DDS Protocol Architecture basics | DDS Protocol in IoT

This page covers DDS Protocol architecture basics. DDS protocol uses brokerless architecture in IoT (Internet of Things). DDS stands for Data Distribution Service.

• It is an IoT protocol developed for M2M (Machine to Machine) Communication by OMG (Object Management Group).
• It enables data exchange via publish-subscribe methodology.
• DDS makes use of brokerless architecture unlike MQTT and CoAP protocols.
• It uses multicasting to bring high quality QoS to the applications.
• DDS protocol can be deployed from low footprint devices to cloud.

DDS Protocol Stack

DDS protocol stack
Figure-1: DDS Protocol Stack

DDS V1.2 API standard is language independent, OS and HW architecture independent. The figure-1 depicts DDS protocol stack. As shown there are two layers viz. DCPS and DLRL.

• DCPS (Data Centric Publish Subscribe) layer delivers information to subscribers. DCPS is a standard API for data centric, topic based, real time publish/subscribe layer.
• DLRL (Data Local Reconstruction Layer) provides interface to DCPS functionalities. This enables sharing of distributed data among devices which are IoT enabled. DLRL is standard API for creating object views out of collection of topics.

DDSI/RTPS V2.1 is a standard wire protocol which allows interoperability between different implementations of DDS standard.

DDS Architecture working operation

DDS Protocol Architecture
Figure-2: DDS Protocol Architecture

The figure-2 depicts DDS protocol architecture.

DDS is a fully distributed GDS (Global Data Space). GDS specifications make it fully distributed in order to avoid introduction of single point of failure or bottleneck.

• In DDS protocol architecture, applications can autonomously and asynchronously read/write data in GDS.
• The publishers and subscribers can join or leave the GDS at any point in time. This is because they are dynamically discovered.
• Publishers and subscribers express their intention to produce or consume specific type of data such as topics.
• The subscriptions are matched taking into account topics with details such as (name, data type, QoS).
• Subscriptions are dynamically matched. Moreover data flows from publisher to the subscribers.


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