Trust is a crucial aspect when cyber-physical systems have to rely on resources and services under ownership of various entities, such as in the case of Edge, Fog and Cloud computing. The DECENTER's Fog Computing Platform is developed to support Big Data pipelines, which start from the Internet of Things (IoT), such as cameras that provide video-streams for subsequent analysis. It is used to implement Artificial Intelligence (AI) algorithms across the Edge-Fog-Cloud computing continuum which provide benefits to applications, including high Quality of Service (QoS), improved privacy and security, lower operational costs and similar. In this article, we present a trust management architecture for DECENTER that relies on the use of blockchain-based Smart Contracts (SCs) and specifically designed trustless Smart Oracles. The architecture is implemented on Ethereum ledger (testnet) and three trust management scenarios are used for illustration. The scenarios (trust management for cameras, trusted data flow and QoS based computing node selection) are used to present the benefits of establishing trust relationships among entities, services and stakeholders of the platform.

The Internet of Things (IoT) such as the use of robots, sensors, actuators, electronic signalization and a variety of other Internet enabled physical devices may provide for new advanced smart applications to be used in construction in very near future. Such applications require real-time responses and are therefore time-critical. Therefore, in order to support collaboration, control, monitoring, supply management, safety and other construction processes, they have to meet dependability requirements, including requirements for high Quality of Service (QoS). Dependability and high QoS can be achieved by using adequate number and quality of computing resources, such as processing, memory and networking elements, geographically close to the smart environments. The goal of this study is to develop a practical edge computing architecture and design, which can be used in to support smart construction environments with high QoS. This study gives particular attention to the solution design, which relies on latest cloud and software engineering approaches and technologies, and provides elasticity, interoperability and adaptation to companies' specific needs. Two edge computing applications supporting video communications and construction process documentation are developed and demonstrate a viable edge computing design for smart construction.

Context: Existing software workbenches allow for the deployment of cloud applications across a variety of Infrastructure-as-a-Service (IaaS) providers. The expected workload, Quality of Service (QoS) and Non-Functional Requirements (NFRs) must be considered before an appropriate infrastructure is selected. However, this decision-making process is complex and timeconsuming. Moreover, the software engineer needs assurances that the selected infrastructure will lead to an adequate QoS of the application. Objective: The goal is to develop a new method for selection of an optimal cloud deployment option, that is, an infrastructure and configuration for deployment and to verify that all hard and as many soft QoS requirements as possible will be met at runtime. Method: A new Formal QoS Assurances Method (FoQoSAM), which relies on stochastic Markov models is introduced to facilitate an automated decision-making process. For a given workload, it uses QoS monitoring data and a user-related metric in order to automatically generate a probabilistic model. The probabilistic model takes the form of a finite automaton. It is further used to produce a rank list of cloud deployment options. As a result, any of the cloud deployment options can be verified by applying a probabilistic model checking approach. Results: Testing was performed by ranking deployment options for two