The wide adoption of the recently coined fog and edge computing paradigms alongside conventional cloud computing creates a novel scenario, known as the cloud continuum, where services may benefit from the overall set of resources to optimize their execution. To operate successfully, such a cloud continuum scenario demands for novel management strategies, enabling a coordinated and efficient management of the entire set of resources, from the edge up to the cloud, designed in particular to address key edge characteristics, such as mobility, heterogeneity and volatility. The design of such a management framework poses many research challenges and has already promoted many initiatives worldwide at different levels. In this paper we present the results of one of these experiences driven by an EU H2020 project, focusing on the lessons learnt from a real deployment of the proposed management solution in three different industrial scenarios. We think that such a description may help understand the benefits brought in by a holistic cloud continuum management and also may help other initiatives in their design and development processes.

Multiprotocol label switching and traffic engineering are proposed by the IETF to improve the network performance. Moreover, some QoS routing algorithms must be added in order to optimize the path selection process. However, in highly dynamic large networks, existing QoS routing algorithms suffer from a blocking probability, which in part is due to the existence of inaccuracy in the network state information used to select the path. This paper deals with the BYPASS based routing mechanism, which was introduced in the previous paper to overcome this routing inaccuracy effect in IP/MPLS scenarios. We suggest an enhancement of the BBR mechanism to optimize the bandwidth allocation by balancing the path length and the residual bandwidth, and its performance is evaluated by simulation.

The wide adoption of the recently coined fog and edge computing paradigms alongside conventional cloud computing creates a novel scenario, known as the cloud continuum, where services may benefit from the overall set of resources to optimize their execution. To operate successfully, such a cloud continuum scenario demands for novel management strategies, enabling a coordinated and efficient management of the entire set of resources, from the edge up to the cloud, designed in particular to address key edge characteristics, such as mobility, heterogeneity and volatility. The design of such a management framework poses many research challenges and has already promoted many initiatives worldwide at different levels. In this paper we present the results of one of these experiences driven by an EU H2020 project, focusing on the lessons learnt from a real deployment of the proposed management solution in three different industrial scenarios. We think that such a description may help understand the benefits brought in by a holistic cloud continuum management and also may help other initiatives in their design and development processes.

This contribution deals with the RWA (routing and wavelength assignment) in semi-transparent optical networks. In semi-transparent networks, a parameter called maximum transmission distance (MTD) is used to indicate the distance reachable in wavelength continuity. When for a given lightpath, the signal cannot be detected at the destination node a regenerator has to be installed in an intermediate node. The regenerator breaks up the optical continuity and the optical network becomes a semi-transparent optical network. The new RWA mechanism proposed in this paper will take into account the physical impairment such as the Maximum Transmission Distance (MTD). Moreover this new RWA algorithm will be based on the Prediction-Based Routing (PBR) mechanism and will take into account the routing inaccuracy problem. The goal of the proposed algorithm will be both, to reduce the number of blocked connections due to the routing inaccuracy problem and to select routes that fulfil the MTD physical impairment.

Usual QoS routing algorithms involve the periodic update of network state information in all the network nodes. Based on this knowledge the QoS routing algorithms select the `best' route. It has been shown in the literature that the performance of these QoS routing algorithms strongly depends on the frequency of updating. We propose a new QoS routing mechanism called Prediction-Based Routing based on predicting the availability of links and routes regardless from the network state information. Consequently, update messages are not required, hence reducing signalling overhead and providing a major enhancement in terms of scalability. We show that the PBR is a viable option compared with usual QoS routing algorithms from the point of view of performance, complexity ad signalling overhead.