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6 - IoT Processing Topologies and Types
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Book:
- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 115-127
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Summary
Learning Outcomes
After reading this chapter, the reader will be able to:
List common data types in IoT applications
Understand the importance of processing
Explain the various processing topologies in IoT
Understand the importance of processing off-loading toward achieving scalability and cost-effectiveness of IoT solutions
Determine the importance of choosing the right processing topologies and associated considerations while designing IoT applications
Determine the requirements that are associated with IoT-based processing of sensed and communicated data.
Data Format
The Internet is a vast space where huge quantities and varieties of data are generated regularly and flow freely. As of January 2018, there are a reported 4:021 billion Internet users worldwide. The massive volume of data generated by this huge number of users is further enhanced by the multiple devices utilized by most users. In addition to these data-generating sources, non-human data generation sources such as sensor nodes and automated monitoring systems further add to the data load on the Internet. This huge data volume is composed of a variety of data such as e-mails, text documents (Word docs, PDFs, and others), social media posts, videos, audio files, and images, as shown in Figure 6.1. However, these data can be broadly grouped into two types based on how they can be accessed and stored: 1) Structured data and 2) unstructured data.
Structured data
These are typically text data that have a pre-defined structure [1]. Structured data are associated with relational database management systems (RDBMS). These are primarily created by using length-limited data fields such as phone numbers, social security numbers, and other such information. Even if the data is human or machinegenerated, these data are easily searchable by querying algorithms as well as humangenerated queries. Common usage of this type of data is associated with flight or train reservation systems, banking systems, inventory controls, and other similar systems. Established languages such as Structured Query Language (SQL) are used for accessing these data in RDBMS. However, in the context of IoT, structured data holds a minor share of the total generated data over the Internet.
Unstructured data
In simple words, all the data on the Internet, which is not structured, is categorized as unstructured. These data types have no pre-defined structure and can vary according to applications and data-generating sources.
2 - Basics of Network Security
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 25-47
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Summary
Learning Outcomes
After reading this chapter, the reader will be able to:
Understand the concepts of network security
List the basic terminologies and technologies associated with security, privacy, and authenticity
Explain functioning of digital signatures and key management
Differentiate between network layer, transport layer, and application layer security
Explain firewalls
Relate new concepts with concepts learned before to make a smooth transition to IoT
Introduction
The range of operations dependent on computers, computer networks, and the Internet is vast. Healthcare, banking, governance, security, military, research, power, agriculture, and other fields are nowadays largely dependent on networked systems. The huge implications of the failure of one of these domains due to computerbased security lapses are undeniable. This necessitates the need for various security protocols for computer networks and computer-based systems. Typically, security in networks focuses on preventing unauthorized or forced access to a user's or organization's system or systems. The concept of security applies even to computers or systems which are not connected to a network or the Internet. The main aspects of securing a system are security, privacy, and authenticity. The security operations in computers encapsulate protection of hardware, software, data, and identity.
The various forms of network attacks are classified into two broad categories: General cyber threats, and threats to web databases [1]. Attacks such as authentication violation, non-repudiation, Trojan horses, viruses, fraud, sabotage, denial of service, and even natural disasters are categorized as general cyber threats. In contrast, attacks such as access control violations, integrity violations, confidentiality violations, privacy violations, authenticity violations, and identity thefts are categorized as threats to web databases. Most of the commonly available security tools are antiviruses, anti-malware, anti-spyware, and firewalls. These are mostly software-based tools and used by individuals or for personal computing systems. However, costlier options such as hardware-based systems and hardware–software hybrid systems such as access control mechanisms, hardware firewalls, and proxy servers are the most opted for security measures for large organizations. These tools are designed to protect a user from a range of attacks.
Points to ponder
Zero day attacks are exploits (attacks) that make use of a previously unknown security vulnerability in a system (software or hardware) to gain access to the system or take over it. The term `zero day’ refers to the time duration of the discovery of the vulnerability and the launch of attack (the attack is launched on the day of the discovery of the vulnerability).
13 - Vehicular IoT
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Book:
- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 283-292
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Summary
Learning Outcomes
After reading this chapter, the reader will be able to:
Relate to the applicability of IoT in real scenarios
List the salient features of vehicular IoT
Understand the requirements, challenges, and advantages of implementing IoT in vehicles
Relate to the appropriate use of various IoT technologies through a real-life case on vehicular IoT
Introduction
In this chapter, we discuss the application of IoT in connected vehicular systems. The use of connected vehicles is increasing rapidly across the globe. Consequently, the number of on-road accidents and mismanagement of traffic is also increasing. The increasing number of vehicles gives rise to the problem of parking. However, the evolution of IoT helps to form a connected vehicular environment to manage the transportation systems efficiently. Vehicular IoT systems have penetrated different aspects of the transportation ecosystem, including on-road to off-road traffic management, driver safety for heavy to small vehicles, and security in public transportation. In a connected vehicular environment, vehicles are capable of communicating and sharing their information. Moreover, IoT enables a vehicle to sense its internal and external environments to make certain autonomous decisions. With the help of modern-day IoT infrastructure, a vehicle owner residing in Earth's northern hemisphere can very easily track his vehicular asset remotely, even if it is in the southern hemisphere. In this chapter, we discuss the importance and applications of IoT in the vehicular systems. Figure 13.1 represents a simple architecture of a vehicular IoT system. The architecture of the vehicular IoT is divided into three sublayers: device, fog, and cloud.
Device: The device layer is the bottom-most layer, which consists of the basic infrastructure of the scenario of the connected vehicle. This layer includes the vehicles and road side units (RSU). These vehicles contain certain sensors which gather the internal information of the vehicles. On the other hand, the RSU works as a local centralized unit that manages the data from the vehicles.
Fog: In vehicular IoT systems, fast decision making is pertinent to avoid accidents and traffic mismanagement. In such situations, fog computing plays a crucial role by providing decisions in real-time, much near to the devices. Consequently, the fog layer helps to minimize data transmission time in a vehicular IoT system.
Conceptual Questions
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 375-387
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Summary
Introduction
This portion of the book spans the contents of the entire book. It is designed to provide readers with an idea about the various concepts required for utilizing IoT in real life. We present, here, various conceptual questions, which one comes across in real life; they can be answered using the concepts, protocols, and methodologies covered in the previous chapters of this book. This portion also provides an informal guideline for teachers and instructors to formulate questions relating to IoT and its technologies.
The questions provided in here are significantly different from the ones covered at the end of each chapter. They require the reader to delve deeper into the concepts and fundamentals of the covered technologies, which will require some effort on the reader's part. At times, the readers will have to consult other books, online resources, and materials. This exercise will enable them to explore, beyond the introductory level, the various concepts covered in this book.
Questions
Q1 What are the roles of end-users and the service provider in cloud computing?
Q2 What is a hypervisor?
Q3 Let there be a task of 480 TB from a host machine that needs to be processed in the cloud. The service provider has three data centers (DC), DC1, DC2, and DC3, which are capable of processing the task. The following table describes the capacity of different data centers: To which of the DCs do you think it best to allocate the task? Justify your answer.
Q4 Let there be four fog nodes F1, F2, F3, and F4, connected with several IoT devices. The data generated from the IoT devices can be processed either in single or multiple fog nodes. The fog nodes, F1, F2, F3, and F4, can accommodate up to 20 GB, 90 GB, 28 GB, and 46 GB respectively. Further, these fog nodes, F1, F2, F3, and F4 take 12 μs; 18 μs; 28 μs and 22 μs to complete 10 GB of task. A cloud architecture is also available to execute different tasks; it can process 20 GB of task in 8 μs. An IoT device requires to process 246 GB of data. The time taken to transmit data packets to the cloud is longer than the time taken to transmit data packets to fog nodes. However, the device is associated with a critical application.
7 - IoT Connectivity Technologies
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Book:
- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 128-162
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Summary
Learning Outcomes
After reading this chapter, the reader will be able to:
List common connectivity protocols in IoT
Identify the salient features and application scope of each connectivity protocol
Understand the terminologies and technologies associated with IoT connectivity
Determine the requirements associated with each of these connectivity protocols in real-world solutions
Determine the most appropriate connectivity protocol for each segment of their IoT implementation
Introduction
This chapter outlines the main features of fifteen identified commonly used and upcoming IoT connectivity enablers. These connectivity technologies can be integrated with existing sensing, actuation, and processing solutions for extending connectivity to them. Some of these solutions necessarily require integration with a minimal form of processing infrastructure, such as Wi-Fi. In contrast, others, such as Zigbee, can work in a standalone mode altogether, without the need for external processing and hardware support. These solutions are outlined in the subsequent sections in this chapter.
IEEE 802.15.4
The IEEE 802.15.4 standard represents the most popular standard for low data rate wireless personal area networks (WPAN) [1]. This standard was developed to enable monitoring and control applications with lower data rate and extend the operational life for uses with low-power consumption. This standard uses only the first two layers—physical and data link—for operation along with two new layers above it: 1) logical link control (LLC) and 2) service-specific convergence sublayer (SSCS). The additional layers help in the communication of the lower layers with the upper layers. Figure 7.1 shows the IEEE 802.15.4 operational layers. The IEEE 802.15.4 standard was curated to operate in the ISM (industrial, scientific, and medical) band.
The direct sequence spread spectrum (DSSS) modulation technique is used in IEEE 802.15.4 for communication purposes, enabling a wider bandwidth of operation with enhanced security by the modulating pseudo-random noise signal. This standard exhibits high tolerance to noise and interference and offers better measures for improving link reliability. Typically, the low-speed versions of the IEEE 802.15.4 standard use binary phase shift keying (BPSK), whereas the versions with high data rate implement offset quadrature phase shift keying (O-QPSK) for encoding the message to be communicated. Carrier sense multiple access with collision avoidance (CSMA-CA) is the channel access method used for maintaining the sequence of transmitted signals and preventing deadlocks due to multiple sources trying to access the same channel.
Dedication
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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9 - IoT Interoperability
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Book:
- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 214-234
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Summary
Learning Outcomes
After reading this chapter, the reader will be able to:
Understand the importance of interoperability in IoT
List various interoperability types
Identify the salient features and application scope of each interoperability type
Understand the challenges associated with interoperability in IoT
Comprehend the importance of real-world use of interoperability frameworks in IoT
Introduction
The introduction of billions of connected devices under the IoT environment, which may extend to trillions soon, has contributed massively to the evolution of interoperability. As more and more manufacturers and developers are venturing into IoT, the need for uniform and standard solutions is felt now more than ever before [1]. Figure 9.1 shows the various facets of interoperability in IoT. Interoperability is considered as the interface between systems or products—hardware, software, or middleware—designed in such a manner that the connecting devices can communicate, exchange data, or services with one another seamlessly irrespective of the make, model, manufacturer, and platform.
The urgency in the requirement for interoperability and interoperable solutions in IoT arose mainly due to the following reasons:
(i) Large-scale Cooperation: There is a need for cooperation and coordination among the huge number of IoT devices, systems, standards, and platforms; this is a long-standing problem. Proprietary solutions are seldom reusable and economical in the long run, which is yet another reason for the demand for interoperability.
(ii) Global Heterogeneity: The network of devices within and outside the purview of gateways and their subnets are quite large considering the spread of IoT and the applications it is being adapted to daily. Device heterogeneity spans the globe when connected through the Internet. A common syntax, platform, or standard is required for unifying these heterogeneous devices.
(iii) Unknown IoT Device Configuration: Device heterogeneity is often accompanied by further heterogeneity in device configurations. Especially considering the global-scale network of devices, the vast combinations of device configurations such as data rate, frequencies, protocols, language, syntax, and others, which are often unknown beforehand, further raise the requirement of interoperable solutions.
(iv) Semantic Conflicts: The variations in processing logic and the way data is handled by the numerous sensors and devices making up a typical IoT implementation, makes it impossible for rapid and robust deployment. Additionally, the variations in the end applications and their supported platform configurations further add to the challenges.
PART TWO - INTERNET OF THINGS
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 73-74
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List of Tables
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp xxv-xxvi
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PART FOUR - IOT CASE STUDIES AND FUTURE TRENDS
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 269-270
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Preface
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp xxxi-xxxvi
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Summary
Overview and Goals
Internet of Things (IoT) is rapidly gaining a foothold in the technology sector; it has managed to emerge as a highly sought-after field of study and research in computing sciences and electronics. The vastly interdisciplinary nature of the areas to which IoT can be applied has managed to pique the interest of the whole world. IoT finds diverse use in domains spanning industrial, military, as well as regular consumer applications. The versatility of IoT and its ability to connect anything make it one of the most demanded technologies of the modern age. The involvement of people from vastly diverse and distinct backgrounds, all point to the need for a concise repository of information on this new technology.
The Internet hosts much information on IoT, which is in the form of theory, tutorials, courses, implementations, and others. However, these discussions are so scattered that even professionals in this field have trouble obtaining integrated and concise information on IoT.
IoT is a new paradigm for connecting “things” in order to automate a system. In the context of IoT, “things” include computers, cell phones, medical devices, vehicles, wearables, and other appliances and devices for daily use. These “things” tend to be heterogeneous, which results in the development and existence of a vast number of communication solutions and protocols, which vary distinctly from each other. Consequently, communications among these “things” is a challenging issue in IoT. Another major challenge in IoT is the dynamic nature of “mobile things,” which generally follow a decentralized architecture. Due to this decentralized communication and control structure, the connectivity and data transmission dynamically changes with time, in turn resulting in a new set of challenges.
Pedagogical Aids
We have included various pedagogical aids to help the reader swiftly grasp the contents and the treatment of the various topics covered in this book. We have provided a set of conceptual questions at the end of this book. For solving these questions, the reader must have completely grasped the concepts covered in this book.
Additionally, we provide visual presentations of the chapters covered in this book so that it can be used as a teaching aid in colleges and universities. Each chapter of this book has the following pedagogical components:
Learning outcomes, which gives an initial glimpse into the chapter.
8 - IoT Communication Technologies
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 163-213
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Summary
Learning Outcomes
After reading this chapter, the reader will be able to:
List common communication protocols in IoT
Identify the salient features and application scope of each communication protocol
Understand the terminologies and technologies in IoT communication
Determine the requirements associated with each of these communication protocols in real-world solutions
Determine the most appropriate communication protocol for their IoT implementation
Introduction
Having covered the various connectivity technologies for IoT in the previous chapter, this chapter specifically focuses on the various intangible technologies that enable communication between the IoT devices, networks, and remote infrastructures. We organize the various IoT communication protocols according to their usage into six groups: 1) Infrastructure protocols, 2) discovery protocols, 3) data protocols, 4) identification protocols, 5) device management protocols, and 6) semantic protocols. These protocols are designed to enable one or more of the functionalities and features associated with various IoT networks and implementations such as routing, data management, event handling, identification, remote management, and interoperability. Figure 8.1 outlines the distribution of these IoT communication protocol groups [3].
Before delving into the various IoT communication protocols, we outline some of the essential terms associated with IoT networks that are indirectly responsible for the development of these communication protocols.
Constrained nodes
Constrained nodes is a term associated with those nodes where regular features of Internet-communicating devices are generally not available. These drawbacks are often attributed to the constraints of costs, size restrictions, weight restrictions, and available power for the functioning of these nodes. The resulting restrictions of memory and processing power often limit the usage of these nodes. For example, most of these nodes have a severely limited layer 2 capability and often lack full connectivity features and broadcasting capabilities. While architecting their use in networks and networked applications, these nodes require special design considerations. The issues of energy optimization and bandwidth utilization are dominant work areas associated with these nodes [1].
Constrained networks
Constrained networks [2], [1] are those networks in which some or all of the constituent nodes are limited in usage aspects due to the following constraints:
limited processing power resulting in restrictions on achieving smaller duty cycles.
PART ONE - INTRODUCTION
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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4 - Emergence of IoT
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 75-96
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Summary
Learning Outcomes
After reading this chapter, the reader will be able to:
Explain the chronology for the evolution of Internet of Things (IoT)
Relate new concepts with concepts learned earlier to make a smooth transition to IoT
List the reasons for a prevailing universal networked paradigm, which is IoT
Compare and correlate IoT with its precursors such as WSN, M2M, and CPS
List the various enablers of IoT
Understand IoT networking components and various networking topologies
Recognize the unique features of IoT which set it apart from other similar paradigms
Introduction
The modern-day advent of network-connected devices has given rise to the popular paradigm of the Internet of Things (IoT). Each second, the present-day Internet allows massively heterogeneous traffic through it. This network traffic consists of images, videos, music, speech, text, numbers, binary codes, machine status, banking messages, data from sensors and actuators, healthcare data, data from vehicles, home automation system status and control messages, military communications, and many more. This huge variety of data is generated from a massive number of connected devices, which may be directly connected to the Internet or connected through gateway devices. According to statistics fromthe Information Handling Services [7], the total number of connected devices globally is estimated to be around 25 billion. This figure is projected to triple within a short span of 5 years by the year 2025. Figure 4.1 shows the global trend and projection for connected devices worldwide.
The traffic flowing through the Internet can be attributed to legacy systems as well as modern-day systems. The miniaturization of electronics and the cheap affordability of technology is resulting in a surge of connected devices, which in turn is leading to an explosion of traffic flowing through the Internet.
Points to ponder
“The Internet of Things (IoT) is the network of physical objects that contain embedded technology to communicate and sense or interact with their internal states or the external environment.“
—Gartner Research [5]One of the best examples of this explosion is the evolution of smartphones. In the late 1990’s, cellular technology was still expensive and which could be afforded only by a select few. Moreover, these particular devices had only the basic features of voice calling, text messaging, and sharing of low-quality multimedia.
Contents
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Book:
- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp vii-xvi
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3 - Predecessors of IoT
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 48-72
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Summary
Learning Outcomes
After reading this chapter, the reader will be able to:
Interpret the foundation of IoT
List the basic terminologies and technologies associated with wireless sensor networks (WSN)
List the basic terminologies and technologies associated with machine-to-machine communications (M2M)
List the basic terminologies and technologies associated with cyber-physical systems (CPS)
Differentiate between WSN, M2M, and CPS
Relate new concepts with concepts learned before to make a smooth transition to IoT
Introduction
Before delving into the details of the Internet of Things (IoT), a discussion on the base technologies, which make up the crux of IoT, is required. A majority of these technologies, before the IoT era, were used separately for sensing, decision making, and automation tasks. The range of application domains of these technologies extended from regular domains like healthcare, agriculture, home monitoring, and others to specialized domains such as military and mining. Some of these precursor technologies still being used and often re-engineered for IoT are wireless sensor networks (WSN), machine-to-machine (M2M) communications, and cyber physical systems (CPS). All of these precursor paradigms have their distinct signatures and application scopes. A basic overview of these precursor technologies is covered in the subsequent sections in this chapter.
Wireless Sensor Networks
Wireless sensor networks (WSN), as the name suggests, is a networking paradigm that makes use of spatially distributed sensors for gathering information concerning the immediate environment of the sensors and collecting the information centrally. Here, the sensors are not standalone devices but a combination of sensors, processors, and radio units—referred to as sensor nodes—sensing the environment and communicating the sensed data wirelessly to a remote location, which may or may not be connected to a backbone network. Figure 3.1 shows the block diagram of the various standard components of a typical WSN node [4]. The exact specifications of each of these blocks vary depending on the implementation requirements and the network architect's choice.
Figure 3.2 shows a typical WSN implementation, where the master node aggregates data from multiple slave nodes, forwards it to a remote server utilizing access to the Internet through cellular connectivity. The stored data on the server can be visualized by a user or a subscriber to the system from anywhere in the world over the Internet. WSNs mainly follow a system of communication known as master–slave architecture.
5 - IoT Sensing and Actuation
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 97-114
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Summary
Learning Outcomes
After reading this chapter, the reader will be able to:
List the salient features of transducers
Differentiate between sensors and actuators
Characterize sensors and distinguish between types of sensors
List the multi-faceted considerations associated with sensing
Characterize actuators and distinguish between types of actuators
List the multi-faceted considerations associated with actuation
Introduction
A major chunk of IoT applications involves sensing in one form or the other. Almost all the applications in IoT—be it a consumer IoT, an industrial IoT, or just plain hobby-based deployments of IoT solutions—sensing forms the first step. Incidentally, actuation forms the final step in the whole operation of IoT application deployment in a majority of scenarios. The basic science of sensing and actuation is based on the process of transduction. Transduction is the process of energy conversion from one form to another. A transducer is a physical means of enabling transduction. Transducers take energy in any form (for which it is designed)—electrical, mechanical, chemical, light, sound, and others—and convert it into another, which may be electrical, mechanical, chemical, light, sound, and others. Sensors and actuators are deemed as transducers. For example, in a public announcement (PA) system, a microphone (input device) converts sound waves into electrical signals, which is amplified by an amplifier system (a process). Finally, a loudspeaker (output device) outputs this into audible sounds by converting the amplified electrical signals back into sound waves. Table 5.1 outlines the basic terminological differences between transducers, sensors, and actuators.
Sensors
Sensors are devices that can measure, or quantify, or respond to the ambient changes in their environment or within the intended zone of their deployment. They generate responses to external stimuli or physical phenomenon through characterization of the input functions (which are these external stimuli) and their conversion into typically electrical signals. For example, heat is converted to electrical signals in a temperature sensor, or atmospheric pressure is converted to electrical signals in a barometer. A sensor is only sensitive to the measured property (e.g., a temperature sensor only senses the ambient temperature of a room). It is insensitive to any other property besides what it is designed to detect (e.g., a temperature sensor does not bother about light or pressure while sensing the temperature).
PART FIVE - IOT HANDS-ON
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 319-320
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10 - Cloud Computing
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 237-255
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Summary
Learning Outcomes
After reading this chapter, the reader will be able to:
Understand the concept of cloud computing and its features
Understand virtualization, different cloud models, and service-level agreements (SLAs)
Identify the salient features of various cloud computing models
Understand the concept of sensor-clouds
Introduction
Sensor nodes are the key components of Internet of Things (IoT). These nodes are resource-constrained in terms of storage, processing, and energy. Moreover, in IoT, the devices are connected and communicate with one another by sharing the sensed and processed data. Handling the enormous data generated by this large number of heterogeneous devices is a non-trivial task. Consequently, cloud computing becomes an essential building block of the IoT architecture. This chapter aims at providing an extensive overview of cloud computing. Additionally, Check yourself will help the learner to learn different concepts are related to cloud computing.
Cloud computing is more than traditional network computing. Unlike network computing, cloud computing comprises a pool of multiple resources such as servers, storage, and network from single/multiple organizations. These resources are allocated to the end users as per requirement, on a payment basis. In cloud computing architecture, an end user can request for customized resources such as storage space, RAM, operating systems, and other software to a cloud service provider (CSP) as shown in Figure 10.1. For example, a user can request for a Linux operating system for running an application from a CSP; another end user can request for Windows 10 operating system from the same CSP for executing some application. The cloud services are accessible from anywhere and at any time by an authorized user through Internet connectivity.
Points to ponder
Gmail, Facebook, and Twitter are examples of cloud computing applications.
Currently, many companies such as Amazon Web Service and Microsoft Azure provide cloud services.
Cloud computing comprises a shared pool of computing resources, which are accessible dynamically, ubiquitously, and on-demand basis by the users. This shared pool of resources includes networks, storage, processor, and servers. These resources are accessible by multiple users through a regular command-line terminal at the same or different time instants. The services of cloud computing are based on the pay-per-use model. The concept is the same as paying utility bills based on consumption. In cloud computing, a user pays for the cloud services as per the duration of their resource usage.
11 - Fog Computing and Its Applications
- Sudip Misra, Anandarup Mukherjee, Arijit Roy
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- Introduction to IoT
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- 09 January 2021
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- 15 April 2021, pp 256-268
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Summary
Learning Outcomes
After reading this chapter, the reader will be able to:
Understand the concept of Fog computing and its features
List the salient features of a Fog computing architecture
Identify the requirements of a Fog computing architecture
Understand the importance of Fog computing through real-life use cases and identify its application scope in IoT
Introduction
In the Internet of Things (IoT), billions of Things connect through wired or wireless connectivity. These Things or devices produce a huge volume of data, which are typically transmitted to the cloud for analysis. Sometimes, the process of transmitting the data to the cloud and analyzing the data may consume a significant amount of time, which is undesirable for time-critical applications, such as healthcare. Therefore, providing real-time services is a major challenge in cloud computing. The concept of Fog computing was introduced considering the high latencies involved in cloud computing. This chapter aims to provide an insight into the fog computing architecture and how it reduces the latency of data processing and transmission.
In the IoT architecture, physical devices transmit data to the cloud. After specific processing of these data, service is provided to the end user applications. Fog computing follows a distributed architecture, which enables processes to execute near the edge of the devices to avoid service latency. A fog layer is an intermediate layer between the physical IoT devices and the cloud. The term, fog computing, was coined by Cisco.
In Figure 11.1, we depict the difference between the basic architecture of cloud and fog computing. In traditional cloud architecture, all data from the devices are transmitted to the cloud directly and then, processed in order to receive the final end user services. These end user services may be in the form of results of analytics, visualizations, and other such processed information. In fog computing architecture, time-sensitive data from different devices are transmitted to the fog devices at the fog layer. Further, data are processed to serve an end user application. Moreover, based on the requirements, the data are transmitted to the cloud layer for long-term storage.
Essential characteristics in fog computing
A fog computing platform resides between cloud and physical IoT devices; it provides processing, storage, and networking services.