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Iot architecture

A brief description of some standard IoT Architectures

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Iot architecture

  1. 1. Presented by: Anam Iqbal PhD Scholar Department of CSE NIT, Srinagar
  2. 2. “A global infrastructure of the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies.” “The internet of things in the internetworking of physical devices, vehicles, building, and other items – embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data.” IoT
  3. 3. FEATURES OF IoT  Fundamental features of a sustainable IoT architecture include  Artificial Intelligence: IoT makes virtually anything “smart”. Knowledge can be extracted from generated data.  Interconnectivity: Anything can be interconnected, any time and anywhere using a communication infrastructure.  Distributivity: Data is gathered from different sources and processed by several entities in a distributed manner.  Heterogeneity: The devices in IoT are heterogeneous as based on different hardware platforms.  Interoperability: Devices from different vendors cooperate, in order to achieve common goals. Also, systems and protocols will have to be designed in a way that allows objects (devices) from different manufacturers to exchange data and work in an interoperable way.  Scalability: The number of devices that need to be managed and that communicate with each other is of a great magnitude.  Security: Users feelings of helplessness and being under some unknown external control could seriously hinder IoT's deployment.  Dynamic changes: The state of devices change dynamically, eg sleeping or waking up, connected or disconnected, as well as context of devices including location and speed. The number of devices can also change dynamically.  Everything as a service: All resources are consumed as services.  Without addressing these conditions, the result of the IoT architecture is a failure.
  4. 4. BASIC ARCHITECTURE Figure 1: Basic Architecture of IoT
  5. 5. SENSOR NETWORK: • Consists of sensing nodes (sensors) communicating in a wireless multi-hop fashion for gathering data. • Sensor network can exist without IoT, but IoT cannot exist without a senor network. • Sensors provide information, knowledge, or data about the Physical Entity (the identity of the Physical Entity and state of the Physical Entity) they monitor. • A sensor can measure the physical property and convert it into signal that can be understood by an instrument. • The sensors enable the interconnection of the physical and digital worlds allowing real-time information to be collected and processed. HARDWARE Wireless Sensor Networks (WSN) and radio frequency identification (RFID) are considered as the two main building blocks of sensing and communication technologies for IoT. Figure 2: Sensor Network
  6. 6. Virtual Sensors: • The data acquired by a set of sensors can be collected, processed according to an application-provided aggregation function, and then perceived as the reading of a single virtual sensor. Figure 3: Flow of information between real devices and virtual sensors • There are various types of sensors for different purposes. • Typical sensors could detect light, acceleration, air quality, movement, temperature, their location or humidity. • Current research is investigating new small sensors to analyze even liquids or gases. • The miniaturization of hardware has enabled powerful sensors to be produced in much smaller forms which are integrated into objects in the physical world. • E.g: miniaturised gas chromatography system for detecting volatile organic compounds developed at the Institute for Microsensors, -actuators and systems (IMSAS) at the University of Bremen. • Location-sensing techniques like triangulation, proximity or scene analysis can be combined with different transmitting technologies based on radio, infrared light, magnetism, ultrasound or vision for designing location-aware objects.
  7. 7. • A virtual sensor may not have any real sensor’s physical properties such as manufacturer or battery power information, but does have other properties, such as: who created it; what methods are used, and what original sensors it is based on. • Two degrees of complexity: • The combination of a limited number of related sensors or measurements to derive new virtual data (usually done at the sensor node or gateway level). • The complex process of deriving virtual information from a huge space of sensed data (generally at the application level). • Valuable higher-level knowledge is being derived from lower-level events and can be approached using different technologies from many independent research fields (such as, discrete event simulation active databases, network management, or temporal reasoning), Figure 4: Different levels for sensor virtualization.
  8. 8. GATEWAY • A gateway is a hardware device that acts as a "gate" between two networks. It may be a router, firewall, server, or other device that enables traffic to flow in and out of the network. • Gateway is also a node itself. • The gateway node is considered to be on the "edge" of the network as all data must flow through it before coming in or going out of the network. • Traditional network gateways have mostly performed protocol translation and device management functions. • They are not intelligent, programmable devices that could perform in-depth and complex processing on IoT data. • Today's "smart" IoT gateways -- delivered by companies such as Dell Technologies, Wind River/Intel, Nexcom and others -- are full-fledged computing platforms running modern operating systems (for example, Linux or Windows). • These systems are sometimes also called intelligent gateways or edge gateways. • The advantages of having a fully programmable and manageable platform closer to the IoT devices they support is immense: • Trusted connectivity and security -- ensuring the integrity of the network and system in both directions • Protocol and data bridge -- being able to translate and transfer data among and between systems operating with different communications protocols and data formats, often requiring bidirectional communication capabilities • Storage and analysis -- onboard application development platforms and storage to drive intelligence and decision-making closer to the edge device • Management -- the ability to provision, update and control access of connected devices to the system as well as policy-based permissions
  9. 9. 1. Singular: This type of virtual sensor provides one to one mapping so that a single physical sensor can be virtualized, shared among multiple applications. 2. Accumulator: It provides many to many mapping. 3. Aggregator: The function of Aggregator is to act on top of physical sensors, to read and do the simple computations like averaging, finding maximum and minimum, sorting, counting as per application need. 4. Selector: It can select a single value from a group of values, based on specific criteria. 5. Qualifier: It is categorized to work on events based on priority. A Qualifier will be activated if a threshold for a single observable quantity is breached. It checks the highest or lowest value from a group of observed sensor data. 6. Context-Qualifier: Virtual sensor designed for prioritizing events when threshold levels of multiple variables are breached at same time. It is a typical example of many to one mapping, where multiple physical sensors are grouped and monitored together to alert a SaaS level application. 7. Predictor and Compute: Physical sensors are unable to detect the events in priory. It may detect the occurrence of a present event, but not the future event. A virtual sensor like predictor can be deployed to guess the occurrence of event in future, which may provide sophisticated solution to patient monitoring like averting cardiac arrest. Also when decision making is involved in such scenarios, compute virtual sensor can be used. TYPES OF VIRTUAL SENSORS BASED ON THE SERVICES OFFERED
  10. 10. List of some of the measurement devices used in IoT: Accelerometers Temperature sensors Magnetometers Proximity sensors Gyroscopes Acoustic sensors Light sensors Pressure sensors Gas RFID sensors Humidity sensors Micro flow sensors Image sensors COMMUNICATION: 1. CHALLENGES a) Addressing and identification: Things need to be identified through a unique address, on the basis of which they communicate with each other. For this, we need a large addressing space, and a unique address for each smart object. b) Low power communication: Communication of data between devices is a power consuming task, specially, wireless communication. Therefore, we need a solution that facilitates communication with low power consumption. c) Routing protocols with low memory requirement and efficient communication patterns. d) High speed and nonlossy communication. e) Mobility of smart things.
  11. 11. 2. ENABLING TECHNOLOGIES FOR COMMUNICATION: 1. RFID (radio-frequency identification): • Used for short range low power communication. • To identify and track the data of the things. • It allows the design of tiny microchips (called tags),which can be appended to an object of our daily life. • Stored data in these tags can automatically be used to identify and extract useful information from the object. • Tag acts as an electronic barcode. 2. Sensor: • To collect and process the data to detect the changes in the physical status of things. 3. Smart Tech: • To enhance the power of the network by devolving processing capabilities to different parts of the network. 4. Nano Tech: • To make the smaller devices have the ability to connect and interact.
  12. 12. C) Short Range: •Direct connection between devices – sensor networks •Typical low power usage. •Examples: Bluetooth, Zigbee, Z-wave, •Broadcast systems D) Other examples: • Satellite systems 3. WIRELESS TECHNOLOGIES: B) WLAN •Initial service: Wireless Ethernet extension •Moderate coverage per access point (10’s –100 meters) •Moderate/high data rate (100’s Mbits/s) •Examples: IEEE 802.11(a-g), Wimax A) Telecommunication systems • Initial/primary service: mobile voice telephony • Large coverage per access point (100’s of meters –10’s of kilometers) • Low/moderate data rate (10’s of Kbit/s –10’s of Mbits/s) • Examples: GSM, UMTS, LTE
  13. 13.  IEEE 802.15.4 has developed a low-cost, low-power consumption, low complexity, low to medium range communication standard at the link and the physical layers for resource constrained devices.  Bluetooth low energy (Bluetooth LE, is the ultra-lowpower version of the Bluetooth technology that is up to 15 times more efficient than Bluetooth.  Ultra-Wide Bandwidth (UWB) Technology is an emerging technology in the IoT domain that transmits signals across a much larger frequency range than conventional systems. UWB, in addition to its communication capabilities, it can allow for high precision ranging of devices in IoT applications.  RFID/NFC proposes a variety of standards to offer contact less solutions. Proximity cards can only be read from less than 10 cm and follows the ISO 14443 standard and is also the basis of the NFC standard. RFID tags or vicinity tags dedicated to identification of objects have a reading distance which can reach 7 to 8 meters. • One of the essential challenges in IoT is how to interconnect “things” in an interoperable way while taking into account the energy constraints, knowing that the communication is the most energy consuming task on devices. • Several low power communication technologies have been proposed from different standardisation bodies. The most common ones are:
  14. 14. MIDDLEWARE: • Software layer that stands between the networked operating system and the application and provides well known reusable solutions to frequently encountered problems like heterogeneity, interoperability, security, dependability. • In charge of processing and managing the obtained raw data. • Provides an abstraction level to users and developers. • IoT requires stable and scalable middleware solutions to process the data coming from the networking layers. Challenges addressed by IoT Middleware: (1). Interoperability and programming abstractions: For facilitating collaboration and information exchange between heterogeneous devices, different types of things can interact with each other easily with the help of middleware services. Interoperability is of three types: network, semantic, and syntactic. Network interoperability deals with heterogeneous interface protocols for communication between devices. It insulates the applications from the intricacies of different protocols. Syntactic interoperability ensures that applications are oblivious of different formats, structures, and encoding of data. Semantic interoperability deals with abstracting the meaning of data within a particular domain. (2) Device discovery and management: This feature enables the devices to be aware of all other devices in the neighborhood and the services provided by them. Here the infrastructure is mostly dynamic. The devices have to announce their presence and the services they provide. Finally, any IoT middleware needs to perform load balancing, manage devices based on their services, capabilities and levels of battery . SOFTWARE:
  15. 15. 3) Scalability: Middleware makes the required changes when the infrastructure scales, as a large number of devices are expected to communicate in an IoT setup. (4) Big data and analytics: IoT sensors typically collect a huge amount of data. It is necessary to analyze all of this data in great detail. As a result a lot of big data algorithms are used to analyze IoT data. (5) Security and privacy: The middleware has built-in mechanisms to address security and privacy issues, as the IoT applications are mostly related to someone’s personal life or an industry. The middleware should have built-in mechanisms to address such issues, along with user authentication, and the implementation of access control. (6) Cloud services: The cloud is an important part of an IoT deployment. Most of the sensor data is analyzed and stored in a centralized cloud. It is necessary for IoT middleware to seamlessly run on different types of clouds and to enable users to leverage the cloud to get better insights from the data collected by the sensors. (7) Context detection: The data collected from the sensors needs to be used to extract the context by applying various types of algorithms. The context can subsequently be used for providing sophisticated services to users.
  16. 16. (3) Database oriented: •In this approach, the network of IoT devices is considered as a virtual relational database system. •The database can then be queried by the applications using a query language. (4) Semantic: •Semantic middleware focuses on the interoperation of different types of devices, which communicate using different formats of data. It incorporates devices with different data formats and ties all of them together in a common framework. •The framework is used for exchanging data between diverse types of devices. •This technique allows multiple physical resources to communicate even though they do not implement or understand the same protocols. (5) Application specific: •This type of middleware is used specifically for an application domain for which it is developed because the whole architecture of this middleware software is fine-tuned on the basis of requirements of the application. •The application and middleware are tightly coupled. Middlewares can be classified as follows on the basis of their design; (1) Event based: •All the components interact with each other through events. •Each event has a type and some parameters. •Events are generated by producers and received by the consumers. (2) Service oriented: •Is based on Service Oriented Architectures (SOA), and have independent modules that provide services through accessible interfaces. •A service oriented middleware views resources as service providers. •Service oriented middleware must have runtime support for advertising services by providers and support for discovering and using services by consumers. e.g HYDRA
  17. 17. • Applications are the interface to the Internet of Things and provide tools for data-entry and retrieval, analysis, planning, forecasting and more. • This part of the software layer constitutes the front end of the whole IoT architecture through which IoT potential will be exploited. • It provides the required tools (e.g. actuating devices) for developers to realize the IoT vision. In this vision, the range of possible applications is impressive. APPLICATIONS:
  18. 18. A NETWORK ENGINEER’S VIEW vs DESIGNER’S VIEW OF IoT Engineer’s look at IoT Stack as a protocol map. Figure 5: A network engineer’s view of IoT Figure 6: A designer’s view of IoT Designers look at IoT tech as a front end and back end with enabling infrastructure in between.
  19. 19. The client side. A pathway for connecting clients and operators. Operators on the server side Figure 7: Three layer IoT Architecture THREE LAYER ARCHITECTURE
  20. 20. • Includes objects to be detected (from physical moving objects, such as humans, cars, ) or factors to be observed ( temperature, or humidity) . • Includes sensors, other hardware such as; embedded systems, RFID tags and readers and others. 1. PERCEPTION LAYER: • The network layer is responsible for processing the received data from the Perception Layer. • It is in charge of transmitting data to the application layer through various network technologies, such as wireless/wired networks and Local Area Networks (LAN). • The main media for transmission include 3G, 4G, Wifi, bluetooth, Zigbee, UMB, infrared technology, and so on. • Huge quantities of data will be carried by the network. • Crucial to provide a sound middleware to store and process this massive amount of data. 2. NETWORK LAYER 3. APPLICATION LAYER • It is the layer at the top of the architecture and is responsible for delivery of various applications to different users in IoT. • It realizes the use of smart objects by a set of functions to users to meet defined requirements. • The applications can be from different industry segments such as: manufacturing, logistics, retail, environment, public safety, healthcare, food and drug etc. • With the increasing maturity of RFID technology, numerous applications are evolving which will be under the umbrella of IoT.
  21. 21. Figure 8: The 4 stag IoT Solutions Architecture Device Data Procesing and platform Edge Thing/Devic e/Cloud
  22. 22. Stage 1: Networked Things (Wireless sensors and actuators) Sensors convert information obtained in outer world into data for analysis. Actuators can intervene the physical reality, e.g switching off lights Stage 2: Sensor data aggregation systems and analog- to-digital data conversion This stage makes data both digitalized and aggregated. Enormous amount of information collected on previous stage is processed and squeezed into optimal size for further analysis. Stage 3: The appearance of edge IT systems The prepared data is transferred to the IT world. So basically the analytics and pre-processing of data is done . Also some additional processing might happen here , prior to the stage of entering the data center. Stage 4: Analysis, management, and storage of data The main processed on the last stage of IoT happen in the data center or cloud. It enables in-depth processing, along with a follow-up revision for feedback. Data from other sources might also be included to ensure the in-depth analysis.
  23. 23. REFERENCE ARCHITECTURE  This architecture comprises of service layers and presentation layers.  Service layers include Event Processing and Analytics, Resource Management and Service Discovery, as well as Message Aggregation and Enterprise Service Bus (ESB) services built on top of communication and physical layers.  API management, which is essential for defining and sharing system services and web-based dashboards (or equivalent) for managing and accessing these APIs, are also included in the architecture.  Due to the importance of device management, security and privacy enforcement in different layers, and the ability to uniquely identify objects and control their access level, these components are pre-stressed independently in this architecture. Figure 9 : Reference Architecture for IoT
  24. 24. REFERENCE ARCHITECTURE CONTINUED Reference Architecture SOA based Architecture Sensing layer Network layer Service layer Interface layer API Oriented Architecture o Sensing layer is integrated with available hardware objects to sense the status of things. o Network layer is the infrastructure to support over wireless or wired connections among things. o Service layer is to create and manage services required by users or applications. o Interfaces layer consists of the interaction methods with users or applications. Web APIs and Representational State Transfer (REST)- based methods have been introduced as promising alternative solutions to RMI. This helps in using the communication channel and processing the power of devices more efficiently.
  25. 25. The IoT Layered Architecture Figure 10: IoT layered architecture
  26. 26. THE DETAILED IOT LAYERED ARCHITECTURE Figure 11: Detailed IoT layered architecture
  27. 27. Figure 12: The seven layer IoT Architecture THE SEVEN LAYER IOT ARCHITECTURE
  28. 28. IoT “devices” are capable of: • Analog to digital conversion, as required • Generating data • Being queried / controlled over-the-net 1. Physical Devices & Device Controllers (The “Things” in IoT) • Devices are diverse, and there are no rules about size, location, form factor, or origin. Some devices will be the size of a silicon chip. Some will be as large as vehicles. The IoT must support the entire range. 2. Connectivity (Communication & Processing Units) Connectivity includes: • Communicating with and between the Level 1 devices and the network. • Communication across the network. • Communicating with and between the Level 2 and low-level information processing occuring at Level 3. • Reliable delivery across the network(s). • Implementation of various protocols. • Switching and routing. • Translation between protocols. • Security at the network level.
  29. 29. 3. Edge (Fog) Computing (Data Element Analysis & Transformation) •The functions of Level 3 are driven by the need to convert network data flows into information that is suitable for storage and higher level processing at Level 4. Level 3 processing can encompass many examples, such as: o Evaluation: Evaluating data for criteria as to whether it should be processed at a higher level o Formatting: Reformatting data for consistent higher-level processing o Expanding/decoding: Handling cryptic data with additional context (such as the origin) o Distillation/reduction: Reducing and/or summarizing data to minimize the impact of data and traffic on the network and higher- level processing systems o Assessment: Determining whether data represents a threshold or alert; this could include redirecting data to additional destinations •Functions Include: o Data filtering, cleanup, aggregation o Packet content inspection o Combination of network and data level analytics o Thresholding o Event generation
  30. 30. 4. Data Accumulation (Storage): • Makes the network data usable by applications. • Converts data-in-motion to data-at-rest. • Converts format from network packets to database relational tables. • Achieves transition from ‘Event based’ to ‘Query based’ computing. • Dramatically reduces data through filtering and selective storing. 5. Data Abstraction (Aggregation & Access) • Abstracts the data interface for applications • Create schemas and views of data in the manner that applications want • Combines data from multiple sources, simplifying the application • Filtering, selecting, projecting, and reformatting the data to serve the client applications • Reconciles differences in data shape, format, semantics, access protocol, and security 6. Application (Reporting, Analytics, Control) 7. Collaboration & Processes (Involving people and business processes)

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