An Efficient Discovery Protocol of Large-Scale CPS Middleware for Real-Time Control System

Abstract

A Cyber Physical System (CPS) is an autonomous embedded system based on high reliability with real-time control of distributed physical systems through wired/wireless networks. There is usually large volume of data which needs to be delivered to right places at the right time. In addition, large number of controllers in the automation and control systems are usually distributed which increases the complexity that there needs to be more point-to-point Ethernetconnections in the network. Because the controllers in the network may share control data and interact with each other from different communication protocols, including higher level operator systems. The interdependencies between these nodes may potentially create a complex architecture of the network in the distributed system especially if the point-topoint connection needs to be established. Publish-subscribe model shows some appealing properties, such as connectionless and multicast, that can be used to reduce some of the visible complexity in the software systems. Data distribution middleware for CPS should be based on a data-centric approach and guarantee real-time performance. In this regard, OMG's DDS is the best proximity middleware. RTPS (Real-Time Publish/Subscribe) is proposed for real-time service discovery in DDS. However, legacy discovery protocols cannot completely support the CPS system with a largescale network (approx. 100,000 entities) like a warship, because service discovery messages are proportional to the square of the number of participants in RTPS. This paper proposes a scalable and fast service discovery protocol with improved discovery time for large-scale cyber physical systems based on the boot-strap algorithm and adaptive PDP message period. As a result, the proposed protocol improves reliability and real-time for service discovery in cyber physical systems. In this paper, mathematical analysis and test-bed experiments are conducted to evaluate the performance of the proposed protocol. Consequently, mathematical analysis and test-bed experiments provide almost identical results. The performance results prove that our protocol works to scale for large-scale CPS networks by minimizing the discovery time as well as traffic simultaneously

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