Towards Cognitive Self-Management of IoT-Edge-Cloud Continuum based on User Intents

Elasticity of the computing continuum with on demand availability allows for automated provisioning and release of computing resources as needed; however, this self management capability is severely limited due to the lack of knowledge on historical and timely resource utilisation and means for stakeholders to express their needs in a high-level manner. In this paper, we introduce and discuss a new concept – intent-based cognitive continuum for sustainable elasticity.acceptedVersio

QoS-aware architectures, technologies, and middleware for the cloud continuum

The recent trend of moving Cloud Computing capabilities to the Edge of the network is reshaping how applications and their middleware supports are designed, deployed, and operated. This new model envisions a continuum of virtual resources between the traditional cloud and the network edge, which is potentially more suitable to meet the heterogeneous Quality of Service (QoS) requirements of diverse application domains and next-generation applications. Several classes of advanced Internet of Things (IoT) applications, e.g., in the industrial manufacturing domain, are expected to serve a wide range of applications with heterogeneous QoS requirements and call for QoS management systems to guarantee/control performance indicators, even in the presence of real-world factors such as limited bandwidth and concurrent virtual resource utilization. The present dissertation proposes a comprehensive QoS-aware architecture that addresses the challenges of integrating cloud infrastructure with edge nodes in IoT applications. The architecture provides end-to-end QoS support by incorporating several components for managing physical and virtual resources. The proposed architecture features: i) a multilevel middleware for resolving the convergence between Operational Technology (OT) and Information Technology (IT), ii) an end-to-end QoS management approach compliant with the Time-Sensitive Networking (TSN) standard, iii) new approaches for virtualized network environments, such as running TSN-based applications under Ultra-low Latency (ULL) constraints in virtual and 5G environments, and iv) an accelerated and deterministic container overlay network architecture. Additionally, the QoS-aware architecture includes two novel middlewares: i) a middleware that transparently integrates multiple acceleration technologies in heterogeneous Edge contexts and ii) a QoS-aware middleware for Serverless platforms that leverages coordination of various QoS mechanisms and virtualized Function-as-a-Service (FaaS) invocation stack to manage end-to-end QoS metrics. Finally, all architecture components were tested and evaluated by leveraging realistic testbeds, demonstrating the efficacy of the proposed solutions

Agile innovation: Innovating with enterprise systems

The contemporary organisations are presented with an eclectic collection of technologies that has dramatically shifted the process of innovation. This thesis investigates the nature and the process of attaining innovation through the modern IT portfolio. A qualitative study of nine organizations was conducted. The results identified that the modern IT portfolio innovates through a new innovation process called 'agile innovation,' which differs from the existing innovation types

Automated planning for cloud service configurations

The declarative approach has been widely accepted as an appropriate way to manage configurations of large scale systems – the administrators describe the specification of the “desired” configuration state of the system, and the tool computes and executes the necessary actions to bring the system from its current state into this desired state. However, none of state-of-the-art declarative configuration tools make any guarantees about the order of the changes across the system involved in implementing configuration changes. This thesis presents a technique that addresses this issue – it uses the SFP language to allow administrators to specify the desired configuration state and the global constraints of the system, compiles the specified reconfiguration task into a classical planning problem, and then uses an automated planning technique to automatically generate the workflow. The execution of the workflow can bring the system into the desired state, while preserving the global constraints during configuration changes. This thesis also presents an alternative approach to deploy the configurations – the workflow is used to automatically choreograph a set of reactive agents which are capable to autonomously reconfigure a computing system into a specified desired state. The agent interactions are guaranteed to be deadlock/livelock free, can preserve pre-specified global constraints during their execution, and automatically maintain the desired state once it has been achieved (self-healing). We present the formal semantics of SFP language, the technique that compiles SFP reconfiguration tasks to classical planning problems, and the algorithms for automatic generation and execution of the reactive agent models. In addition, we also present the formal semantics of core subset of SmartFrog language which is the foundation of SFP. Moreover, we present a domain-independent technique to compile a planning problem with extended goals into a classical planning problem. As a proof of concept, the techniques have been implemented in a prototype configuration tool called Nuri, which has been used to configure typical use-cases in cloud environment. The experiment results demonstrate that the Nuri is capable of planning and deploying the configurations in a reasonable time, with guaranteed constraints on the system throughout reconfiguration process