Adaptive real-time video transmission over DDS

Abstract

An increasing number of industrial applications include video processing capacities, which allow, among others, remote monitoring of industrial processes and control of private and public areas. Image processing has real-time requirements which result in resource demands at both node and network levels. Moreover, video is usually compressed and coded to be transmitted which generates variable bit-rate streams. This introduces variable processing requirements inside the node in terms of memory and processor cycles required for the processing of the sequence of different video frames. A direct impact on the network resource is also obvious since variable network bandwidth will be required to transmit the frames that may affect the bandwidth assigned to other streams. Efficient distributed video surveillance requires that real-time constraints be respected or, at least, quality of service guarantees (QoS) be provided. The traditional approach to video transmission has focused at the level of the network protocols. However, architectural solutions at the middleware level introduce higher flexibility and more efficiency in development time. This paper presents an architecture that precisely defines an integral set up of the different components that are relevant in achieving realtime and QoS-based video surveillance. The paper describes how the DDS standard for real-time distributed systems, can be used for this purpose; based on the decoupled interaction paradigm of DDS, higher complexity surveillance deployments are possible. A prototype surveillance system is presented which includes video transmission and adaptation to environmental sensing events.

Live video transmission over data distribution service with existing low-power platforms

“…Garcia-Valls, Basanta-Val and Estévez-Ayres tested RTI's implementation of DDS middleware to see the average delay of message writes but only tested messages up to a maximum size of 1000 bytes which took on average 0.103ms [5]. Proposed experiments for this study will be using high bandwidth video in which sample sizes will be significantly larger to simulate worst case scenarios of high bandwidth video.…”

Prototyping low-cost and flexible vehicle diagnostic systems

“…Examples are traditional component based technologies such as Corba (OMG, 2012), its light-weight evolution Ice (Internet Communication Engine) (ZeroC, 2003); object oriented middleware such as RMI (Remote Method Invoction) (Sun, 2016) that is a language dependant solution but platform independant solution, its service enhancement named River (Apache, 2013), and other message based technologies such as JMS (Java Messaging Service), AMQP (Advanced Message Queuing Protocol) (IITF, 2014). In the last decade, publish-subscribe data centric middleware such as DDS (Data Distribution Systems for Real-Time applications) (OMG, 2015) have become de-facto standards for system interoperability in a number of domains from web applications, industrial automation, or remote real-time video surveillance (García-Valls et al, 2010).…”

Model-driven template metaprogramming

“…This complexity arises from the high level of variability that needs to be managed by the systems [2].…”