## 1 Introduction  
The industrial internet of things (IIoT) and smart manufacturing have become the most popular industrial technical paradigms and business concepts in recent years. With the continuous integration of emerging information and communication technologies (ICT), the manufacturing industry is envisaged to experience a revolution in its way of operating toward autonomous and smart manufacturing. A wide spectrum of smarter sensors, actuators, controllers, and robotics are connected and integrated to constitute ubiquitous systems, which can potentially maximise the efficiency of machines and the throughput of operations [1]. The envisioned manufacturing systems can potentially empower collaborative manufacturing, which promises greater production flexibility and product variability with minimised human interventions.  
As a new computing paradigm, the internet of things (IoT) has found applications in many different fields, such as home automation, medical aid, elderly care, smart grid, traffic management, and many others [2]. The integration of the IoT paradigm in the automation industry has fostered IIoT, which promises an even greater prospective future. There are several newly coined terms to describe this futuristic industrial concept, such as Manufacturing 2.0, Industry 4.0, Industrial Internet, smart factory and IIoT. Although they are proposed in a different context of applications, they share the basic ideas of improving the operation mode of industrial processes by interactive collaborations and intelligent optimisations of machines with connectivity.  
Evidently, digital manufacturing is a highly interdisciplinary field involving a wide range of applied sciences. Studies in these fields have attracted much effort in both academia and industry, especially machine-to-machine (M2M) connectivity and communication which are critical building blocks for machine collaboration and process optimisation [3]. High-quality connectivity and ubiquitous M2M communications will boost innovations in industrial applications. However, industrial practices suggest that the organisation, collaboration, and interoperability of connected machines are still tricky tasks.  
M2M service platforms are being standardised to enable inter-communication between machines at different levels, and many standard development organisations (SDOs) are working toward M2M standards for industry, such as the Institute of Electrical and Electronics Engineers (IEEE), the European Telecommunications Standards Institute (ETSI), the Internet Engineering Task Force (IETF), and the 3 rd Generation Partnership Project (3 GPP). Some technological solutions and standards have been invented for different application contexts, such as Wi-Fi, 3G, 4G, Long-Term Evolution (LTE) radio communication standards, and network protocols WirelessHART, ISA100.11a, Z-Wave, and KNX [4]. There are also SDOs working toward system frameworks called manufacturing reference architectures (MRAs), such as the ETSI M2M service architecture, the Smart Manufacturing Leadership Coalition (SMLC) smart manufacturing platform, the oneM2M harmonised reference architecture, and Microsoft Discrete Manufacturing Reference Architecture (DiRA) [5]. The focal issues of these MRAs are openness, interoperability, inter-module collaborations, and manufacturing process optimisation.  
Although the crucial technical issues have been addressed, there exists an underlying gap between model-based service architectures and mechanical operations. Thus, the techniques are not yet ready to use in dealing with the heterogeneous machines in a flexible and interoperable way. Ubiquitous M2M messaging and machine understanding are recognised as the central issues to manufacturing management. This article highlights the major technical gaps of M2M communications in IIoT, and gives a reference architecture and a collaboration-oriented M2M (CoM2M) mechanism to enhance the interoperability between interconnected machines focusing on machine connectivity, messaging and understanding.