Automated integration of real-time and non-real-time defense systems

Dalkiran E., Onel T., Topcu O., Demir K. A.

DEFENCE TECHNOLOGY, vol.17, no.2, pp.657-670, 2021 (SCI-Expanded, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 17 Issue: 2
  • Publication Date: 2021
  • Doi Number: 10.1016/j.dt.2020.01.005
  • Journal Name: DEFENCE TECHNOLOGY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.657-670
  • Keywords: Systems integration, System of systems, Systems engineering, Software engineering, C4I systems, Defense systems, Data distribution service, DDS integration, Java message service, JMS, SERVICE
  • Middle East Technical University Northern Cyprus Campus Affiliated: Yes

Abstract

Various application domains require the integration of distributed real-time or near-real-time systems with non-real-time systems. Smart cities, smart homes, ambient intelligent systems, or network-centric defense systems are among these application domains. Data Distribution Service (DDS) is a communi-cation mechanism based on Data-Centric Publish-Subscribe (DCPS) model. It is used for distributed systems with real-time operational constraints. Java Message Service (JMS) is a messaging standard for enterprise systems using Service Oriented Architecture (SOA) for non-real-time operations. JMS allows Java programs to exchange messages in a loosely coupled fashion. JMS also supports sending and receiving messages using a messaging queue and a publish-subscribe interface. In this article, we pro -pose an architecture enabling the automated integration of distributed real-time and non-real-time systems. We test our proposed architecture using a distributed Command, Control, Communications, Computers, and Intelligence (C4I) system. The system has DDS-based real-time Combat Management System components deployed to naval warships, and SOA-based non-real-time Command and Control components used at headquarters. The proposed solution enables the exchange of data between these two systems efficiently. We compare the proposed solution with a similar study. Our solution is superior in terms of automation support, ease of implementation, scalability, and performance.