Quality of Service-aware matchmaking for adaptive microservice-based applications

Applications that make use of Internet of Things (IoT) can capture an enormous amount of raw data from sensors and actuators, which is frequently transmitted to cloud data centers for processing and analysis. However, due to varying and unpredictable data generation rates and network latency, this can lead to a performance bottleneck for data processing. With the emergence of fog and edge computing hosted microservices, data processing could be moved towards the network edge. We propose a new method for continuous deployment and adaptation of multi-tier applications along edge, fog, and cloud tiers by considering resource properties and non-functional requirements (e.g., operational cost, response time and latency etc.). The proposed approach supports matchmaking of application and Cloud-To-Things infrastructure based on a subgraph pattern matching (P-Match) technique. Results show that the proposed approach improves resource utilization and overall application Quality of Service. The approach can also be integrated into software engineering workbenches for the creation and deployment of cloud-native applications, enabling partitioning of an application across the multiple infrastructure tiers outlined above

Building applications for smart and safe construction with the DECENTER Fog Computing and Brokerage Platform

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

A Recommender System for Robust Smart Contract Template Classification

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

Pareto-optimised Fog Storage Services with novel Service-Level Agreement specification

(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

Deployment of Application Microservices in Multi-Domain Federated Fog Environments

In this paper we consider the problem of initial resource selection for a single-domain fog provider lacking sufficient resources for the complete deployment of a batch of IoT applications. To overcome resources shortage, it is possible to lease assets from other domains across a federation of cloud-fog infrastructures to meet the requirements of those applications: the fog provider seeks to minimise the number of external resources to be rented in order to successfully deploy the applications' demands exceeding own infrastructure capacity. To this aim, we introduce a general framework for the deployment of applications across multiple domains of cloud-fog providers while guaranteeing resources locality constraints. The resource allocation problem is presented in the form of an integer linear program, and we provide a heuristic method that explores the resource assignment space in a breadth-first fashion. Extensive numerical results demonstrate the efficiency of the proposed approach in terms of deployment cost and feasibility with respect to standard approaches adopted in the literature

Smart Contracts for Service-Level Agreements in Edge-to-Cloud Computing

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