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Multi-access Edge Computing (MEC) is an essential technology for the fifth generation (5G) of mobile networks. MEC enables low-latency services by bringing computing resources close to the end-users. The integration of 5G and MEC technologies provides a favorable platform for a wide range of applications, including various mission-critical applications, such as smart grids, industrial internet, and telemedicine, which require high dependability and security. Ensuring both security and dependability is a complex and critical task, and not achieving the necessary goals can lead to severe consequences. Joint modeling can help to assess and achieve the necessary requirements. Under these motivations, we propose an extension of a two-level availability model for a 5G-MEC system. In comparison to the existing work, our extended model (i) includes the failure of the connectivity between the 5G-MEC elements and (ii) considers attacks against the 5G-MEC elements or their interconnection. We implement and run the model in M\"{o}bius. The results show that a three-element redundancy, especially of the management and core elements, is needed and still enough to reach around 4-nines availability even when connectivity and security are considered. Moreover, the evaluation shows that slow detection of attacks, slow recovery from attacks, and bad connectivity are the most significant factors that influence the overall system availability., Comment: 18 pages, 11 figures

Multi-access Edge Computing (MEC) is one of the enabling technologies of the fifth generation (5G) of mobile networks. MEC enables services with strict latency requirements by bringing computing capabilities close to the users. As with any new technology, the dependability of MEC is one of the aspects that need to be carefully studied. In this paper, we propose a two-level model to compute the availability of a 5G-MEC system. We then use the model to evaluate the availability of a 5G-MEC system under various configurations. The results show that having a single redundancy of the 5G-MEC elements leads an acceptable availability. To reach a high availability, the software failure intensity of the management elements of 5G and MEC should be reduced., Comment: 10 pages, 11 figures, 3 tables. Accepted to be published at the 32nd International Conference on Computer Communications and Networks (ICCCN 2023)

The Fifth Generation (5G) of mobile networks offers new and advanced services with stricter requirements. Multi-access Edge Computing (MEC) is a key technology that enables these new services by deploying multiple devices with computing and storage capabilities at the edge of the network, close to end-users. MEC enhances network efficiency by reducing latency, enabling real-time awareness of the local environment, allowing cloud offloading, and reducing traffic congestion. New mission-critical applications require high security and dependability, which are rarely addressed alongside performance. This survey paper fills this gap by presenting 5G MEC's three aspects: security, dependability, and performance. The paper provides an overview of MEC, introduces taxonomy, state-of-the-art, and challenges related to each aspect. Finally, the paper presents the challenges of jointly addressing these three aspects., Comment: 39 pages, 12 figures, 15 tables. This paper is published at IEEE Access (https://ieeexplore.ieee.org/document/10158694)

The Network Slicing (NS) paradigm enables the partition of physical and virtual resources among multiple logical networks, possibly managed by different tenants. In such a scenario, network resources need to be dynamically allocated according to the slices' requirements. In this paper, we attack the above problem by exploiting a Deep Reinforcement Learning approach. Our framework is based on a distributed architecture, where multiple agents cooperate towards a common goal. The agents' training is carried out following the Advantage Actor Critic algorithm, which allows to handle continuous action spaces. By means of extensive simulations, we show that our approach yields better performance than both a static allocation of system resources and an efficient empirical strategy. At the same time, the proposed system ensures high adaptability to different scenarios without the need for additional training., Comment: 14 pages, 11 figures, 4 tables. This paper is under review at IEEE Transaction on Networking. Copyright IEEE 2021

Software-defined networking (SDN) promises to improve the programmability and flexibility of networks, but it may bring also new challenges that need to be explored. One open issue is the quantitative assessment of the properties of SDN backbone networks to determine whether they can provide similar availability to the traditional IP backbone networks. To achieve this goal, a two-level availability model that is able to capture the global network connectivity without neglecting the essential details and which includes a failure correlation assessment should be considered. The two-level availability model is composed by a structural model and the dynamic models of the principal minimal-cut sets of the network. The purpose of this technical report is to extensively present the implementation on M\"obius of the Stochastic Activity Network (SAN) availability model of the network elements and the principal minimal-cut sets of a SDN backbone network and the corresponding traditional backbone network., Comment: IIK, NTNU, Tech. Rep., March 2017

Software-defined networking (SDN) promises to improve the programmability and flexibility of networks, but it may bring also new challenges that need to be explored. The purpose of this technical report is to assess how the deployment of the SDN controllers affects the overall availability of SDN. For this, we have varied the number, homing and location of SDN controllers. A two-level modelling approach that is used to evaluate the availability of the studied scenarios. Our results show how network operators can use the approach to find the optimal cost implied by the connectivity of the SDN control platform by keeping high levels of availability., Comment: Department of Telematics, NTNU, Tech. Rep., March 2016