping.
Attackers can induce delays in several ways. We illustrate this idea by describing two different
attacks. It is not uncommon for an attacker to take over a router, and when this happens, the
attacker can introduce artificial delay, even when the router is uncongested. As a second
example, attackers with bot armies can bombard a particular router with “filler” messages, the
only purpose of which is to congest the targeted router.
Rushing is the opposite problem: a technique to make it appear that messages can be delivered
sooner than can be reasonably expected. Attackers often employ rushing attacks by first
hijacking routers that service parts of the Internet that are fairly far apart in terms of network
topology. The attackers cause the compromised routers to form a virtual link between them. A
virtual link emulates a MAC layer protocol but running over a transport layer connection
between the two routers instead of a PHY layer. The virtual link, also called a wormhole, allows
the routers to claim they are connected directly by a link and so are only one hop apart. The two
compromised routers can therefore advertise the wormhole as a “low-cost” path between their
respective regions of the Internet. The two regions then naturally exchange traffic through the
compromised routers and the wormhole.
An adversary usually launches a rushing attack as a prelude to other attacks. By attracting
traffic to the wormhole endpoints, the compromised routers can eavesdrop and modify the
datagrams flowing through them. Compromised routers at the end of a wormhole are also an
ideal vehicle for selective deletion of messages.
What is network virtualization?
Network Virtualization (NV) refers to abstracting network resources that were traditionally delivered in
hardware to software. NV can combine multiple physical networks into one virtual, software-based
network, or it can divide one physical network into separate, independent virtual networks.
Network virtualization software allows network administrators to move virtual machines across different
domains without reconfiguring the network. The software creates a network overlay that can run separate
virtual network layers on top of the same physical network fabric.
Why network virtualization?
Network virtualization is rewriting the rules for the way services are delivered, from the software-defined
data center (SDDC) to the cloud, to the edge. This approach moves networks from static, inflexible, and
inefficient to dynamic, agile, and optimized. Modern networks must keep up with the demands for
cloud-hosted, distributed apps, and the increasing threats of cybercriminals while delivering the speed
and agility you need for faster time to market for your applications. With network virtualization, you can
forget about spending days or weeks provisioning the infrastructure to support a new application. Apps
can be deployed or updated in minutes for rapid time to value.
How does network virtualization work?
Network virtualization decouples network services from the underlying hardware and allows the virtual
provisioning of an entire network. It makes it possible to programmatically create, provision, and manage
networks all in software while continuing to leverage the underlying physical network as the
packet-forwarding backplane. Physical network resources, such as switching, routing, firewalling, load
balancing, virtual private networks (VPNs), and more, are pooled, delivered in software, and require only
Internet Protocol (IP) packet forwarding from the underlying physical network.
Network and security services in software are distributed to a virtual layer (hypervisors, in the data
center) and “attached” to individual workloads, such as your virtual machines (VMs) or containers,
following networking and security policies defined for each connected application. When a workload is
moved to another host, network services and security policies move with it. And when new workloads are
created to scale an application, necessary policies are dynamically applied to these new workloads,
providing greater policy consistency and network agility.
The benefits of network virtualization
help organizations achieve major advances in speed, agility, and security by automating and simplifying
many of the processes that go into running a data center network and managing networking and security
in the cloud. Here are some of the key benefits of network virtualization:
● Reduce network provisioning time from weeks to minutes
● Achieve greater operational efficiency by automating manual processes
● Place and move workloads independently of physical topology
● Improve network security within the data center
A description of the new networking paradigms I believe will address the limitations of
the Internet’s current network architecture
Software-Defined Networking (SDN):
SDN separates the control plane from the data plane, allowing for centralized management and
programmability of network resources. This enables more flexible and dynamic network
configurations, making it easier to adapt to changing traffic patterns and application
requirements.
Network Function Virtualization (NFV):
NFV involves virtualizing network functions such as firewalls, load balancers, and routers. This
allows for more efficient resource utilization and easier scaling, as these functions can be
instantiated as virtual instances on commodity hardware.
Edge Computing:
Edge computing involves processing data closer to the source or point of consumption, reducing
latency and bandwidth usage. This paradigm is particularly useful for applications that require
real-time processing, such as Internet of Things (IoT) devices and augmented reality (AR)
applications.
Content-Centric Networking (CCN):
CCN focuses on retrieving content based on its name rather than its location (as in traditional IP
addressing). This approach can improve content distribution and caching, making data retrieval
more efficient and reducing the load on central servers.
Named Data Networking (NDN):
Similar to CCN, NDN replaces IP addresses with content names, aiming to make
communication more data-centric. This can improve security, caching, and content distribution,
as well as simplify some aspects of network management.
Mesh Networks:
Mesh networks involve interconnected nodes that cooperate to provide network coverage. They
can be particularly useful in areas with limited infrastructure or during network outages, as
nodes can relay data to reach their destination.
Blockchain-Based Networking:
Blockchain technology can potentially be applied to networking to enhance security,
transparency, and decentralized control. It could enable more secure identity management,
peer-to-peer communication, and resource sharing.
5G and Beyond: The evolution of cellular networks, including 5G and future generations, aims to
provide higher data rates, lower latency, and better connectivity for a wide range of devices.
These networks can enable new applications and use cases that were not feasible with previous
generations of mobile networks.
Quantum Networking:
Quantum networking leverages the principles of quantum mechanics to enable secure
communication through quantum key distribution and other quantum protocols. While still in its
early stages, this paradigm could revolutionize encryption and data security.
Cognitive Networking: Cognitive networks can autonomously adapt to changing conditions by
learning from the environment and optimizing their performance. This paradigm can improve
network efficiency and reliability by dynamically adjusting routing, spectrum usage, and other
parameters.
My views on the extent to which I believe new networking paradigms will be able to meet
the demands of users of the Internet with the emergence of the IoT.
Scalability:
IoT devices are projected to number in the billions, and traditional networking architectures
might struggle to handle such h scale. Paradigms like Software-Defined Networking (SDN) and
Network Function Virtualization (NFV) can provide more efficient resource utilization and
scalability by abstracting and centralizing network management.
Low Latency:
Many IoT applications, such as real-time monitoring and control, demand low-latency
communication. Edge computing and fog computing, which are closely related to IoT, can bring
computation and storage closer to the devices, reducing the round-trip time for data
transmission and improving response times.
Data Management:
IoT generates massive amounts of data that need to be efficiently collected, processed, and
analyzed. Content-Centric Networking (CCN) and Named Data Networking (NDN) could
alleviate the strain on centralized servers by focusing on content retrieval and efficient caching,
enhancing data management.
Reliability and Security:
IoT devices often operate in sensitive environments and may be vulnerable to security threats.
Blockchain-based networking and quantum networking could offer enhanced security measures
for IoT communication, ensuring data integrity and authentication.
Resource Efficiency:
IoT devices often have limited power and computational resources. Cognitive networking can
help optimize resource allocation and communication protocols to extend the battery life of IoT
devices and improve overall efficiency.
Heterogeneity:
IoT encompasses a wide range of devices with varying communication technologies and
capabilities. 5G and beyond could provide the necessary connectivity for diverse IoT devices,
accommodating their differing requirements.
Network Congestion:
The sheer volume of IoT devices could lead to network congestion. Mesh networks can help
alleviate congestion by allowing devices to relay data, creating a more distributed and
self-healing network infrastructure.
Diverse Use Cases:
IoT encompasses a wide array of applications, from smart cities and industrial automation to
healthcare and agriculture. Different networking paradigms might be better suited to specific use
cases, necessitating a flexible and adaptable approach.
Regulatory and Privacy Considerations: IoT networks must adhere to various regulations and
privacy requirements. Networking paradigms that offer enhanced security and data protection
mechanisms will be crucial to ensure compliance.
https://www.vmware.com/topics/glossary/content/network-virtualization.html
https://www.oracle.com/za/internet-of-things/what-is-iot/#:~:text=What%20is%20IoT%3F,and%2
0systems%20over%20the%20internet.
https://www.sciencedirect.com/topics/computer-science/internet-architecture

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internet architecture.pdf

  • 1. Internet of things What is IoT? The Internet of Things (IoT) describes the network of physical objects—“things”—that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the Internet. These devices range from ordinary household objects to sophisticated industrial tools. With more than 7 billion connected IoT devices today, experts expect this number to grow to 10 billion by 2020 and 22 billion by 2025. Oracle has a network of device partners. Why is the Internet of Things (IoT) so important? Over the past few years, IoT has become one of the most critical technologies of the 21st century. Now that we can connect everyday objects—kitchen appliances, cars, thermostats, baby monitors—to the internet via embedded devices, seamless communication is possible between people, processes, and things. By means of low-cost computing, the cloud, big data, analytics, and mobile technologies, physical things can share and collect data with minimal human intervention. In this hyperconnected world, digital systems can record, monitor, and adjust each interaction between connected things. The physical world meets the digital world—and they cooperate.
  • 2. What technologies have made IoT possible? While the idea of IoT has been in existence for a long time, a collection of recent advances in a number of different technologies has made it practical. ​ Access to low-cost, low-power sensor technology. Affordable and reliable sensors are making IoT technology possible for more manufacturers. ​ Connectivity. A host of network protocols for the internet has made it easy to connect sensors to the cloud and to other “things” for efficient data transfer. ​ Cloud computing platforms. The increase in the availability of cloud platforms enables both businesses and consumers to access the infrastructure they need to scale up without actually having to manage it all. ​ Machine learning and analytics. With advances in machine learning and analytics, along with access to varied and vast amounts of data stored in the cloud, businesses can gather insights faster and more easily. The emergence of these allied technologies continues to push the boundaries of IoT and the data produced by IoT also feeds these technologies. ​ Conversational artificial intelligence (AI). Advances in neural networks have brought natural-language processing (NLP) to IoT devices (such as digital personal assistants Alexa, Cortana, and Siri) and made them appealing, affordable, and viable for home use. limitations of the Internet: 1) The quality of information resources might not always be reliable and accurate. 2) Searching for information can be very tedious. (It is definitely time-consuming) 3) Internet is definitely not 100% secure.
  • 3. Internet Architecture The Internet architecture, which is also sometimes called the TCP/IP architecture after its two main protocols, is depicted in Figure 1.14. An alternative representation is given in Figure 1.15. The Internet architecture evolved out of experiences with an earlier packet-switched network called the ARPANET. Both the Internet and the ARPANET were funded by the Advanced Research Projects Agency (ARPA), one of the research and development funding agencies of the U.S. Department of Defense. The Internet and ARPANET were around before the OSI architecture, and the experience gained from building them was a major influence on the OSI reference model. Delay and Rushing Delay is a natural consequence of implementations of the Internet architecture. Datagrams from a single connection typically transit a path across the Internet in bursts. This happens because applications at the sender, when sending large messages, tend to send messages larger than a single datagram. The transport layer partitions these messages into segments to fit the maximum segment size along the path to the destination. The MAC tends to output all the frames together as a single blast after it has accessed the medium. Therefore, routers with many links can receive multiple datagram bursts at the same time. When this happens, a router has to temporarily buffer the burst, since it can output only one frame conveying a datagram per link at a time. Simultaneous arrival of bursts of datagrams is one source of congestion in routers. This condition usually manifests itself at the application by slow communications time over the Internet. Delay can also be intentionally introduced by routers, such as via traffic shaping. Attackers can induce delays in several ways. We illustrate this idea by describing two different attacks. It is not uncommon for an attacker to take over a router, and when this happens, the attacker can introduce artificial delay, even when the router is uncongested. As a second example, attackers with bot armies can bombard a particular router with “filler” messages, the only purpose of which is to congest the targeted router. Rushing is the opposite problem: a technique to make it appear that messages can be delivered sooner than can be reasonably expected. Attackers often employ rushing attacks by first
  • 4. hijacking routers that service parts of the Internet that are fairly far apart in terms of network topology. The attackers cause the compromised routers to form a virtual link between them. A virtual link emulates a MAC layer protocol but running over a transport layer connection between the two routers instead of a PHY layer. The virtual link, also called a wormhole, allows the routers to claim they are connected directly by a link and so are only one hop apart. The two compromised routers can therefore advertise the wormhole as a “low-cost” path between their respective regions of the Internet. The two regions then naturally exchange traffic through the compromised routers and the wormhole. An adversary usually launches a rushing attack as a prelude to other attacks. By attracting traffic to the wormhole endpoints, the compromised routers can eavesdrop and modify the datagrams flowing through them. Compromised routers at the end of a wormhole are also an ideal vehicle for selective deletion of messages.
  • 5. What is network virtualization? Network Virtualization (NV) refers to abstracting network resources that were traditionally delivered in hardware to software. NV can combine multiple physical networks into one virtual, software-based network, or it can divide one physical network into separate, independent virtual networks. Network virtualization software allows network administrators to move virtual machines across different domains without reconfiguring the network. The software creates a network overlay that can run separate virtual network layers on top of the same physical network fabric. Why network virtualization? Network virtualization is rewriting the rules for the way services are delivered, from the software-defined data center (SDDC) to the cloud, to the edge. This approach moves networks from static, inflexible, and inefficient to dynamic, agile, and optimized. Modern networks must keep up with the demands for cloud-hosted, distributed apps, and the increasing threats of cybercriminals while delivering the speed and agility you need for faster time to market for your applications. With network virtualization, you can forget about spending days or weeks provisioning the infrastructure to support a new application. Apps can be deployed or updated in minutes for rapid time to value. How does network virtualization work? Network virtualization decouples network services from the underlying hardware and allows the virtual provisioning of an entire network. It makes it possible to programmatically create, provision, and manage networks all in software while continuing to leverage the underlying physical network as the packet-forwarding backplane. Physical network resources, such as switching, routing, firewalling, load balancing, virtual private networks (VPNs), and more, are pooled, delivered in software, and require only Internet Protocol (IP) packet forwarding from the underlying physical network. Network and security services in software are distributed to a virtual layer (hypervisors, in the data center) and “attached” to individual workloads, such as your virtual machines (VMs) or containers, following networking and security policies defined for each connected application. When a workload is moved to another host, network services and security policies move with it. And when new workloads are
  • 6. created to scale an application, necessary policies are dynamically applied to these new workloads, providing greater policy consistency and network agility. The benefits of network virtualization help organizations achieve major advances in speed, agility, and security by automating and simplifying many of the processes that go into running a data center network and managing networking and security in the cloud. Here are some of the key benefits of network virtualization: ● Reduce network provisioning time from weeks to minutes ● Achieve greater operational efficiency by automating manual processes ● Place and move workloads independently of physical topology ● Improve network security within the data center A description of the new networking paradigms I believe will address the limitations of the Internet’s current network architecture Software-Defined Networking (SDN): SDN separates the control plane from the data plane, allowing for centralized management and programmability of network resources. This enables more flexible and dynamic network configurations, making it easier to adapt to changing traffic patterns and application requirements. Network Function Virtualization (NFV):
  • 7. NFV involves virtualizing network functions such as firewalls, load balancers, and routers. This allows for more efficient resource utilization and easier scaling, as these functions can be instantiated as virtual instances on commodity hardware. Edge Computing: Edge computing involves processing data closer to the source or point of consumption, reducing latency and bandwidth usage. This paradigm is particularly useful for applications that require real-time processing, such as Internet of Things (IoT) devices and augmented reality (AR) applications. Content-Centric Networking (CCN): CCN focuses on retrieving content based on its name rather than its location (as in traditional IP addressing). This approach can improve content distribution and caching, making data retrieval more efficient and reducing the load on central servers. Named Data Networking (NDN): Similar to CCN, NDN replaces IP addresses with content names, aiming to make communication more data-centric. This can improve security, caching, and content distribution, as well as simplify some aspects of network management. Mesh Networks: Mesh networks involve interconnected nodes that cooperate to provide network coverage. They can be particularly useful in areas with limited infrastructure or during network outages, as nodes can relay data to reach their destination. Blockchain-Based Networking: Blockchain technology can potentially be applied to networking to enhance security, transparency, and decentralized control. It could enable more secure identity management, peer-to-peer communication, and resource sharing. 5G and Beyond: The evolution of cellular networks, including 5G and future generations, aims to provide higher data rates, lower latency, and better connectivity for a wide range of devices. These networks can enable new applications and use cases that were not feasible with previous generations of mobile networks.
  • 8. Quantum Networking: Quantum networking leverages the principles of quantum mechanics to enable secure communication through quantum key distribution and other quantum protocols. While still in its early stages, this paradigm could revolutionize encryption and data security. Cognitive Networking: Cognitive networks can autonomously adapt to changing conditions by learning from the environment and optimizing their performance. This paradigm can improve network efficiency and reliability by dynamically adjusting routing, spectrum usage, and other parameters. My views on the extent to which I believe new networking paradigms will be able to meet the demands of users of the Internet with the emergence of the IoT. Scalability: IoT devices are projected to number in the billions, and traditional networking architectures might struggle to handle such h scale. Paradigms like Software-Defined Networking (SDN) and Network Function Virtualization (NFV) can provide more efficient resource utilization and scalability by abstracting and centralizing network management. Low Latency: Many IoT applications, such as real-time monitoring and control, demand low-latency communication. Edge computing and fog computing, which are closely related to IoT, can bring computation and storage closer to the devices, reducing the round-trip time for data transmission and improving response times.
  • 9. Data Management: IoT generates massive amounts of data that need to be efficiently collected, processed, and analyzed. Content-Centric Networking (CCN) and Named Data Networking (NDN) could alleviate the strain on centralized servers by focusing on content retrieval and efficient caching, enhancing data management. Reliability and Security: IoT devices often operate in sensitive environments and may be vulnerable to security threats. Blockchain-based networking and quantum networking could offer enhanced security measures for IoT communication, ensuring data integrity and authentication. Resource Efficiency: IoT devices often have limited power and computational resources. Cognitive networking can help optimize resource allocation and communication protocols to extend the battery life of IoT devices and improve overall efficiency. Heterogeneity: IoT encompasses a wide range of devices with varying communication technologies and capabilities. 5G and beyond could provide the necessary connectivity for diverse IoT devices, accommodating their differing requirements. Network Congestion: The sheer volume of IoT devices could lead to network congestion. Mesh networks can help alleviate congestion by allowing devices to relay data, creating a more distributed and self-healing network infrastructure. Diverse Use Cases: IoT encompasses a wide array of applications, from smart cities and industrial automation to healthcare and agriculture. Different networking paradigms might be better suited to specific use cases, necessitating a flexible and adaptable approach. Regulatory and Privacy Considerations: IoT networks must adhere to various regulations and privacy requirements. Networking paradigms that offer enhanced security and data protection mechanisms will be crucial to ensure compliance.