A TMO-based object group model to structuring replicated real-time objects for distributed real-time applications

Chang Sun Shin, Su Chong Joo, Young Sik Jeong

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Scopus citations

Abstract

We designed the TMO-based Object Group(TMOOG) model with various services for supporting distributed real-time applications, and analyzed whether these given service strategies can be adopted and worked to this model well. In this paper, we are interested in the object group model that can be defined as a single logical view system for providing replication transparency and supporting real-time services. The TMOOG model is based on the concept of the object group recommended by the TINA-C and the OMG. Our model consists of a set of computational Time-triggered and Message-triggered Objects(TMOs) for real-time services and several management objects providing how to manage these TMOs and maintain their information such as repositories for executing given distributed real-time applications. The TMOs in an object group may act as copies, called replicas, of a replicated object with the same roles. For the distributed real-time applications, we focused on the following strategies; dynamic object selection and binding strategy to support replication transparency, and real-time strategy to support real-time applications. For supporting these strategies, we adopted the Dynamic Binder object, the Scheduler object and some related objects to our model. These strategies can be flexibly implemented as object implementations by using appropriate algorithms in the model. Our model is designed on Commercial Off-The-Shelf(COTS) middleware without restricting the special Object Request Broker(ORB) or the operating system. Finally, from the analyzed results numerically, we verified whether our model can support these strategies and showed the feasibility of these service strategies adopted from TMOOG model.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsMinglu Li, Qianni Deng, Xian-He Sun, Jun Ni
PublisherSpringer Verlag
Pages918-926
Number of pages9
ISBN (Print)3540219935, 9783540219934
DOIs
StatePublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3033
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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