TR97-01

RT-CRM: Real-Time Channel-based Reflective Memory


    •  Shen, C., Mizunuma, I., "RT-CRM: Real-Time Channel-Based Reflective Memory", IEEE Real-Time Technology and Applications Symposium (RTAS), June 1997, pp. 239-251.
      BibTeX TR97-01 PDF
      • @inproceedings{Shen1997jun,
      • author = {Shen, C. and Mizunuma, I.},
      • title = {RT-CRM: Real-Time Channel-Based Reflective Memory},
      • booktitle = {IEEE Real-Time Technology and Applications Symposium (RTAS)},
      • year = 1997,
      • pages = {239--251},
      • month = jun,
      • url = {https://www.merl.com/publications/TR97-01}
      • }
  • Research Area:

    Data Analytics

Abstract:

In this paper, we propose and present Real-Time Channel-based Reflective Memory (RT-CRM) -- a useful programming model and middleware communication service for constructing distributed real-time industrial monitoring and control applications on commercially available open systems. RT-CRM provides remote real-time data reflection abstraction using a simple writer-push model. This writer-push approach enables us to easily decouple the QoS characteristics of the writers from that of the readers. This decoupling is crucial in supporting different kinds of remote data transfer and access needs that one often finds in distributed industrial systems. We will describe the design of RT-CRM, along with a set of easy-to-use API to access the RT-CRM service. We have implemented RT-CRM as part of a larger real-time middleware project, MidART. We address many of the important implementation issues including buffer management and QoS support. We demonstrate the feasiblity of RT-CRM through a discussion of our application programming support and preliminary performance data.

 

  • Related News & Events

    •  NEWS    RTAS 1997: publication by Chia Shen and others
      Date: June 9, 1997
      Where: IEEE Real-Time Technology and Applications Symposium (RTAS)
      Research Area: Data Analytics
      Brief
      • The paper "RT-CRM: Real-Time Channel-Based Reflective Memory" by Shen, C. and Mizunuma, I. was presented at the IEEE Real-Time Technology and Applications Symposium (RTAS).
    •