The IoT platform - Internet of Things - ثاني ثانوي

2. The lot IoT in our Lives In this unit, students will learn about how networking and communication technologies enable loT platforms and systems. They will also learn about their social impact and their expected evolution in the near future. Finally, we will cover the main concerns and limitations of IoT systems and how they are regulated. Learning Objectives In this unit, you will learn to: > Identify the cloud, fog, and edge layers for loT applications. > Describe the main enablers of loT systems. > Distinguish the networking protocols and technologies that are the basis of loT communications, > Classify the main applications of IoT solutions. > Recognize the importance of the IoT in the near future. > Describe the security concerns of complex loT systems. > State the technological challenges of lot systems. > Identify how loT applications are regulated.

Lesson 1 The loT Platform The Internet in the internet of Things The term Internet of Things contains two keywords: Internet and Things. We explained what Things (smart devices) are and now we will explore the Internet part of an IoT solution. Cloud connectivity and services enable smart objects to gather measurements from the sensors and send commands to control the actuators. IoT devices are usually connected to a cloud IoT service using a communication protocol and through this service, the main IoT application will take decisions based on the collected data. In this lesson you will learn about the Cloud-Fog-Edge architecture, the networks and protocols used, and the type of data exchanged to support an effective IoT solution. Cloud, Fog and Edge The most common cloud computing infrastructure is called the Cloud-Fog-Edge architecture. Briefly, this model describes three levels of storage, connectivity, and applications where "cloud" is the data center infrastructure. "edge" is the data processing that happens at the network's edge, close to the physical object creating the data, and "fog" is the mediator between the edge and the cloud for various purposes. You already know how cloud computing. enables the storage and processing of data for a range of applications. Now, you will learn about the two other parts of the loT computing infrastructure. Physical object البحر Cloud Fog Edge 2073-1445 Figure 2.1 Edge to tog to cloud arcitecture Link to gelden www.len edu.

Fog Computing Fundamentals A constant technological goal of loT systems is to distribute data management as close to the sensor/actuator nodes. Fog computing is the most well-known example of edge services in lot, that is closer to the things that generate the lot data. A fog node can be any device with computing, storage, and network connectivity. Some examples are industrial controllers, switches, routers, embedded servers, and loT gateways. Analyzing loT data close to its origin reduces latency, offloads gigabytes of network traffic from the core network, and keeps sensitive data within the local network. Enilpoins (Sensor) Fog (Server) Endpoint (Sensor) → Fog (Server) Latency is the delay in the processing of data over a network connection or the delay between a user action and the response. Endpoint A data routing service that can receive and send data from and to other services. It can be a program on a computer or a dedicated hardware device. Latency- Gateway A gateway enables connectivity for devices that cannot connect directly to the internet. A WiFi hotspot works as a gateway. 38 -Distance Distance Agure 2.2 Example of latency Increasing by the distance Typically, fog services are performed very close to the loT device, as close to the edge endpoints as possible. One significant benefit is that the fog node has contextual awareness of the sensors it manages due to its geographic proximity to those sensors. Because the fog node can analyze data from all the sensors on that section, it can provide contextual analysis of the messages it receives and may choose to send only relevant data to the cloud. As a result, the volume of data sent upstream is significantly reduced, making it much more helpful to cloud-based applications and analytics servers. Furthermore, having contextual awareness allows fog nodes to respond to events in the loT network much faster than the traditional close model, which would likely cause higher latency and slower response times. Thus, the fog layer provides a distributed network capability, allowing devices to be monitored, controlled, and analyzed Pulcin real-time without waiting for communication from the cloud's central application and analytics servers.. 2173-1445 Filtered data Data from sensors Figure 3 Fog data analysis

Fog Computing Advantages Fog applications are as diverse as the loT itself. Their typical responsibilities include data reduction, monitoring, and analyzing real-time data from network-connected devices. Table 2.1. Fog Computing Advantages Advantage Contextual location awareness and low latency Geographic distribution Deployment near loT endpoints Wireless communication between the fog and the IoT device Use for real-time interactions Description The fog node is located as close as possible to the loT endpoint to provide distributed computing. In direct contrast to the more centralized cloud, fog node-targeted services and applications require widely spread installations. Typically, fog nodes are deployed in the presence of several lot endpoints. Typical metering deployments typically consist of 3000 to 4000 nodes per gateway, which also serves as a fog computing node. Although it is possible to connect wired nodes, the benefits of fog are greatest when a large number of endpoints are involved, and wireless access is the simplest way to achieve scalability. Important fog applications involve interactions in real-time, as opposed to batch processing. The preprocessing of data in fog nodes enables upper-layer applications to process a subset of the larger data packets وزارة التعليم real-time newby maru modas Fog wireless more endpoints Figure 2.4: Features of the fog layer 39

Edge Computing Endpoints Newer types of loT endpoints have sufficient computing power to perform low-level analytics and filtering. These are called edge computing endpoints or edge devices. This layer in the cloud-fog-edge architecture provides more efficiency to the loT solution. The cloud is not replaced by edge or fog computing. Instead, all these layers complement one another. The edge and fog computing layers assist in filtering, analyzing, and managing data. They prevent the cloud from being queried for each event by each lot device. This model suggests that network bandwidth, computation, and data storage resources are organized hierarchically. Data is collected, analyzed, and sent at each stage based on the capabilities of the resources at each layer. The latency decreases as more data is sent to edge endpoints closer to the loT devices. The benefit of this hierarchy is that responses to events from resources close to the loT device are quick with immediate results. At the same time, big data storage and processing resources in cloud data centers are available when needed. Edge and Fog Working Together Edge device Edge devices are intelligent gateways capable of processing data locally. IoT devices can connect to edge devices over local networks like WiFi and Bluetooth. Edge and fog computing necessitates using an abstraction layer to enable applications to communicate with one another. The abstraction layer exposes standardized Application Programming Interfaces (APIs) for monitoring, provisioning, and controlling physical resources. To support flexibility and consistency across the loT system, the abstraction layer also requires a mechanism to support virtualization, with the ability to run multiple operating systems or service containers on physical devices. Regarding architecture, fog nodes closest to the network edge receive data from loT devices. The fog loT application then directs various data types to the best location for analysis. The most time-sensitive data is analyzed closest to the smart objects generating the data on the edge or fog. node. Data that can be acted on in seconds or minutes is routed to an aggregation node for analysis and action. Less time-critical data is sent to the cloud for historical analysis, big data analytics, and long-term storage. For example, thousands of fog nodes could send data summaries to the cloud for historical analysis and storage. Considering these factors will help decide whether edge or fog computing would improve the system's efficiency. Sensor Mobile device Sensing Edge layer Fog layer Cloud Data Center Real-time data processing Edge analytics Monitoring • Data visualization 40 Data management • Data analysis Data filtering Figure 2.5 Edge and fog lavers in an IoT system Application logic Big data processing Big data warehousing

IoT Enablers IoT Data In IoT, data, generated by billions of loT devices, creates considerable value since it allows organizations to analyze sensed data in order to offer new services that improve user experience, cut costs or open up new revenue streams. Even though unstructured data makes up the majority of loT-generated data, the insights it offers through analytics can transform operations and help to develop new business models. However, managing and evaluating all this data can be challenging. To solve this problem, loT deployments are designed to filter noncritical data generation or consumption, cut back on upstream data that is not necessary, and respond to devices as quickly as possible. Consider a smart city with hundreds of thousands of smart lighting devices connected via an loT system. Most Information transferred between lighting network modules and the control center is of little interest. However, patterns in this data might give helpful insights that can assist in forecasting when lights need repairs or when they can be turned on or off, reducing operational expenses. وزارة التعليم 125-1485 Figure 2. A sinact city with cum smart devices 41

42 Data Classification Not all data should be treated in the same way; it can be classified and evaluated in several ways. Several data analytics tools and processing techniques can be utilized. 10T-relevant classifications include whether the data is structured or unstructured and whether it is in motion or at rest. Data in Motion Vs. at Rest Data is either in transit, and called "data in motion", or stored somewhere and called "data at rest". Network traffic and traditional client/server exchanges, such as web browsing, file transfers, and emails are examples of data in motion. Data at rest is data saved on a simple USB drive, a hard drive on your notebook or a storage array in a cloud data center. From the standpoint of the lot, data from smart objects is considered data in motion as it travels across the network to its final destination. This data is frequently handled at the edge devices or fog nodes. When data processing happens at an edge device, it can be filtered or destroyed, or it may be transmitted to a fog node or a data center for additional processing and possible storage. Data at rest Data in motion Figure 27 Data in motion and data al rest Edge Analytics The adoption of cloud services has been an area of evolution for loT in recent years and data analytics is a vital element. In the world of lot, huge amounts of data are collected on the devices and must frequently be analyzed and acted upon in real-time. Not only is the volume of data generated at the edge massive, requiring increased network bandwidth to the cloud, but the data may be so time sensitive that it requires urgent attention, and waiting for deep analysis in the cloud is not viable. A relatively new technology, edge amalytics, solves this issue by providing data analytics functions within the loT device. The data analysis is performed on the device for minimal latency before the data is sent to the cloud. العليم 173-1865 Data at rest Figure 2.8 Edge analytics processing

ليم Networking Protocols Basic Networking Protocols The fundamental Internet networking protocols, Internet Protocol (IP), TCP, and UDP, also provide connectivity for Internet of Things networks. Data transmission between smart objects and any other system in an loT application is handled via higher-level protocols. These new protocols have been developed to address the requirements of loT data transfer. Some loT networks rely on a push model, such as a sensor reporting at regular intervals or responding to a local trigger. And others rely on a pull model, such as an application that queries the sensor for data across the loT network. Table 2.2: How TCP and UDP protocols work Transmission Control Protocol (TCP) This connection-oriented protocol needs the formation of a session between the source and destination onor to data transmission It can be compared to a standard telephone conversation. In which two phones must be commected and a communication link established before the two parties can communicate. User Datagram Protocol (UDP) With this pretocol data can be sent quickly from source to destination, but there is no guarantee that it will get there, this is like sending mall, in which a letter is mailed to the right person but it is not known for sure whether this letter is received until another letter is sent to the initial sender as a response. Wireless Access Protocols NFC Near-field communication (NFC) is a collection of protocols with a range of up to 4 centimeters. The small range and the low cost of the technology make NFC ideal for implementation in personal, everyday objects. Some applications include contactless payment systems using an NFC-enabled credit card or smartphone. Bluetooth Bluetooth is radio frequency wireless technology for exchanging data across short distances, removing the need for cables. Bluetooth is used for communication between devices of up to 10 meters. It can be found in various devices, appliances, gadgets, and even vehicles that, after they have been paired together, can send data to each other at high speeds. Devices include headphones and speakers, wireless keyboards, smart locks, and wristband watches. IEEE 802.15.4 IEEE 802.15.4 is a wireless access technology for low-cost, low-data-rate devices powered by Electricity or running on batteries. This networking technology is inexpensive and can support a longer battery life. It is also easy to set up because it uses a small protocol stack and is simple and flexible. 15 - כלו

44 IoT Networking Protocols Table 2.3 contains some of the latest networking protocols that loT devices use to communicate with each other and the Internet. These protocols build upon the basic Internet networking protocols.. Table 2.3: IoT networking protocols Protocol name GLO GLOWMAN LOWPAN Features 6LOWPAN is an acronym of IPv6 over Low Power Wireless Personal Area Networks. This protocol delivers low-cost and secure loT communications. ZigBee ZigBee ZigBee is an evalunion of bLOWPAN and provides a simpler and lus expensive way of communication than Bluetooth and WiFi. Common applications Include building automabon, home automation, and healthcare ISA i 100 WIRELESS ISA100.11a WirelessHART Wireless IART وزارة التعليم כקוע THREAD Threed ISA100 11a protocol is a standard for Industrial automaten of wireless systems. used for process control. WirelessHART is a protocol stack foi creating a time-synchronized, salf organizing and selfhealing mesh architecturE Thread is a set of protocols for making a safe and reliable mesh network for connecting and contrilling devices, mainly at home.

IoT Communication Technologies The various communication technologies for loT solutions are classified by the range of information and data transmitted through them. Keep in mind that devices that use long range communication technologies consume much more energy than their short range counterparts. Table 2.4: IoT communication technologies classified by distance Distance Short range Medium range Long range loT communication technologies A serial cable is a classic example of a wired system. Wireless short-range solutions, with a maximum distance of tens of meters between two devices, are usually a replacement for serial cables. Short-range wireless technologies include Bluetooth, Near-Field Communication (NFC) and Radio Frequency Identification (RFID). This is the most common type of loT access technology There are various implementations in the tens to hundreds of meters range. The maximum distance between two devloss is frequently less than one kilometer, but Radio Frequency (RF) technologies have no predetermined maximum distances, as long as the radio signal is broadcast and received properly. Medium-range wireless technologies include ILEE 802 11 Wi-Fi. Wired technologies such as IEC 302 3 Ethernet and IEEE 1901.2 Narrowband Power Line Communications (PLC) may also be classified as medium-range Long-range technologies are required for distances larger than one kilometer between two devices. Cellular (2G, 3G, 4G, 5G) and Low-Power Wide-Area (LPWA) technologies are examples of wireless technologies. LPWA communications may communicate over a broad area while requiring little power. As a result, these technologies are appropriate for battery-powered loT sensors IEEE 802.3 via optical fiber and IEEE 1901 Broadband Power Line Communications are both categorized as long-range but are not considered loT access technologies. Long Range Medium Range 802.3 Fiber 5G 4G LPWA 1901.2 PLC 802 11 WiFi RFID وزارة التعليم Bluetooth Short Range NFC 2173-17 Figure 2.9 Ranges of communication technologies 45

Connectivity Issues An Internet connection can be unreliable and loss of connectivity for a short or longer period can happen unexpectedly. What should an loT device do when the network connection is lost? The options are to drop the data or store the data locally until network connectivity is restored. The choice depends on the application, how critical the data is and the way the data is used to control actuators. It also depends on the amount of time the network connectivity is lost for. Data can be temporarily stored locally if the connection is restored quickly, but otherwise, an loT device cannot hold a large amount of data on its local storage. The code on the loT device must be smart enough to know how to handle connectivity issues. Sometimes loT devices can make limited decisions to control actuators without a connection to the main loT application. The edge or cloud services must also be capable of functioning with incomplete or delayed data. For example, they should not send commands to the loT device for data that are no longer relevant. Many cloud issues include momentary loss of network connectivity or timeouts when a service is unavailable, and loT devices can auto-recover from these problems. IoT cloud providers like AWS loT Core and Microsoft Azure loT Hub support the detection and handling of more persistent connectivity issues when they appear on systems implemented with these technologies. The lot cloud services can diagnose the problem, try to provide a temporary solution, and assist in guidance for a permanent fix. The loT system administrators are alerted when critical devices and infrastructure have issues and take action. AWS IoT Core Microsoft Azure * Edge router وزارة التعليم 123-1485 46 Internet connectivity Figure 21 of cloud services provide self-recovery actions Cloud server

Exercises 1 Read the sentences and tick ✔True or False. 1. The fog layer is closer to the smart objects than the edge layer. 2. The Internet can connect directly to the edge layer. 3. The fog layer can communicate directly with cloud services. 4. Data processing can occur both in the fog and cloud layers. 5. Data transferred to a hard drive can be considered "data at rest.". 6. Edge analytics replaces data processing in the cloud. 7. The UDP protocol awaits confirmation from the receiver that the package was received. 8. The ZigBee protocol sends more information about the sender object than other protocols 9. Cellular networks are used for short-range communication between smart objects 10. When connectivity issues occur, all the network protocols lose the data in transit. True False 0 • 2 Consider how adding the fog layer in loT applications improves their effectiveness. Present your ideas below. وزارة التعليم

48 3 Draw a diagram to visualize the relationship between the cloud, fog and edge layers of the loT architecture. 4 Discuss how edge analytics assist in effective loT solutions. وابة التعليم M-15

5 Classify the types of applications using the TCP and UDP communication protocols, respectively, 6 Describe the main characteristics of the IEEE 802.15.4 network protocol that makes it so prominent in loT applications. Present your ideas below. 7 Search the Internet for information about the main differences in communication between cellular networks and Bluetooth technologies. وزارة التعليم