A Real-Time Push-Pull Communications Model for Distributed Real-Time and Multimedia Systems

Real-time and multimedia applications like multi-party collaboration, internet telephony and distributed command control systems require the exchange of information over distributed and heterogeneous nodes. Multiple data types including voice, video, sensor data, real-time intelligence data and text are being transported widely across today's information, control and surveillance networks. All such applications can bene t enormously from middleware, operating system and networking services that can support QoS guarantees, high availability, dynamic recon gurability and scalability. In this paper, we propose a middleware layer called the \Real-Time Push-Pull Communications Service" to easily and quickly disseminate information across heterogeneous nodes with exible communication patterns. Realtime push-pull communications is an extension of the real-time publisher/subscriber model, and represents both \push" (data transfer initiated by a sender) and \pull" (data transfer initiated by a receiver) communications. Nodes with widely di ering processing power and networking bandwidth can coordinate and co-exist by the provision of appropriate and automatic support for transformation on data. In particular, unlike the real-time publisher/subscriber model, di erent information sources and sinks can operate at di erent frequencies and also can choose another (intermediate) node to act as their proxy and and deliver data at the desired frequency. In addition to the synchronous communications of the publisher-subscriber model, information sinks can also choose to obtain data asynchronously. This service has been implemented on RT-Mach, a resource-centric kernel using resource kernel primitives [7]. This paper presents an overview of the design, implementation and a performance evaluation of the model. We also test the applicability and versatility of this service using RT-Conference, a multi-party multimedia collaboration application built on top of this model. Finally, we summarize some key lessons learned in this process.