The Internet of Things needs for computing power and storage are expected to remain on the rise in the next decade. Consequently, the amount of data generated by devices at the edge of the network will also grow. While cloud computing has been an established and effective way of acquiring computation and storage as a service to many applications, it may not be suitable to handle the myriad of data from IoT devices and fulfill largely heterogeneous application requirements. Fog computing has been developed to lie between IoT and the cloud, providing a hierarchy of computing power that can collect, aggregate, and process data from/to IoT devices. Combining fog and cloud may reduce data transfers and communication bottlenecks to the cloud and also contribute to reduced latencies, as fog computing resources exist closer to the edge. This paper examines this IoT-Fog-Cloud ecosystem and provides a literature review from different facets of it: how it can be organized, how management is being addressed, and how applications can benefit from it. Lastly, we present challenging issues yet to be addressed in IoT-Fog-Cloud infrastructures.

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The Internet of Things, Fog and Cloud continuum: Integration and challenges

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The Internet of Things, Fog and Cloud Continuum: Integration and Challenges

This paper develops a formal framework, founded on description logics, to assist decision making in relation to the manufacturing operation and control in modern enterprises that stand to benefit from the transition to Industry 4.0. The objective is to provide sophisticated support to individuals making decisions in the area of production operations management and in particular, production scheduling and material requirements planning. Using this framework, this paper demonstrates an approach to encode the domain knowledge of human experts managing the production as sets of formal rules. These rules can be implemented in an intelligent system that can assist and empower human experts, reducing difficulty when making decisions in complex manufacturing environments.

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A Rule-Based Approach Founded on Description Logics for Industry 4.0 Smart Factories

IoT-enabled applications, such as cloud manufacturing, guided water quality or air quality analysis, energy-conscious societal applications, and smart agricultural economics, are designed using a blend of high-end computing technologies, such as cloud, edge, and fog. Smart cities and governmental authorities keep a keen eye out for implementing IoT applications in an automated/decentralized approach with enhanced security measures so that tens of thousands of users, including entrepreneurs, are benefited. Existing IoT architectures are prone to energy inefficiency or resource underutilization problems due to the avoidance of apt technologies, such as serverless computing. This article proposes to set forth a serverless blockchain-enabled IoT architecture for societal applications. It explores the existing IoT architectures and pinpoints the advantages of applying serverless blockchains on IoT architectures. In addition, the proposed IoT architecture is illustrated with a specific use case of IoT societal applications namely air quality monitoring for smart cities (AQMS). This article discloses how air quality sensor data from defective industries were securely transacted to blockchain networks surpassing from the three levels of computing namely edge, fog, and cloud while utilizing serverless and server-oriented functions. In addition, this article exposes a list of the most potent serverless functions that assist AQMS IoT societal applications in detail. The IoT architecture, discussed in this article, will enable innovations and research works for IoT developers and researchers.

Serverless Blockchain-Enabled Architecture for IoT Societal Applications

Academia and Industry have acknowledged that having a fully described software architecture is a crucial asset for software development and maintenance. The description of a software architecture is read by many stakeholders when developing and maintaining complex software systems which are composed by multiple elements, including software, systems, hardware and processes. The software architecture as a development product is useful for technical activities, such as describing the views and concerns of the future software products, as well as for management activities, including allocating tasks to each team and as an input for project management activities. One main issue when describing the software architecture is knowing what elements must be included in the architecture, and at what level of detail. Therefore, it is not unusual that software architects have to deal with difficulties in terms of how to describe the architecture. This paper brings two main purposes: first is the idea of establishing levels of a maturity model for software architectures, which can help in organizing, describing and communicating the software architecture for multiple stakeholders, and, second, a way to evaluate how mature is the software architecture.

ArchCaMO - A Maturity Model for Software Architecture Description Based on ISO/IEC/IEEE 42010:2011

This paper reports the work in progress towards the specification of a conceptual architecture of a smart system for supporting the management of disruptions in the manufacturing domain. In particular, it proposes an approach to the description of the system architecture based on a number of interrelated viewpoints following the pertinent ISO 42010 standard. The approach is being developed in the context of the EU-funded H2020 DISRUPT project aiming to deliver a comprehensive data-driven solution for automated vertical and horizontal integration facilitating the transition into smart manufacturing.

WiP: An Architecture for Disruption Management in Smart Manufacturing

The orchestration of smart manufacturing service operations and processes arises as a challenging step in the realization of the Industry 4.0 vision. This paper presents the work in progress towards the specifications of a controlling environment for data-driven orchestration of software services in future smart manufacturing scenarios. The paper discusses the role and significance of multi-aspect data in the management of manufacturing operations and proposes a reference architecture for controlling the orchestration of the respective data services, following the work that has been conducted in the context of the EU-funded project DISRUPT.

Towards a Cloud-Based Controller for Data-Driven Service Orchestration in Smart Manufacturing

Significant effort is currently being invested on enhancing digitization in all aspects of industrial processes and manufacturing on the quest for the next transformational change towards sustainable manufacturing and the factories of the future. This vision, commonly termed as Industry 4.0, is at the core of a number of funded projects in Europe. This short paper briefly reports experiences from the EU-funded project DISRUPT and focuses on the identification of some key challenges in the interplay between Industry 4.0 and High Performance Computing.

High performance computing and industry 4.0: experiences from the DISRUPT project

Data-driven decision making is at the core of Industry 4.0. This paper describes the specification of a conceptual architecture of a smart system for supporting decision making in the context of disruptive events in manufacturing operations. Following a viewpoint-oriented approach, the proposed architecture identifies the functional components that facilitate decision making and establishes the interfaces between them, demonstrates the information flow within the manufacturing ecosystem for vertical / horizontal integration and establishes the mapping of the functional components to different software containers, execution environments and physical devices.

Specification of a Software Architecture for an Industry 4.0 Environment

The Reference Architecture Model Industry 4.0 (RAMI4.0) proposes two models to guide the design of virtual representations of assets. A cubic model represents assets in the form of layers and allows them to be tracked over their lifetime and assigned to technical or organizational hierarchies. The I4.0 component model suggests how to organise virtual representations, i.e., asset properties (data and functions). A service hierarchy has also been proposed as the mechanism to gain access to asset properties. This paper presents an analysis of the RAMI4.0 service hierarchy, compared to traditional service oriented architecture, towards a methodology for the design of RAMI4.0 services. We envision a methodology based on object-oriented analysis and design principles. The rationale behind our approach is the similarity that holds between objects and assets as I4.0 components. Data and functions within objects are accessible through method invocations; data and functions of assets are accessible through service invocations. The paper outlines the use of this approach in defining RAMI4.0 services for a software system being designed to support decision making under events that disrupt manufacturing operations.

Vasilios Tountopoulos

Papers

WiP: An Architecture for Disruption Management in Smart Manufacturing

Towards a Cloud-Based Controller for Data-Driven Service Orchestration in Smart Manufacturing

High performance computing and industry 4.0: experiences from the DISRUPT project

Specification of a Software Architecture for an Industry 4.0 Environment

Towards a Methodology for RAMI4.0 Service Design