The maximum data throughput in a single mode optical fibre is a function of both the signal bandwidth and the wavelength-dependent signal-to-noise ratio (SNR). In this paper, we investigate the use of hybrid discrete Raman & rare-earth doped fibre amplifiers to enable wide-band signal gain, without spectral gaps between amplification bands. We describe the widest continuous coherent transmission bandwidth experimentally demonstrated to date of 16.83 THz, achieved by simultaneously using the S-, C-and L-bands. The variation of fibre parameters over this bandwidth, together with the hybrid amplification method result in a significant SNR wavelengthdependence. To cope with this, the signal was optimised for each SNR, wavelength and transmission band. By using a system-tailored set of geometrically shaped constellations, we demonstrate the transmission of 660⇥25 GBd channels over 40 km, resulting in a record single mode fibre net throughput of 178.08 Tbit/s. Index Terms-Broadband transmission system, high order modulation format, geometric shaping.

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Software defined networking (SDN) and flexible grid optical transport technology are two key technologies that allow network operators to customize their infrastructure based on application requirements and therefore minimizing the extra capital and operational costs required for hosting new applications. In this paper, for the first time we report on design, implementation & demonstration of a novel OpenFlow based SDN unified control plane allowing seamless operation across heterogeneous state-of-the-art optical and packet transport domains. We verify and experimentally evaluate OpenFlow protocol extensions for flexible DWDM grid transport technology along with its integration with fixed DWDM grid and layer-2 packet switching.

IoT requires cloud infrastructures for data analysis (e.g., temperature monitoring, energy consumption measurement, etc.). Traditionally, cloud services have been implemented in large datacentres in the core network. Core cloud offers highcomputational capacity with moderate response time, meeting the requirements of centralized services with low-delay demands. However, collecting information and bringing it into one core cloud infrastructure is not a long-term scalable solution, particularly as the volume of IoT devices and data is forecasted to explode. A scalable and efficient solution, both at the network and cloud level, is to distribute the IoT analytics between the core cloud and the edge of the network (e.g. first analytics on the edge cloud and the big data analytics on the core cloud). For an efficient distribution of IoT analytics and use of network resources, it requires to integrate the control of the transport networks (packet and optical) with the distributed edge and cloud resources in order to deploy dynamic and efficient IoT services. This paper presents and experimentally validates the first IoT-aware multi-layer (packet/optical) transport SDN and edge/cloud orchestration architecture that deploys an IoT-traffic control and congestion avoidance mechanism for dynamic distribution of IoT processing to the edge of the network (i.e., edge computing) based on the actual network resource state.

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