Vanderbilt University

Reactive Stream Processing for Data-centric Publish/Subscribe

The Internet of Things (IoT) paradigm has given rise to a new class of applications wherein complex data analytics must be performed in real-time on large volumes of fast-moving, heterogeneous sensor-generated data. Such data streams are often unbounded and must be processed in a distributed and parallel manner to ensure timely processing and delivery to interested subscribers.

Publication Year: 
2015
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A Cloud-enabled Coordination Service for Internet-scale OMG DDS applications

The OMG Data Distribution Service (DDS), which is a standard specification for data-centric publish/subscribe communications, has shown promise for use in internet of things (IoT) applications because of its loosely coupled and scalable nature, and support for multiple QoS properties, such as reliable and real-time message delivery in dynamic environments.

Publication Year: 
2014
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Content-based Filtering Discovery Protocol (CFDP): Scalable and Efficient OMG DDS Discovery Protocol

The OMG Data Distribution Service (DDS) has been deployed in many mission-critical systems and increasingly in Internet of Things (IoT) applications since it supports a loosely-coupled, data-centric publish/subscribe paradigm with a rich set of quality-of-service (QoS) policies. Effective data communication between publishers and subscribers requires dynamic and reliable discovery of publisher/subscriber endpoints in the system, which DDS currently supports via a standardized approach called the Simple Discovery Protocol (SDP).

Publication Year: 
2014
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Scalable Reactive Stream Processing Using DDS and Rx

Event-driven design is fundamental to developing resilient, responsive, and scalable reactive systems as it supports asynchrony and loose coupling. The OMG Data Distribution Service (DDS) is a proven event-driven technology for building data-centric reactive systems because it provides the primitives for decoupling system components with respect to time, space, quality-of-service, and behavior. DDS, by design, supports distribution scalability. However, with increasing core count in CPUs, building multicore-scalable reactive systems remains a challenge.

Publication Year: 
2014
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Supporting End-to-end Scalability and Real-time Event Dissemination in the OMG Data Distribution Service over Wide Area Networks

Assuring end-to-end quality-of-service (QoS) in distributed real-time and embedded (DRE) systems is hard due to the heterogeneity and scale of communication networks, transient behavior, and the lack of mechanisms that holistically schedule different resources end-to-end.

Publication Year: 
2013

Elastic Infrastructure to Support Computing Clouds for Large-scale Cyber-Physical Systems

Large-scale cyber-physical systems (CPS) in mission-critical areas such as transportation, health care, energy, agriculture, defense, homeland security, and manufacturing, are becoming increasingly interconnected and interdependent. These types of CPS are unique in their need to combine rigorous control over timing and physical properties, as well as functional ones, while operating dynamically, reliably and affordably over significant scales of distribution, resource consumption, and utilization.

Publication Year: 
2014
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