IoT environments are becoming increasingly heterogeneous in terms of their distributions and included entities by collaboratively involving not only data centers known from Cloud computing but also ...the different types of third-party entities that can provide computing resources. To transparently provide such resources and facilitate trust between the involved entities, it is necessary to develop and implement smart contracts. However, when developing smart contracts, developers face many challenges and concerns, such as security, contracts' correctness, a lack of documentation and/or design patterns, and others. To address this problem, we propose a new recommender system to facilitate the development and implementation of low-cost EVM-enabled smart contracts. The recommender system's algorithm provides the smart contract developer with smart contract templates that match their requirements and that are relevant to the typology of the fog architecture. It mainly relies on OpenZeppelin, a modular, reusable, and secure smart contract library that we use when classifying the smart contracts. The evaluation results indicate that by using our solution, the smart contracts' development times are overall reduced. Moreover, such smart contracts are sustainable for fog-computing IoT environments and applications in low-cost EVM-based ledgers. The recommender system has been successfully implemented in the ONTOCHAIN ecosystem, thus presenting its applicability.
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.
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 the 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 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.
•Identification of requirements for Internet of Things based smart construction applications•Dependable edge computing design for smart construction applications•Implementation details for edge computing software components•Two Internet of Things applications for communications and documentation following the edge computing concept•Measurements for the influence of the geographical location on the QoS
(1) Background: Cloud storage is often required for successful operation of novel smart applications, relying on data produced by the Internet of Things (IoT) devices. Big Data processing tasks and ...management operations for such applications require high Quality of Service (QoS) guarantees, requiring an Edge/Fog computing approach. Additionally, users often require specific guarantees in the form of Service Level Agreements (SLAs) for storage services. To address these problems, we propose QoS-enabled Fog Storage Services, implemented as containerised storage services, orchestrated across the Things-to-Cloud computing continuum. (2) Method: The placement of containerised data storage services in the Things-to-Cloud continuum is dynamically decided using a novel Pareto-based decision-making process based on high availability, high throughput, and other QoS demands of the user. The proposed concept is first confirmed via simulation and then tested in a real-world environment. (3) Results: The decision-making mechanism and a novel SLA specification have been successfully implemented and integrated in the DECENTER Fog and Brokerage Platform to complement the orchestration services for storage containers, thus presenting their applicable value. Simulation results as well as practical experimentation in a Europe-wide testbed have shown that the proposed decision-making method can deliver a set of optimal storage nodes, thus meeting the SLA requirements. (4) Conclusion: It is possible to provide new smart applications with the expected SLA guarantees and high QoS for our proposed Fog Storage Services.
Various smart applications are needed to address complex problems in construction falling under the broad categories of safety at work, construction site management, management of resources, waste ...and assets and construction progress monitoring. Fog computing emerges as a new computing paradigm for Edge-to-Cloud computing that integrates Internet of Things (IoT), Artificial Intelligence (AI), and Blockchain technologies to facilitate the development and operation of smart applications. However, a comprehensive methodology that applies Fog computing to construction projects is currently missing. In our work, we use the novel DECENTER Fog Computing and Brokerage Platform to address requirements for flexible use of AI methods in construction projects and develop a relevant methodology. Evaluation is performed through all application development phases at a real construction site in Ljubljana, Slovenia. Testing results show that the use of Fog computing contributes to high response rates, privacy and security when processing sensitive worker and company data.
•New methodology applying fog computing to achieve smart construction sites•Flexible combination of AI methods to fit a variety of construction projects•QoS-aware orchestration of the AI applications for dependable response time•Privacy preserving data management through Ethereum-based Smart Contracts•Experimental study showing methodology's applicability and resulting performance
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.
•Probabilistic method for choosing an optimal cloud deployment option.•Equivalence classification of available cloud deployment options.•Model-checking approach to verify decision-making ...results.•Experimental study comparing the new probabilistic method with a baseline method.
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 time-consuming. 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 cloud applications, File Upload and Video-conferencing. The FoQoSAM method was compared to a baseline Analytic Hierarchy Process (AHP). The results show that the first ranked cloud deployment options satisfy all hard and at least one of the soft requirements for both methods, however, the FoQoSAM method always satisfies at least an additional QoS requirement compared to the baseline AHP method.
Conclusions: The proposed new FoQoSAM method is appropriate and can be used in decision-making when ranking and verifying cloud deployment options. Due to its practical utility it was integrated into the SWITCH workbench.
Modern component-based software engineering environments allow deployment of cloud applications on various computing infrastructures, such as Edge-to-Cloud infrastructures. The heterogeneous nature ...of such computing resources results in variable Quality of Service (QoS). Therefore, the deployment decision can seriously affect the application’s overall performance. This study presents an approach for automated deployment of cloud applications in the Edge-to-Cloud computing continuum that considers non-functional requirements (NFRs). In addition, the authors explore multiple methods for selection of optimal cloud infrastructure, such as IaaS. The paper presents an experimental evaluation performed using a cloud application for storing data under different workloads. For the purposes of the experimental evaluation, a Kubernetes cluster composed of 44 computing nodes was used. The cluster nodes were geographically distributed computing infrastructures hosted by several service providers. The proposed approach allows a reliable selection of infrastructures, which satisfy high QoS requirements for cloud applications, from heterogeneous Edge-to-Cloud computing environments. Современные среды разработки программного обеспечения на основе компонентно-ориентированного программирования позволяют беспрепятственно развертывать облачные приложения в различных вычислительных инфраструктурах, таких как Edge-to-Cloud. Неоднородная природа таких вычислительных ресурсов приводит к непостоянному качеству обслуживания (QoS). Поэтому решение о развертывании приложения может серьезно повлиять на его общую производительность. В статье рассмотрен подход к автоматизированному развертыванию облачных приложений в вычислительном континууме Edge-to-Cloud, учитывающий нефункциональные требования (NFR). Исследованы способы выбора оптимальной услуги с точки зрения ожидаемого качества обслуживания. Экспериментальная оценка проведена с помощью облачного приложения для хранения данных в трех случаях с разной нагрузкой. Проведены эксперименты на кластере Kubernetes, состоящем из 44 вычислительных узлов (облачных инфраструктур). Узлы кластера были географически распределены в нескольких местах и размещались несколькими поставщиками услуг. Подход позволит надежно выбирать инфраструктуры из гетерогенных Edge-to-Cloud сред, удовлетворяющих требованиям к качеству обслуживания облачных приложений.
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