• Identified SONNET scenarios and use-cases, system architecture, requirements and performance indicators
• Identified a Context-Aware Architecture for Self-Organization and context-based scheduling applications (figure 1)
• Developed a context-based battery priority scheduling algorithm for limited battery powered devices utilizing high data rate demanding applications.
• Proposed a Multi-domain SDN MEC architecture (figure 2) for resource provisioning. In particular, a deadlock aware algorithm for scheduling resources for Industrial IoT (IIoT) devices onto a MEC platform which incorporates the banker’s resource-request algorithm is proposed.
• Design and development of an energy-aware routing algorithm for SDN based Networks
We proposed a novel Temporal Resource-aware Routing Algorithm for SDN (STR-RA). Performance of the algorithm is verified using a GNS3 based implementation with an Opendaylight controller. The simulation results were compared against legacy RIP (Routing Information Protocols) and OSPF(Open Shortest Path First) protocols, where a gain of up to 6 orders of magnitude was observed in E2E (End-to-End) delay reduction.
• Design of SO-Network Sharing for heterogeneous networks (figure 3)
A mobile networking scenario was proposed that exploit the context-aware architecture paradigm, and SON module to gather context information about the user Signal-to-Noise and Interference in order to maximise the coverage-capacity of the network under a network sharing regime, as well to ensure energy efficient connectivity.
• Design of novel SO-CoMP transmission approaches for beyond 5G networks
SONNET implemented a hybrid approach based on centralized and distributed self-organized small cells that achieves low signalling overhead through direct small cell communication. The SON approach is shaped by two different optimization approaches, that include machine learning (ML) and game theory.
• An integrated SONNET testbed was developed, that is able to emulate interconnected heterogeneous infrastructures within a cloud based framework; this involved the integration of an in-house network (LSBU) and system level simulator (GS) with a commercial ray tracer tool (SIG). In particular, the SONNET deployment entertains a novel SO-KDN (Self-Organised Knowledge-Defined Networking) model which provides beyond-5G self-organization (Self-Optimization, Self-Configuration, Self-Healing and Self-Learning) on a Knowledge-Defined Network. A comprehensive set of simulation results were given too demonstrate how SO and machine learning in synergy can optimise network performance for the routing-as-a-service use-case.
The dissemination plan led to 32 published works (20 journals, 12 conference papers), 3 international workshops, and several key note talks and tutorials. The exploitation plan led to influencing the standards community through publication in the IEEE Communications Standards Magazine (SDN-Sim: Integrating a System-Level Simulator with a Software Defined Network; 4(1), March 2020). The scientifc outcomes also provided the basis for tutorials (for e.g. CollaborateCom 2019, AI-as-Service), and content for laboratory coursework (new experimentation problem-solving) that was included in the MSc program at the Uni. of Patras (Greece) and London South bank University (UK).
