A scalable service discovery protocol with the optimal discovery time for large-scale cyber physical systems

Abstract

A Cyber Physical System (CPS) is an autonomous embedded system based on high reliability with real-time control of distributed physical systems through networks. 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 large-scale 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 service discovery protocol with optimal discovery time for large-scale cyber physical systems using random back-off and slow-start algorithms. 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.