My research focuses on how we can better manage networked system infrastructures and resources.

Connected mobility solutions, data analytics for IoT services, ultra-high definition video streaming, all these emerging applications build upon complex networks of interconnected machines and devices to operate. Information exchanged through these networks is expected to be delivered almost instantaneously, with no losses, and at high rate.

Making sure that these complex networks provide the best performance is challenging: they involve very different types of software and hardware resources that need to work together, they span geographical areas ranging from few centimetres to thousands of kilometres, and they keep changing to adapt to new needs and requirements.

My work is contributing to developing new ways by which we can build, monitor, maintain and control these networks so as to make any type of digital applications a reality.

Keywords: digitisation of electric mobility; data logistics for connected mobility; knowledge-centric networking; software-based and programmable networks; network monitoring and management.

Ongoing projects

Data logistics for future mobility

This project investigates the challenges of interoperability for the integration between heterogeneous infrastructures – inter-domain; and between heterogeneous providers and operators - interstakeholder, in the context of connected and automated mobility ecosystem. It defines the notion of data logistics for converged energy, mobility and information systems.

Collaboration: Grantham Institute for Climate Change, Imperial College London

Network as a compute

The emergence of new digital services with applications such as sub-second data analytics, high-speed data feed delivery or high-performance computing is imposing stringent performance requirements on the networking infrastructures that support these services. This project is looking at how to take advantage of recent advances in dataplane programmability, with initiatives like P4, to offload some application computational tasks to the network, making in essence the network part of the application's workload compute cycle.

Keywords: programmable dataplane; P4; in-network computation

Past projects


EVOLVE is a multi-disciplinary programme of research that aims at engineering data-driven solutions to support future emobility infrastructures. Details can be found here.

Collaboration: Grantham Institute for Climate Change, Imperial College London

IXP management complexity

This project investigated the link between evaluating the complexity of operating typical network architectures and characterizing the knowledge that is required to configure and monitor these networks. It explored the use of standardised models of network functionality in the community (i.e., YANG models) to develop an operator-centric complexity evaluation framework.

Collaboration: IIJ Institute of Innovation, Tokyo, Japan

Network abstractions & intents

This project aimed at closing the loop in software-based networking environments between high-level business objectives dictating what is expected for the applications and services running on top of the network infrastructure and low-level commands driving the configuration of network resources. In this project, we were particularly interested in understanding how to design better abstraction(s) for network and management functions so as to reduce the complexity of today's network management practices.

Collaboration: Department of Electronic and Electrical Engineering, University College London
Keywords: intent-based networking; abstractions; northbound interface; software-based networks; interaction management

Adaptive network monitoring

This project focused on trade-offs for large-scale and efficient network monitoring. A key question that our work aimed to answer is: how to achieve accurate and timely network monitoring report collection while performing scalable and low-overhead statistics extraction? We specifically focused on two scenarios currently receiving a strong interest in the community, namely software-defined networks and software packet processing. Our main objective was to investigate how to take advantage of adaptive monitoring mechanisms to satisfy hardware constraints, while reducing potential accuracy degradation.

Collaboration: Department of Electronic and Electrical Engineering, University College London
Keywords: self-adaptive monitoring; decentralised monitoring; large-scale monitoring

SDN-based resource management

This project investigated from an architectural and functional point of view, the applicability of SDN-based approaches to network resource management. A key contribution of our research was the development of a novel SDN-based management and control framework to support both static and adaptive resource management applications, as well centralised/decentralised deployment. Its main feature lies in its modular design enabling a clear separation of concerns between control and management. In addition, to support communication in decentralised settings, we also developed a new signalling approach building on top well defined interfaces and re-usable functions. In parallel, we also investigated how to use the OpenFlow technology for realising flexible traffic management.

Keywords: adaptive resource management; SDN; OpenFlow; decentralised network management functionality

ISP-operated content delivery services

This research focused on the development of scalable and lightweight cache/content management approaches for ISP-operated content delivery services. A key contribution that resulted from our research efforts is a hybrid cache management approach for virtualised ISP networks, combining periodical proactive cache reconfiguration with distributed reactive cache replacement. We also developed a distributed approach based on the parallelisation of the decision-making process and the use of network partitioning to cluster the distributed decision-making points.

Keywords: content delivery service; cache management

Self-managed networks

This concerns the work carried out during my Ph.D. The objective of my thesis was to address, through realistic and specific in-network self-management applications, some of the main engineering challenges raised by the design and implementation of self-managed decentralised and adaptive networks. In this context, I proposed a novel framework for decentralised network resource management and demonstrated its functionality on three realistic use case scenarios for dynamic traffic engineering, energy efficiency and cache management in Internet Service Providers.

Keywords: self-managed networks; online traffic engineering; network energy savings

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