The IoT connection is the enabling technology that powers IoT but it’s the communication of the IoT device via the internet that really enables an IoT solution to create value. Communication between the IoT device and IoT gateway and onward into the cloud makes it possible to perform data processing, analytics and storage. IoT bridges both telecoms and IT protocols and several IoT-specific protocols have emerged to help standardize and streamline IoT communication processes.
The role of an IoT gateway is important here because it acts as an aggregator of data from connected IoT devices which can then communicate onwards to the cloud. The IoT gateway is a device that connects IoT endpoints, equipment systems, sensors and cloud resources. An IoT gateway can be an item of hardware or a virtual device and in either case is a fundamental enabler of IoT communication.
Cloud and IoT go hand-in-hand because cloud resources enable IoT organizations to process data from the IoT device to IT systems and then also communicate data from the cloud to the IoT device. This necessity for two-way communications is a vital enabler of IoT benefits, especially for applications that are continually adjusting and need inputs from a centralized administrator – whether automated or human.
Communications protocols used in IoT deployments include Lightweight M2M (Machine-to-Machine) which is a device management protocol designed for sensor networks and the device volumes associated with M2M environments. Machine Type Communications (MTC) and massive Machine Type Communications (mMTC) also cater for this high device volume end of the IoT market and allow fully automated data generation, exchange, processing and actuation among intelligent machines, with low or no human intervention.
Typically, the protocols utilized in IoT comprise low power and low processing burdens which fit with the requirements of sensor devices and devices such as smart meters that have long lifecycles. However, as greater complexity becomes a requirement for more sophisticated IoT use cases, protocols that demand more processing power and greater power consumption are set to be adopted. Advanced message queuing protocol (AMQP) is one example of an IoT protocol for receiving and placing messages in queues and setting up a relationship between components. However, it is not suitable for IoT devices that have limited memory.
Another example is data distribution service (DDS) which is a scalable IoT protocol that enables high-quality IoT communication. In comparison to IoT DDS allows for interoperable data exchange independently of a hardware and software platform. However, there are many options for communication and data protocols in IoT. Which of these are selected will be dependent on the application and use case.
In common with the connectivity selected for a use case, the IoT communications protocol stack offers options for all levels of IoT requirements and is maturing rapidly. An important aspect of this maturity is to bridge the differences between connectivity, internet and data protocols. This enables improved communications between all the systems involved and also prepares the architecture for additional cloud-based and virtualized functions including artificial intelligence, machine learning and greater reliance on open source systems in future.
AMQP is an open standard application layer protocol used for transactional messages between servers. Main functions include receiving and placing messages in queues, storing messages and setting up a relationship between components. It is not suitable for IoT sensor devices with limited memory.
DDS is a scalable IoT protocol that enables high-quality communication in IoT. Similar to the MQTT, DDS also works to a publisher-subscriber model. In contrast to MQTT, DDS allows for interoperable data exchange independent of the hardware and the software platform.
CoAp is an application layer protocol that has been designed to address the needs of HTTP-based IoT systems. HTTP is foundation of data communication for the World Wide Web but, while it is freely available and usable by any IoT device, it can consume too much power for IoT applications. CoAp has addressed this limitation by translating the HTTP model into usage in restrictive devices and network environments.
A device management protocol designed for sensor networks and the demands of a machine-to-machine (M2M) environment.
A serial communications protocol for use with programmable logic controllers (PLCs) that is used to connect industrial electronic devices.
A protocol designed to connect the physical devices and networks with applications and middleware, making it an ideal connectivity protocol for IoT and M2M.
A descriptive term for fully automatic data generation, exchange, processing and actuation among intelligent machines, with low or no intervention by humans.
The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition and decision-making. AI also enables machines to learn from experience.
A part of computer science working to enable computers to see, identify and process images in a manner similar to human vision.
A machine learning technique that teaches computers to learn by example.
Machine learning is a method of data analysis that automates construction of analytical models, based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.
A computer system modelled on the human brain and nervous system that is designed to help machines reason more like humans.
A set of routine definitions, protocols, and tools for building software and applications. An API connects your business processes, services, content, and data to channel partners, internal teams, and independent developers in an easy and secure way. APIs are becoming the de facto standard by which companies exchange data and build consistent cross-channel customer experiences.
A gateway that translates communications between telecommunications and computer networks (most often the Internet).
Internet-based computing that allows for data access from distinct computers or devices. Typically referred to as though the ‘cloud’ itself is storing the data, but data is stored on physical computers that allow access at any time to the data via the Internet.
A model in which computation is largely or completely performed on distributed device nodes known as smart devices or edge devices as opposed to taking place in a centralised cloud environment.
A specific class of computer software that provides the low-level control for the device’s specific hardware. FOTA refers to the capability of upgrading firmware over-the-air.
Also known as edge computing or fogging, Fog computing is a term created by Cisco that refers to extending cloud computing to the edge of an enterprise’s network.
A type of dataflow programming in which programme steps communicate with each other by transmitting data through some kind of channel. The channels are managed by the larger system, leaving the connected components free to focus on processing input and producing output.
A cloud computing environment that uses a mix of on-premise, private cloud and third-party, public cloud services with orchestration between the two platforms.
OTA provisioning refers to various methods of distributing new software, configuration settings, and even updating encryption keys to devices of sorts.
Describes software for which the original source code is freely available and can be redistributed or modified.
Peer-to-peer computing or networking is a distributed application architecture that partitions tasks or workloads between peers. Peers are equally privileged, equipotent participants in the application.
Also referred to as a RESTful web service a RESTful API is based on representational state transfer (REST) technology, an architectural style and approach to communications often used in web services development.
Simple Object Access Protocol (SOAP) is a communication protocol for the exchange of information between various operational systems using Extensible Markup Language (XML).
Amounts of data that are so large that traditional technologies cannot handle their transfer or analysis. Certain IoT technologies specialize in handling and transferring big data as it is seen as key to large companies’ goal to maximize efficiency.
A growing list of records, called blocks, which are linked using cryptography. For use as a distributed ledger, a blockchain is typically managed by a peer-to-peer network collectively adhering to a protocol for inter-node communication and validating new blocks.
Describes a wide range of strategies for refining data sets so they provide what a user, or set of users, needs without including other data that can be repetitive, irrelevant or even sensitive.
A data janitor is a person who takes large amounts of big data and condenses it into information that businesses can act upon.
An approach to business governance that values decisions that can be backed up with verifiable data.
An open source distributed processing framework that manages data processing and storage for big data applications running in clustered systems.
Pervasive computing, also called ubiquitous computing
The embedding of computational capability into everyday objects to make them effectively communicate and perform useful tasks in a way that minimizes the end user’s need to interact with computers.
A computer system for gathering, analyzing and controlling real-time data.
The Internet Protocol suite is the computer networking model and set of communications protocols used on the Internet and similar computer networks.