UNIT1-Fundamentals of SCADA IOT.pdf

ICSF- 302 FUNDAMENTALS OF SCADA & IOT UNIT I Aditya Rajesh More Evolution of Internet of Things Fundamentals of SCADA and IoT Unit I- by Aditya More 2 Evolution of Internet of Things The basic premise and goal of IoT is to “connect the unconnected.” This me...

ICSF- 302 FUNDAMENTALS OF SCADA & IOT UNIT I Aditya Rajesh More Evolution of Internet of Things Fundamentals of SCADA and IoT Unit I- by Aditya More 2 Evolution of Internet of Things The basic premise and goal of IoT is to “connect the unconnected.” This means that objects that are not currently joined to a computer network, namely the Internet, will be connected so that they can communicate and interact with people and other objects. IoT is a technology transition in which devices will allow us to sense and control the physical world by making objects smarter and connecting them through an intelligent network. Instead of viewing IoT as a single technology domain, it is good to view it as an umbrella of various concepts, protocols, and technologies, all of which are at times somewhat dependent on a particular industry. At the same time, it introduces new challenges, such as scaling the vast numbers of devices and amounts of data that need to be processed. Fundamentals of SCADA and IoT Unit I- by Aditya More 3 Evolution of Internet of Things Genesis of IoT: This section highlights IoT’s place in the evolution and development of the Internet. IoT and Digitization: This section details the differences between IoT and digitization and defines a framework for better understanding their relationship. IoT Impact: This section shares a few high-level scenarios and examples to demonstrate the influence IoT will have on our world. Convergence of IT and OT: This section explores how IoT is bringing together information technology (IT) and operational technology (OT). IoT Challenges: This section provides a brief overview of the difficulties involved in transitioning to an IoT-enabled world. Fundamentals of SCADA and IoT Unit I- by Aditya More 4 Genesis of IoT The age of IoT is often said to have started between the years 2008 and 2009. During this time period, the number of devices connected to the Internet eclipsed the world’s population. With more “things” connected to the Internet than people in the world, a new age was upon us, and the Internet of Things was born. The person credited with the creation of the term “Internet of Things” is Kevin Ashton. While working for Procter & Gamble in 1999, Kevin used this phrase to explain a new idea related to linking the company’s supply chain to the Internet. Kevin has subsequently explained that IoT now involves the addition of senses to computers. Fundamentals of SCADA and IoT Unit I- by Aditya More 5 Genesis of IoT Fundamentals of SCADA and IoT Unit I- by Aditya More 6 IoT and Digitization IoT and digitization are terms that are often used interchangeably. In most contexts, this duality is fine, but there are key differences to be aware of. At a high level, IoT focuses on connecting “things,” such as objects and machines, to a computer network, such as the Internet. IoT is a well-understood term used across the industry as a whole. On the other hand, digitization can mean different things to different people but generally encompasses the connection of “things” with the data they generate and the business insights that result. Fundamentals of SCADA and IoT Unit I- by Aditya More 7 IoT and Digitization Digitization, as defined in its simplest form, is the conversion of information into a digital format. Digitization has been happening in one form or another for several decades. The transportation industry is currently undergoing digitization in the area of taxi services. Businesses such as Uber and Lyft use digital technologies to allow people to get a ride using a mobile phone app. In the context of IoT, digitization brings together things, data, and business process to make networked connections more relevant and valuable. A good example of this that many people can relate to is in the area of home automation with popular products, such as Nest. With Nest, sensors determine your desired climate settings and also tie in other smart objects, such as smoke alarms, video cameras, and various third-party devices. Fundamentals of SCADA and IoT Unit I- by Aditya More 8 IoT Impact Managing and monitoring smart objects using real-time connectivity enables a whole new level of data- driven decision making. This in turn results in the optimization of systems and processes and delivers new services that save time for both people and businesses while improving the overall quality of life. Fundamentals of SCADA and IoT Unit I- by Aditya More 9 IoT and Digitization Assignment No. 1 The following examples will illustrate some of the benefits of IoT and their impact. ✓ Connected Roadways ✓ Connected Factory ✓ Smart Connected Buildings ✓ Smart Creatures Fundamentals of SCADA and IoT Unit I- by Aditya More 10 Convergence of IT and OT IT supports connections to the Internet along with related data and technology systems and is focused on the secure flow of data across an organization. OT monitors and controls devices and processes on physical operational systems. These systems include assembly lines, utility distribution networks, production facilities, roadway systems, and many more. Typically, IT did not get involved with the production and logistics of OT environments. Specifically, the IT organization is responsible for the information systems of a business, such as email, file and print services, databases, and so on. In comparison, OT is responsible for the devices and processes acting on industrial equipment, such as factory machines, meters, actuators, electrical distribution automation devices, SCADA. Fundamentals of SCADA and IoT Unit I- by Aditya More 11 Convergence of IT and OT Fundamentals of SCADA and IoT Unit I- by Aditya More 12 Challenges of IoT 1. IoT security IoT devices have been notoriously vulnerable to cyber attacks due to inherent issues. Their limited power supply necessitates low-power data transmission, making it challenging to implement robust security protocols like encryption and authentication, which increase power consumption. Over time, new vulnerabilities in device firmware are inevitable as technologies and exploitation techniques evolve. However, updating these vulnerabilities is difficult; on-site updates are impractical, and remote updates consume significant power and data. Additionally, IoT devices often depend on end users’ network infrastructure, such as WiFi, exacerbating their susceptibility to cyber attacks and enabling access to other networked devices and applications. Fundamentals of SCADA and IoT Unit I- by Aditya More 13 Challenges of IoT 2. Coverage To transmit and receive data, IoT devices need a network connection. Lose the connection, and you lose the device’s capabilities. While there are numerous IoT connectivity solutions, they’re all best suited for different types of coverage. The solution you choose can severely limit where you can deploy. This makes coverage a constant IoT challenge. For example, WiFi is a common choice for IoT connectivity. But your devices can only operate within a short range of a router, and you can only deploy your devices at locations that have WiFi. When the infrastructure isn’t available, you have to either pay to build it or outfit your devices with a backup solution that already has coverage. Fundamentals of SCADA and IoT Unit I- by Aditya More 14 Challenges of IoT 3. Scalability The scalability challenge of IoT involves managing a vast number of devices deployed across different regions, each requiring unique connectivity solutions like cellular networks, WiFi, or LoRaWAN. This diversity creates a fragmented ecosystem with various management platforms, support systems, and protocols, complicating tasks such as monitoring, maintenance, and updates. Integrating different technologies can lead to compatibility issues, inefficiencies, and higher operational costs. Different connectivity solutions may have varying levels of security, making it challenging to enforce uniform security policies and increasing the risk of vulnerabilities. Fundamentals of SCADA and IoT Unit I- by Aditya More 15 Challenges of IoT 4. Interoperability One of the great things about IoT is the flexibility to configure your tech stack to fit your specific needs. However, this also poses a challenge: not all IoT devices and solutions are compatible with each other or with your business applications. Adding new hardware and software might require a series of changes to maintain functionality while integrating the new technology. Another challenge for IoT manufacturers is interoperability, especially when using open-source technology. Without a universal standard, different businesses and countries might use different versions of open-source tech. This makes it hard to add new technology from different vendors or deploy IoT solutions in new regions. Fundamentals of SCADA and IoT Unit I- by Aditya More 16 Challenges of IoT 5. Bandwidth availability Radio Frequency (RF) bandwidth is a limited resource that must be shared globally. Even with billions of connected devices, there is generally enough bandwidth, but problems arise when too many devices use the same frequency bands in close areas, leading to signal interference. A common example is WiFi in apartment buildings, where each resident's WiFi router uses the same 2.4GHz or 5GHz frequencies. When routers are close together, such as on either side of the same wall, their signals can interfere with each other when used at the same time. In IoT, with thousands of devices often close together, adding billions more devices will crowd the RF spectrum even more. Manufacturers need to be aware of potential signal interference and bandwidth availability as they develop new IoT solutions. Fundamentals of SCADA and IoT Unit I- by Aditya More 17 Challenges of IoT 6. Limited battery life Most IoT devices have small batteries because the devices themselves are often tiny, with newer generations trending towards even smaller and more efficient designs. Larger batteries would limit where and how these devices can be installed. For instance, a bigger battery on a predictive maintenance sensor could prevent it from being placed in areas where it’s protected from extreme temperatures, debris, or impact. For devices that spend most of their life in the field without access to another power source, the battery is designed to last for years. This longevity is only possible if the device's operations use minimal power. Transmitting or receiving data for long periods drains too much battery life, so devices must be very efficient in their energy use. Fundamentals of SCADA and IoT Unit I- by Aditya More 18 Challenges of IoT 7. Remote access The type of connectivity an IoT device uses affects how you can access it. For instance, relying on your customers' WiFi or ethernet means support staff either need VPN access or must be on-site, which can be costly. On-site visits are expensive, but if that's the only way to troubleshoot or update a device, extra costs are unavoidable. Remote access capabilities significantly reduce support and maintenance expenses for you or your customers and make firmware updates manageable on a large scale. However, many IoT connectivity options lack the data speed needed for global remote access. Performing a single firmware update over a network with low data speed drains too much power for battery-dependent devices. Cellular connectivity addresses this issue. It offers the necessary data speed for efficient updates and supports secure remote access via VPNs. Fundamentals of SCADA and IoT Unit I- by Aditya More 19 M2M (Machine to Machine) Machine to machine, or M2M, is a term that refers to systems in which machines interact with one another autonomously and without the need for human involvement, regardless of the devices or communication channels involved. In 2013, the European Telecommunications Standards Institute (ETSI) and its 13 founding members started a project to develop a blueprint for M2M (Machine to Machine) and IoT (Internet of Things) systems. They took an intelligent idea from networking called "stacks," which is similar to the OSI model. This stacking approach was the best because it allowed one part of the system to change without affecting the neighboring parts. Fundamentals of SCADA and IoT Unit I- by Aditya More 20 The oneM2M IoT Standardized Architecture Fundamentals of SCADA and IoT Unit I- by Aditya More 21 The oneM2M IoT Standardized Architecture Applications Layer: The oneM2M architecture emphasizes the connectivity between IoT devices and their applications. This layer includes the protocols and APIs (Application Programming Interfaces) used by applications to communicate with IoT devices. APIs are tools that allow different software systems to interact with each other. In this layer, oneM2M aims to standardize these APIs for better integration with business intelligence (BI) systems, which analyze data to help businesses make decisions. Applications in the IoT ecosystem are often specific to industries, such as healthcare, smart homes, or industrial automation. Each industry has its own data models and requirements, so these applications are represented as vertical entities. This means they operate within their specific context and use specialized data structures and protocols to function effectively. Fundamentals of SCADA and IoT Unit I- by Aditya More 22 The oneM2M IoT Standardized Architecture Services Layer: This layer supports all industry-specific applications by providing a common infrastructure. OneM2M aims to create technical specifications for a common M2M Service Layer that can be embedded in various hardware and software to connect many devices to application servers. It also encompasses management protocols, which are the rules for managing and controlling devices and networks. Backhaul communications, which link smaller networks to a larger core network using technologies like cellular networks, MPLS (Multiprotocol Label Switching), or VPNs (Virtual Private Networks), are also part of this layer. On top of this infrastructure is the common services layer, which provides middleware and APIs that support third-party services and applications. Middleware is software that connects different systems or applications, enabling them to communicate. Fundamentals of SCADA and IoT Unit I- by Aditya More 23 The oneM2M IoT Standardized Architecture Network Layer: This layer deals with the communication between IoT devices. It includes the devices themselves and the communication networks that connect these devices. The infrastructure comprises wireless mesh technologies, such as IEEE 802.15.4, which is a standard for short-range, low-rate wireless personal area networks, and wireless point-to-multipoint systems, such as IEEE 802.11ah, a protocol for longer-range wireless networking. Wired connections, like those defined by IEEE 1901 standards for communication over power lines using existing electrical infrastructure, are also included. Devices in this layer can communicate directly with each other or through a field area network (FAN) to specific IoT applications. Additionally, the gateway device is part of this layer, acting as a bridge between local device networks and the broader core network Fundamentals of SCADA and IoT Unit I- by Aditya More 24 The IoT World Forum (IoTWF) Standardized Architecture In 2014 the IoTWF architectural committee (led by Cisco, IBM, Rockwell Automation, and others) published a seven-layer IoT architectural reference model. While various IoT reference models exist, the one put forth by the IoT World Forum offers a clean, simplified perspective on IoT and includes edge computing, data storage, and access. It provides a succinct way of visualizing IoT from a technical perspective. Each of the seven layers is broken down into specific functions, and security encompasses the entire model. Fundamentals of SCADA and IoT Unit I- by Aditya More 25 The IoT World Forum (IoTWF) Standardized Architecture Fundamentals of SCADA and IoT Unit I- by Aditya More 26 The IoT World Forum (IoTWF) Standardized Architecture Layer 1: Physical Devices and Controllers The first layer of the IoT Reference Model is the Physical Devices and Controllers layer. This layer includes all the "things" in the Internet of Things, such as sensors and endpoint devices. These devices can range in size from tiny sensors to large machines in factories. Their main role is to generate data and be accessible for queries or control over a network. The size of these “things” can range from almost microscopic sensors to giant machines in a factory. Fundamentals of SCADA and IoT Unit I- by Aditya More 27 The IoT World Forum (IoTWF) Standardized Architecture Layer 2: Connectivity The second layer is the Connectivity layer. Its main purpose is to ensure reliable and timely data transmission. This involves sending data from Layer 1 devices to the network and then to the information processing systems in Layer 3 (Edge Computing). This layer covers all networking elements, including: Last-mile network: Connects sensors/endpoints to the IoT gateway. Gateway: Acts as a bridge between the devices and the larger network. Backhaul networks: Connects the gateway to the core network. The Connectivity layer ensures that data flows smoothly and efficiently across the entire network. Fundamentals of SCADA and IoT Unit I- by Aditya More 28 The IoT World Forum (IoTWF) Standardized Architecture Fundamentals of SCADA and IoT Unit I- by Aditya More 29 The IoT World Forum (IoTWF) Standardized Architecture Layer 3: Edge Computing Layer 3 is dedicated to Edge Computing, which is sometimes referred to as the "fog" layer. This layer plays a crucial role in processing data close to where it is generated, rather than sending all raw data to a central location. By doing this, it helps to reduce the volume of data that needs to be transmitted and stored, improving efficiency and responsiveness in IoT systems. Fundamentals of SCADA and IoT Unit I- by Aditya More 30 The IoT World Forum (IoTWF) Standardized Architecture Key Functions of Layer 3: Data Reduction: This function involves filtering and aggregating raw data from devices to minimize the amount that needs to be sent to central systems. By reducing the data at the edge, it decreases the load on network bandwidth and central storage. Early Processing: At this stage, initial data analysis and processing are performed close to the data source. This can include tasks like anomaly detection, data normalization, and preliminary analytics. Early processing ensures that only relevant and processed information is forwarded, which helps in making quicker decisions and responses. Latency Reduction: By processing data locally, edge computing significantly reduces the time it takes to get actionable insights, which is critical for applications requiring real-time responses, such as industrial automation, autonomous vehicles, and smart grids. Fundamentals of SCADA and IoT Unit I- by Aditya More 31 The IoT World Forum (IoTWF) Standardized Architecture Fundamentals of SCADA and IoT Unit I- by Aditya More 32 The IoT World Forum (IoTWF) Standardized Architecture Upper Layers: Layers 4–7 Fundamentals of SCADA and IoT Unit I- by Aditya More 33 A Simplified IoT Architecture IoT systems share a common structure: connecting devices to a network to transport data for use by applications. Despite differences among various IoT models, they all aim to connect devices to a network for data transport and use by applications, whether in data centers, the cloud, or management points. This simplified framework includes the fundamental building blocks of data collection, storage, and processing, along with device, network, and application management. By breaking down the architecture into these basic components, the framework provides a clear and functional foundation for understanding IoT design and deployment principles across different industries. Fundamentals of SCADA and IoT Unit I- by Aditya More 34 A Simplified IoT Architecture Fundamentals of SCADA and IoT Unit I- by Aditya More 35 A Simplified IoT Architecture Nearly every IoT model includes core layers like devices ("things"), a communications network, and applications. However, the framework presented here uniquely separates core IoT functions and data management into parallel and aligned stacks. The Core IoT Functional Stack is simplified into three layers to help you understand the foundational building blocks of IoT architecture. While this simplification is helpful, the network communications layer within the IoT stack is quite detailed and involves a variety of technologies. Given the diverse nature of IoT sensors and the different methods for connecting them, the network communications layer must consolidate these connections, utilize gateway and backhaul technologies, and ultimately bring data to a central location for analysis and processing. Fundamentals of SCADA and IoT Unit I- by Aditya More 36 A Simplified IoT Architecture Fundamentals of SCADA and IoT Unit I- by Aditya More 37 A Simplified IoT Architecture The applications and analytics layer of IoT doesn't necessarily exist only in the data center or in the cloud. Due to the unique challenges and requirements of IoT, it is often necessary to deploy applications and data management throughout the architecture in a tiered approach, allowing data collection, analytics, and intelligent controls at multiple points in the IoT system. The three data management layers are the edge layer (data management within the sensors themselves), the fog layer (data management in the gateways and transit network), and the cloud layer (data management in the cloud or central data center). Fundamentals of SCADA and IoT Unit I- by Aditya More 38 The Core IoT Functional Stack IoT networks are built around the concept of “things,” or smart objects performing functions and delivering new connected services. These objects are “smart” because they use a combination of contextual information and configured goals to perform actions. These actions can be self-contained (that is, the smart object does not rely on external systems for its actions); however, in most cases, the “thing” interacts with an external system to report information that the smart object collects, to exchange with other objects, or to interact with a management platform. Fundamentals of SCADA and IoT Unit I- by Aditya More 39 Layer 1: Things: Sensors and Actuators Layer 1. Power Source: Objects are either battery-powered for mobility or power-connected for continuous operation. Mobility vs. Continuous Operation: Battery-powered objects offer mobility but have limited lifetime and energy consumption, while power-connected ones ensure continuous operation but lack mobility. 2. Mobility: Objects are classified as mobile or static based on movement requirements. Mobile vs. Static: Mobility range influences power source, from occasional movement (e.g., sensors attached to moving goods) to permanent placement (e.g., fixed sensors in buildings). 3. Reporting Frequency: Determines how often objects report data. Low vs. High Frequency: Higher reporting frequency consumes more energy, affecting power source (e.g., rust sensors reporting monthly vs. motion sensors reporting hundreds of times per second). Fundamentals of SCADA and IoT Unit I- by Aditya More 40 Layer 1: Things: Sensors and Actuators Layer 4. Data Complexity: Describes the quantity of data exchanged at each report cycle. Simple vs. Rich Data: Simple data (e.g., daily index values from humidity sensors) conserves power, while rich data (e.g., multiple parameters from engine sensors) requires more energy for transmission. 5. Report Range: Based on the distance between object and gateway. Short vs. Long Range: Determines necessity and range of communication between object and gateway (e.g., fitness band to phone within a few meters vs. moisture sensor to reader over hundreds of meters). 6. Object Density: Reflects the number of objects connected to a gateway in a given area. Sparse vs. Dense: Varies from few objects per area (e.g., oil pipelines with sensors every few miles) to many objects (e.g., telescope arrays with thousands of mirrors in a small area). Fundamentals of SCADA and IoT Unit I- by Aditya More 41 Layer 2: Communications Network Layer There is a direct relationship between the IoT network technology you choose and the type of connectivity topology this technology allows. Each technology was designed with a certain number of use cases in mind (what to connect, where to connect, how much data to transport at what interval and over what distance). These use cases deter- mined the frequency band that was expected to be most suitable, the frame structure matching the expected data pattern (packet size and communication intervals), and the possible topologies that these use cases illustrate. Fundamentals of SCADA and IoT Unit I- by Aditya More 42 Layer 2: Communications Network Layer Fundamentals of SCADA and IoT Unit I- by Aditya More 43 Layer 2: Communications Network Layer PAN (personal area network): Scale of a few meters. This is the personal space around a person. A common wireless technology for this scale is Bluetooth. HAN (home area network): Scale of a few tens of meters. At this scale, common wireless technologies for IoT include ZigBee and Bluetooth Low Energy (BLE). NAN (neighborhood area network): Scale of a few hundreds of meters. The term NAN is often used to refer to a group of house units from which data is collected. FAN (field area network): Scale of several tens of meters to several hundred meters. FAN typically refers to an outdoor area larger than a single group of house units. LAN (local area network): Scale of up to 100 m. This term is very common in net- working, and it is therefore also commonly used in the IoT space when standard net- working technologies (such as Ethernet or IEEE 802.11) are used. Other networking classifications, such as MAN (metropolitan area network, with a range of up to a few kilometre’s) and WAN (wide area network, with a range of more than a few kilometre’s), are also commonly used. Fundamentals of SCADA and IoT Unit I- by Aditya More 44 Layer 2: Communications Network Layer Point-to-point topologies: These topologies allow one point to communicate with another point. This topology in its strictest sense is uncommon for IoT access, as it would imply that a single object can communicate only with a single gateway. However, several technologies are referred to as “point-to- point” when each object establishes an individual session with the gateway. Point-to-multipoint topologies: These topologies allow one point to communicate with more than one other point. Most IoT technologies where one or more than one gateways communicate with multiple smart objects are in this category. However, depending on the features available on each communicating mode, several subtypes need to be considered. A particularity of IoT networks is that some nodes (for example, sensors) support both data collection and forwarding functions, while some other nodes (for example, some gateways) collect the smart object data. Fundamentals of SCADA and IoT Unit I- by Aditya More 45 Layer 3: Applications and Analytics Layer- Analytics Vs Control Applications Analytics Application: This application gathers data from various smart objects, processes it, and displays the results. The information can include historical reports, statistics, trends, or system states. The key function is processing the data to provide insights about the IoT network that are not apparent from a single smart object's data alone. Control Application: This application manages the behavior of smart objects or related devices. For example, a control application might increase pump speed if a connected pressure sensor detects a drop in pressure. These applications handle complex logic that individual IoT objects can't manage, either due to complexity or because they require data from multiple sources. Fundamentals of SCADA and IoT Unit I- by Aditya More 46 Layer 3: Applications and Analytics Layer- Data Vs Network Analytics Data Analytics: This type of analytics processes data from smart objects to provide insights into the IoT system. For instance, a basic dashboard can alert when a shelf is empty in a store based on weight sensor data. In more complex scenarios, data from various sensors (e.g., temperature, pressure, humidity) can be combined and processed to predict storms. Data analytics can also monitor IoT devices themselves, like using movement data from factory robots to predict maintenance needs before a breakdown. Network Analytics: IoT systems rely heavily on network connectivity. Any loss or degradation in connectivity can significantly impact system efficiency. For example, in open mines, automated dump trucks rely on wireless networks for navigation. A loss of connectivity can halt operations, leading to accidents or decreased efficiency, as the trucks stop moving without a network connection. Fundamentals of SCADA and IoT Unit I- by Aditya More 47 IoT Data Management and Compute Stack The data generated by IoT sensors is one of the single biggest challenges in building an IoT system. In the case of modern IT networks, the data sourced by a computer or server is typically generated by the client/server communications model, and it serves the needs of the application. In sensor networks, the majority of data generated is unstructured and of very little use on its own. In most cases, IoT data processing occurs in the cloud, where smart objects connect for centralized processing. This model is simple and allows a central application to manage all analytics. However, as data volume and device variety increase, the need for more efficient processing often brings data analysis closer to the source, near the IoT devices. Fundamentals of SCADA and IoT Unit I- by Aditya More 48 IoT Data Management and Compute Stack These new requirements include: Minimizing Latency: In many industrial systems, milliseconds matter. Quick responses are essential to prevent issues like manufacturing line shutdowns or restoring electrical service. By analyzing data close to the device that collected it, systems can avert disasters and prevent cascading failures. Conserving Network Bandwidth: Devices such as offshore oil rigs generate 500 GB of data weekly, and commercial jets produce 10 TB of data every 30 minutes of flight. It is impractical to transfer such large amounts of data from numerous edge devices to the cloud. Increasing Local Efficiency: Data collection across vast geographic areas with varying environmental conditions often requires localized responses. Conditions in one area may trigger specific actions independent of another site hundreds of miles away. Analyzing data locally ensures that responses are relevant and immediate, without the need to involve a centralized cloud system for every situation. Fundamentals of SCADA and IoT Unit I- by Aditya More 49 Cloud Computing Model in IoT Fundamentals of SCADA and IoT Unit I- by Aditya More 50 Cloud Computing Model in IoT Several data-related problems need to be addressed in cloud computing- Limited Bandwidth: Last-mile IoT networks often provide very limited bandwidth, sometimes only tens of Kbps per device or less, making it hard to manage thousands or millions of devices. High Latency: Latency can be significant, ranging from hundreds to thousands of milliseconds, rather than the milliseconds needed for quick responses. Unreliable Backhaul: Network backhaul from gateways can be unreliable, often relying on 3G/LTE or satellite links, which can also be costly with per-byte data usage models. High Data Volume: The volume of data transmitted over the backhaul can be large, but much of it may be unimportant, like simple polling messages. Big Data Challenges: Storing and analyzing all sensor data in the cloud is impractical due to the massive amount of data generated, making real-time analysis and response difficult. Fundamentals of SCADA and IoT Unit I- by Aditya More 51 Fog Computing The solution to the challenges mentioned in the previous section is to distribute data management throughout the IoT system, as close to the edge of the IP network as possible. Any device with computing, storage, and network connectivity can be a fog node. Examples include industrial controllers, switches, routers, embedded servers, and IoT gateways. Analyzing IoT data close to where it is collected minimizes latency, offloads gigabytes of network traffic from the core network, and keeps sensitive data inside the local network. The concept of fog was first developed by Flavio Bonomi and Rodolfo Milito of Cisco Systems. In the world of IoT, fog gets its name from a relative comparison to computing in the cloud layer. Just as clouds exist in the sky, fog rests near the ground. In the same way, the intention of fog computing is to place resources as close to the ground—that is, the IoT devices—as possible. Fundamentals of SCADA and IoT Unit I- by Aditya More 52 Fog Computing Fundamentals of SCADA and IoT Unit I- by Aditya More 53 Fog Computing- Characteristics Contextual location awareness and low latency: The fog node sits as close to the IoT endpoint as possible to deliver distributed computing. Geographic distribution: In sharp contrast to the more centralized cloud, the services and applications targeted by the fog nodes demand widely distributed deployments. Deployment near IoT endpoints: Fog nodes are typically deployed in the presence of a large number of IoT endpoints. For example, typical metering deployments often see 3000 to 4000 nodes per gateway router, which also functions as the fog computing node. Wireless communication between the fog and the IoT endpoint: Although it is possible to connect wired nodes, the advantages of fog are greatest when dealing with a large number of endpoints, and wireless access is the easiest way to achieve such scale. Use for real-time interactions: Important fog applications involve real-time interactions rather than batch processing. Preprocessing of data in the fog nodes allows upper-layer applications to perform batch processing on a subset of the data. Fundamentals of SCADA and IoT Unit I- by Aditya More 54 Edge Computing Fog computing solutions are being adopted by many industries, and efforts to develop distributed applications and analytics tools are being introduced at an accelerating pace. The natural place for a fog node is in the network device that sits closest to the IoT endpoints, and these nodes are typically spread throughout an IoT network. However, in recent years, the concept of IoT computing has been pushed even further to the edge, and in some cases it now resides directly in the sensors and IoT devices. Edge computing is also sometimes called “mist” computing. If clouds exist in the sky, and fog sits near the ground, then mist is what actually sits on the ground. Thus, the concept of mist is to extend fog to the furthest point possible, right into the IoT endpoint device itself. Fundamentals of SCADA and IoT Unit I- by Aditya More 55 Edge Computing- Characteristics 1. Resource-Constrained Devices: Edge devices often have limited resources but are becoming increasingly capable of handling more complex tasks. 2. Local Analytics and Filtering: These devices can perform low-level analytics and filtering, enabling them to make basic decisions right at the data source. 3. Proximity to Data Sources: Edge computing processes data close to where it is generated, such as sensors and IoT devices, minimizing the distance data must travel. 4. Quick Local Problem Detection: This close proximity allows for rapid detection and response to localized issues, improving overall system efficiency. Fundamentals of SCADA and IoT Unit I- by Aditya More 56 Edge Computing- Characteristics 5. Improved Responsiveness: By processing data locally, edge computing reduces latency significantly, leading to faster responses and more timely actions. 6. Enhanced Local Monitoring: Edge devices can continuously monitor local conditions and generate immediate alerts, ensuring timely intervention when necessary. 7. Inter-device Communication: Edge devices can communicate with each other to share information and coordinate their actions, improving the overall functionality of the IoT system. 8. Support for Fog Nodes: They complement fog nodes by reporting localized events and data, which helps in broader and more comprehensive analysis of the entire network. Fundamentals of SCADA and IoT Unit I- by Aditya More 57