# Structuring Reference Architectures for the Industrial Internet of Things
## 7 Findings and Best Practices  
Two major trends can be identified throughout most of the considered reference architectures. First, nearly all promote cyber-security as one of the key IIoT requirements as the IIoT will disable the isolation of critical infrastructure and devices behind restrictive firewalls or even in separated networks. However, the scope is usually limited to overview descriptions while concrete specifications are missing. For instance, the Security Framework provided by the IIC [38] adopts the categories confidentiality, integrity and availability for a more fine-grained definition of cyber-security. Still, the level of coverage is generally not further examined. We identified additional, more detailed security-affecting concerns. Amongst the previously mentioned, these are certification processes, provenance tracking, network security and process isolation, which have to be regarded at all levels of affected levels. Respective measures need to be outlined starting with embedded devices, over edge/fog/cloud computing, to vast distributed systems. While the reference architectures claim to guide the interested reader, implementation details about using which method or technology at which position of the architecture are generally missing. For instance, security concerns and requirements of IIoT systems regarding a network-wide detection of intrusion attempts for instance outlined by Reference [42]. The unifying approach behind the presented architecture should further promote such best practices in order to reach common patterns and a broader adoption. Especially regarding security concerns, we identified a considerable demand and effort by the IIoT community. This is reflected in the remarkable amount of security- and trust-related concerns referenced by nearly all frameworks. In addition, the congruent usage of the same terms indicates an already reached common understanding. However, this is contradicted by the low level of detail provided by the considered frameworks. While certain practices have gained wide acceptance in the web-based communities and also new, innovative approaches--like flexible intrusion detection systems for IIoT networks [13] or data usage control in dynamic settings [43]--are available, the majority of IIoT frameworks does not explain which specific recommendations are appropriate in the industrial IoT domain. The second relevant trend is the repeated reference to a set of core technologies, which have the potential to shape the IIoT. While at the beginning of the IIoT discussions mainly RFID and real-time analytics dominated (for instance in Reference [10; 30; 36]), later 5G and AI are more prominently presented [11; 32; 37] as the major developments for IIoT. While the mentioning of these technologies is certainly justified, their actual disruptive impact can only be estimated. Still, the seamless substitution of technology terms indicates an unclear vision of the real requirements and objectives to be met. In particular, it seems that a general shared understanding of the medium layers of the architectures has been established, while the resulting business workflows and the, therefore, necessary applications--being artificial intelligence, big data analytics or even Blockchains--are taken for granted. Moreover, the upper-level layers related to business and usage aspects are less elaborate in order to enable real end-to-end IIoT application networks. In this direction are also the frequently mentioned Service Level Agreements (SLA) and Quality of Service (QoS) measurements. Reference [44] argues, however, that a Quality of Experience (QoE) approach is more feasible. Ad-hoc vehicular clouds can provide exemplary scenarios for mobile edge nodes with on-the-fly connections and outline routing algorithms with high-velocity [44]. Quality of Experience has been discussed in various IoT scenarios mainly for smart cities by References [45; 46; 44]. New implications regarding the upcoming IoT technologies in smart cities are also reviewed by [PERSON] and [PERSON] [47].