The Role of Data Centricity in Smart , Connected Systems
DDS decouples data from the application , which enables the real-time , scalable data exchange within complex , high-performing systems . Unlike traditional client-server architectures , DDS provides direct access to structured data and fosters real-time decision-making . This makes DDS particularly well suited for industry applications where low and stable latency , high throughput , and deterministic performance are critical . Examples include unmanned aerial vehicles , connected surgical devices , intelligent robots , power generation & distribution , and industrial IoT . This approach eliminates the need for point-to-point connections , reducing communication overhead and enabling systems to scale dynamically .
Additionally , DDS includes advanced features such as multicast communication , which optimizes network bandwidth usage by delivering data to multiple Subscribers simultaneously . It also can easily implement redundancy , by arbitrating the gapless delivery of samples from multiple “ hot ” publishers . Delegating removes custom application logic to handle failover and failback , allowing data to get to the right place continually via DDS .
One of the defining advantages of DDS is its Quality of Service ( QoS ) abstraction . Setting QoS policies allows developers to fine-tune system behavior based on specific application requirements . Developers can configure data reliability , fault tolerance , and performance parameters , thereby ensuring that critical data is delivered on time and without loss , even under adverse network conditions .
QoS supports data-centric communication , where applications interact directly with structured data rather than relying on complex protocols or message parsing – this approach simplifies development , improves maintainability , and enhances real-time decision making . DDS also complies with other industry standards , fostering interoperability across platforms and devices , reducing vendor lock-in and slashing integration costs . Overall , DDS empowers businesses to build scalable , reliable , and future-ready systems in increasingly data-driven markets .
4 DDS : THE DATA-CENTRIC CONNECTIVITY STANDARD
DDS serves as the backbone to a data-centric architecture , ensuring that data remains the focal point in developing smart , autonomous systems . The data centricity enabled by DDS is achieved by introducing a Discovery process which works as follows : Nodes with a need to communicate will exchange their publisher / subscriber details at startup , then leverage those details to communicate via a highly-efficient , binary structure using the DDS Real-Time Publish Subscribe ( DDS-RTPS ) protocol . Inside the payload of that protocol is a Sample along with associated metadata , such as the send and receive timestamps , sequence number , length , retry statistics , failover details , and even coherency information .
Data centricity therefore provides capabilities that are impossible to achieve with opaque blob messaging systems . Through its QoS properties , the DDS framework can understand the complex filtered needs of multiple Subscribers . It can then deliver only the data that qualifies ( samples
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