Nowadays, the internet has become a very important part of our life. Today, the internet is everywhere, it has touched almost every corner of the world. It has also affected human life in many ways. We are entering an era of the "Internet of Things". so to develop an IoT application Architecture is one of the important things that need to follow.

Architecture of IoT

The Internet of things provides a new world where almost all devices are connected to a network. IoT is not a single technology, it is a combination of various technologies that work together in this era. We can use them collaboratively to achieve difficult tasks that require a high degree of intelligence. For this Intelligence, IoT devices are equipped with embedded sensors, actuators, processors, and transceivers.

Three and Five Layer Architecture

This architecture was introduced in the early days of this area. It has 3 layers:-
  1. Perception Layer
  2. Network layer
  3. Application layer

  • The perception layer is the physical layer, It has sensors for sensing and collecting information about the environment. It senses physical parameters and recounts other smart objects in the environment. 
  • The main work of the network layer is to connect to other smart things, network devices, and servers. This larger is also used for transmitting and processing sensor data 
  • The application layer is used for delivering application-specific services to the user and explains different applications in which the IoT can be deployed. for eg: sm homes, smart health, and smart cities.
Architecture of IoT - 3 layer and 5 layer architecture

Fig. Architecture of IoT 

The 3-layer architecture is not enough for research on IoT because research focuses on the aspects of IoT. So researchers have explained the five-layer architecture, This architecture includes the processing and business layer. The five layers are perception, transport, processing, application, and business layer. The work of the perception and application layer remains the same as the 3-layer architecture. The role of the transport layer is to transfer the sensor data from the perception layer to the processing layer and vice versa, through networks such as wireless, LAN, Bluetooth, RFID, and 3G NFC. The processing layer is the middleware layer. It stores, analyze, and process the huge data that comes from the transport layer. It can also provide various sets of services to the lower layers. This layer is also used for many technologies such as databases, cloud computing, and big data processing modules. The next business layer is used to manage the whole IoT system including applications, business and profit models, and user privacy.

Seven Layer Architecture

In the seven-layer architecture, the topmost layer is "The Things'. In the IoT environment, the ecosystem has many devices. Devices, sensors, and controllers that enable their interconnection. So endpoint of an IoT system must have connected devices - besides standard sensors, the actuators also include smartphones, micro-controllers, computers, etc.

architecture of iot - seven layer

Fig. Seven Layer

The second layer is Connectivity/Edge. The working of connectivity/Edge is to represent the environment and the place where all connections are made before the exchange of data within the IoT ecosystem. It provides all communication protocols and establishes a network for Edge computing. So this layer determines that this is a distributed architecture and data are processed on the edge of the network. 
The 'Global Infrastructure', the third layer depends on cloud infrastructure. This is because most IoT solutions rely on the integration of cloud services. Observed from the business. Today in the business scenario, this is the necessary component-time because the cloud provides a complete upgrade to the customer's perspective. 

The fourth layer, the data ingestion, is the data entry layer. This layer is used for Big Data, as well as the cleansing and data storing. This layer is also used for, data streaming processes as a building element of data ingestion. 

The fifth layer is data analysis. This layer belongs to the processing of data in order to prepare the report, data mining, the implementation of machine learning, etc.

The sixth layer i.e. application layer is where user applications are stored depending on objects from the lowest layer of architecture takes place. This layer is also c application integration layer where the same layer can be viewed as a service with the implementation of the UI at the top. 

The seventh layer is people and processes, This includes all business entities consortium of IoT ecosystems and, at the same time, the actors involved in decision making on the basis of data obtained from the IoT ecosystem, with the help of the structures that were previously mentioned in architecture. 

Cloud and Fog based Architecture

In some system architecture, the data processing is done in a large centralized system by cloud computers, Cloud-centric architecture helps the cloud at the center's applications above it and the network of smart things below it. Cloud computing offers the services like core infrastructure, platform, software, and storage. It also provides flexibility and scalability. Developer can provide their storage tools, software, data mining and machine learning tools, and visualization tools through the cloud. 

In the real system, the need for data analysis especially in Smart-Grid environments, and also monitoring and pre-processing in the local IoT environment, so introduce a new layer between the physical layer and the transport or gateway layer i.e. fog layer. The fog layer is an extension of cloud and network services to solve this gap in the IoT cluster. That's why the fog layer is logical, that's similar to Cloud, and the fog is directed at the end-user and complements the possibilities of storing data as well as more efficient processing with the use of application services. Therefore, security and privacy are essential building blocks that greatly contribute in particular to the process of attack analysis and situations where the danger is marked in the system as a man-in-the-middle. 

architecture of iot - cloud and fog based architecture

Fig. Cloud and Fog based Architecture

Fog architecture can have more advantages. One of the most important is optimization, i.e. reduced need for information flow in the getaway-cloud relationship and the second most important advantage is the fog layer can have direct communication with another fog and thus create a mesh that avoids the use of cloud resources which in some cases of specific IoT solutions can have advantages and contribute to efficiency. 

Edge Computing IoT Architecture

The aim of Edge computing is closely associated with Fog computing. The main goal of Edge is that the data processing and functional processing capabilities are redirected to the edge elements of the network environment within the IoT ecosystem.) Inside the Edge environment, all data processing takes place on the physical perception layer itself, or directly on a smart device or on an IoT device collector. All these edges within the Edge can be performed independently on their own layer or in combination with other fog or edge layers from the surroundings of the IoT ecosystem. Edge allows a greater level of localized latency reduction than any previous one. This is also facilitated by the potential decentralized connection of the IoT ecosystem elements in a global environment. At the same time, the privacy of data is protected by the system and users and globally increases the security of the IoT ecosystem. 

Hybrid IoT Architecture 

Depending on the project requirement, the architecture of the IoT system can also be constituted as a mixture of Cloud-Fog-Edge. This is particularly advantageous in the context of challenging business goals where it is difficult to meet customer requirements for some of the standard architectures. This combination, i.e. Hybridization is usually called nested.

Architecture of IoT - Hybrid IoT architecture
Fig. Hybrid IoT Architecture

Edge computing layer: It performs observation and recording of user interactions and forwards the feed to the Fog node. From the real-time control signals from the Fog Nodes, the intelligence of the operation is performed directly at the node level.

Fog computing layer: All current data is stored in temporary memory. The control and analytics required to run in real-time are based on the application core rules from the cloud. 

Cloud computing layer: It performs aggregation of data from all Fog nodes and performs analytical processes on large datasets. In addition, it has task forwarding rules for application execution of Fog Nodes.