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.

Although the cloud computing domain is progressing rapidly, the deployment of various network intensive software utilities in the cloud is still a challenging task. The Quality of Service (QoS) for various gaming, simulations, video-conferencing, video-streaming or even file uploading tasks may be significantly affected by the quality and geolocation of the selected underlying computing resources, which are available only when the specific functionality is required. This study presents a new architecture for geographic orchestration of network intensive software components which is designed for high QoS. Key elements of this architecture are a Global Cluster Manager (GCM) operating within Software Defined Data Centres (SDDCs), a runtime QoS Monitoring System, and a QoS Modeller and Decision Maker for automated orchestration of software utilities. The implemented system automatically selects the best geographically available computing resource within the SDDC according to the developed QoS model of the software component. This architecture is event-driven as the services are deployed and destroyed in real-time for every usage event. The utility of the implemented orchestration technology is verified qualitatively, and in relation to the potential gains of selected QoS metrics by using two network intensive software utilities implemented as containers: an HTTP(S) file upload service and a Jitsi Meet videoconferencing service. The study shows potential for QoS improvements in comparison to existing orchestration systems.

The management of Service-Level Agreements (SLAs) in Edge-to-Cloud computing is a complex task due to the great heterogeneity of computing infrastructures and networks and their varying runtime conditions, which influences the resulting Quality of Service (QoS). SLA-management should be supported by formal assurances, ranking and verification of various microservice deployment options. This work introduces a novel Smart Contract (SC) based architecture that provides for SLA management among relevant entities and actors in a decentralised computing environment: Virtual Machines (VMs), Cloud service consumers and Cloud providers. Its key components are especially designed SC functions, a trustless Smart Oracle (Chainlink) and a probabilistic Markov Decision Process. The novel architecture is implemented on Ethereum ledger (testnet). The results show its feasibility for SLA management including low costs operation within dynamic and decentralised Edge-to-Cloud federations.

New software engineering technologies facilitate development of applications from reusable software components, such as Virtual Machine and container images (VMI/CIs). Key requirements for the storage of VMI/CIs in public or private repositories are their fast delivery and cloud deployment times. ENTICE is a federated storage facility for VMI/CIs that provides optimisation mechanisms through the use of fragmentation and replication of images and a Pareto Multi-Objective Optimisation (MO) solver. The operation of the MO solver is, however, time-consuming due to the size and complexity of the metadata, * Vlado Stankovski, University of Ljubljana, Faculty of Civil and Geodetic Engineering, Jamova cesta 2, SI-1000 Ljubljana, Slovenia.2 E-mail: vlado.stankovski@fgg.uni-lj.si 1 specifying various non-functional requirements for the management of VMI/CIs, such as geolocation, operational cost and delivery time. In this work, we address this problem with a new semantic approach, which uses an ontology of the federated ENTICE repository, knowledge base and constraint-based reasoning mechanism. Open Source technologies such as Protégé, Jena Fuseki and Pellet were used to develop a solution. Two specific use cases: (1) repository optimisation with offline and (2) online redistribution of VMI/CIs, are presented in detail. In both use cases, data from the knowledge base is provided to the MO solver. It is shown that Pellet based reasoning can be used to reduce the input metadata size used in the optimisation process by taking into consideration the geographic location of the VMI/CIs and the provenance of the VMI fragments. It is shown that this process leads to reduction of the input metadata size for the MO solver by up to 60% and reduction of the total optimization time of the MO solver by up to 68%, while fully preserving the quality of the solution, which is significant.

Cloud computing is based on Virtual Machines (VM) or containers, which provide their own software execution environment that can be deployed by facilitating technologies on top of various physical hardware. The use of VMs or containers represents an efficient way to automatize the overall software engineering and operation life-cycle. Some of the benefits include elasticity and high scalability, which increases the utilization efficiency and decreases the operational costs. VMs or containers as software artifacts are created using provider-specific templates and are stored in proprietary or public repositories for further use. However, technology specific choices may reduce their portability, lead to a vendor lock-in, particularly when applications need to run in federated Clouds. In this paper we present the current state of development of the novel concept of a VM repository and operational environment for federated Clouds named ENTICE. The ENTICE environment has been designed to receive unmodified and functionally complete VM images from its users, and transparently tailor and optimise them for specific Cloud infrastructures with respect to their size, configuration, and geographical distribution, such that they are loaded, delivered, and executed faster and with improved QoS compared to their current behaviour. Furthermore, in this work a specific use case scenario for the ENTICE environment has been provided and the underlying novel technologies have been presented.