RiSING
The Robust and Secure Distributed Computing (RiSING) aims to investigate methods and design and implement platforms that guarantee efficiency, robustness and security in distributed computing environments covering the whole cloud-to-edge continuum.
Research Focus
Distributed infrastructures leveraging Cloud Computing and Software-Defined Networking (SDN) technologies can provide on-demand computation, storage and connectivity resources to provision advanced cloud-native services. The pervasive diffusion of edge devices and components (sensors, personal handheld and wearable devices) is leading to a fundamental shift from the traditionally centralised cloud model to a more decentralised one, in which workloads are executed closer to the end-user, where data is ultimately produced and consumed. Such a scenario is usually referred to as the cloud-to-edge (or cloud-to-things) continuum, and is characterised by multiple tiers of heterogeneous and geographically dispersed computing elements interconnected by means of various networking technologies. The emerging architectural paradigm that has been elaborated to enable control over such a complex infrastructure is called Fog Computing. Such paradigm has found large traction in multiple sectors such as 5G, industry 4.0, smart cities, digital health, and more. However, ensuring quality of service to the applications delivered in the cloud-to-edge continuum with adequate levels of robustness and security represents one of the biggest challenges that academic and industrial communities are facing nowadays.
In this context, the RiSING research unit aims to study intrinsic properties of fog computing systems and propose, design and implement methods and algorithms that guarantee their security and resiliency, while taking into due account the overall system efficiency (in terms of e.g. resource utilisation or power consumption). RiSING R&D has a dual perspective and concerns both:
- Platform
- Extend cloud models and techniques to provide automated workload orchestration and service management, with the aim of increasing efficiency in delivering applications through the fog. RiSING develops optimal and heuristic strategies aimed at optimising the utilisation of resources in multi-tier/multi-region infrastructures. In addition to that, we designed and implemented FogAtlas, a modular platform to dynamically manage cloud-to-edge computing (and networking) resources [efficiency]
- Improve automation and introduce autonomic to enable failure-tolerance, robustness to misconfigurations and congestions. In this space, RiSING proposes methods to ensure resiliency of the cloud and network control planes, as well as models and algorithms to address network congestions (especially those caused by failures or disasters) [robustness]
- Evolve Software Defined Networks by means of novel solutions based on programmable data planes (e.g. P4 and eBPF) to perform network monitoring, packet filtering and anomaly mitigation. Investigate multi-layer encryption and communications based on quantum technologies [robustness and security]
- Application and Services:
- Study, develop and evaluate Security as a Service (SECaaS) applications to detect anomalies. RiSING is developing lightweight IDS/IPS applications for resource-constrained edge devices based on Artificial Intelligence techniques. Such applications are designed to work in collaboration with advanced fog computing and SDN technologies [security]
RiSING researchers have expertise in modelling complex processes and systems by means of instruments such as graph theory, game theory, machine learning algorithms, discrete and continuous optimization, etc. Research ideas are advanced to innovation by means of research assets based on widely-adopted open-source frameworks such as OpenStack, Kubernetes, ONOS and OpenDaylight, and more.