a simulative model of a 5g telco operator network

Abstract In the near future, an important milestone for the evolution of wireless technologies will be the deployment of 5G network, having the target of supporting very huge data rate generated by a very high number of devices. One of the main technological enablers in this evolution is the joint SDN/NFV paradigm, defined in the last years to support the softwarization process of the Telco Operator networks. Given the very hard quality of experience (QoE) and quality of service (QoS) requirements in some application scenarios, mainly in terms of end-to-end delay, a challenging activity is to realize tools that can support network architects in performance evaluation and network design. With this in mind, this paper proposes a simulative tool for 5G networks, which is able to capture delay statistics due to both CPU load and transmission link congestions in NFVI-PoP nodes. The model is then applied to a case study to demonstrate how it can be applied for performance evaluation

S6: a Smart, Social and SDN-based Surveillance System for Smart-cities

Abstract In the last few years, Software Defined Networks (SDN) and Network Functions Virtualization (NFV) have been introduced in the Internet as a new way to design, deploy and manage networking services. Working together, they are able to consolidate and deliver the networking components using standard IT virtualization technologies not only on high-volume servers, but also in end user premises, Telco operator edge and access nodes thus allowing the emergence of new services. In this context, this paper presents a smart video surveillance platform designed to exploit the facilities offered by full SDN-NFV networks. This platform is based on free and open source software running on Provider Equipment (PE), so allowing function deployment simplification and management cost reduction

Design of an adaptive-rate video-streaming service with different classes of users

The provision of end-to-end Quality of Service (QoS) for multimedia services over IP-based networks is already an open issue. To achieve this goal, service providers need to manage Service Level Agreements (SLAs), which specify parameters of the services operation such as availability and performance. Additional mechanisms are needed to quantitatively evaluate the user-level SLA parameters. This work is focused on the evaluation and assessment of different design options of an adaptive VoD service providing several classes of users and fulfilling the SLA commitments. Based on a straightforward Markov Chain, Markov-Reward Chain (MRC) models are developed in order to obtain various QoS measures of the adaptive VoD service. The MRC model has a clear understanding with the design and operation of the VoD system.5th IFIP International Conference on Network Control & Engineering for QoS, Security and MobilityRed de Universidades con Carreras en Informática (RedUNCI

Design of an adaptive-rate video-streaming service with different classes of users

The provision of end-to-end Quality of Service (QoS) for multimedia services over IP-based networks is already an open issue. To achieve this goal, service providers need to manage Service Level Agreements (SLAs), which specify parameters of the services operation such as availability and performance. Additional mechanisms are needed to quantitatively evaluate the user-level SLA parameters. This work is focused on the evaluation and assessment of different design options of an adaptive VoD service providing several classes of users and fulfilling the SLA commitments. Based on a straightforward Markov Chain, Markov-Reward Chain (MRC) models are developed in order to obtain various QoS measures of the adaptive VoD service. The MRC model has a clear understanding with the design and operation of the VoD system.5th IFIP International Conference on Network Control & Engineering for QoS, Security and MobilityRed de Universidades con Carreras en Informática (RedUNCI

Design of an adaptive-rate video-streaming service with different classes of users

The provision of end-to-end Quality of Service (QoS) for multimedia services over IP-based networks is already an open issue. To achieve this goal, service providers need to manage Service Level Agreements (SLAs), which specify parameters of the services operation such as availability and performance. Additional mechanisms are needed to quantitatively evaluate the user-level SLA parameters. This work is focused on the evaluation and assessment of different design options of an adaptive VoD service providing several classes of users and fulfilling the SLA commitments. Based on a straightforward Markov Chain, Markov-Reward Chain (MRC) models are developed in order to obtain various QoS measures of the adaptive VoD service. The MRC model has a clear understanding with the design and operation of the VoD system.5th IFIP International Conference on Network Control & Engineering for QoS, Security and MobilityRed de Universidades con Carreras en Informática (RedUNCI

A P2P Platform for real-time multicast video streaming leveraging on scalable multiple descriptions to cope with bandwidth fluctuations

In the immediate future video distribution applications will increase their diffusion thanks tothe ever-increasing user capabilities and improvements in the Internet access speed and performance.The target of this paper is to propose a content delivery system for real-time streaming services based ona peer-to-peer approach that exploits multicast overlay organization of the peers to address thechallenges due to bandwidth heterogeneity. To improve reliability and flexibility, video is coded using ascalable multiple description approach that allows delivery of sub-streams over multiple trees andallows rate adaptation along the trees as the available bandwidth changes. Moreover, we have deployeda new algorithm for tree-based topology management of the overlay network. In fact, tree based overlaynetworks better perform in terms of end-to-end delay and ordered delivery of video flow packets withrespect to mesh based ones. We also show with a case study that the proposed system works better thansimilar systems using only either multicast or multiple trees

Battery Management in a Green Fog-Computing Node: a Reinforcement-Learning Approach

In the last years, Internet is evolving towards the cloud-computing paradigm complemented by fog-computing in order to distribute computing, storage, control, networking resources, and services close to end-user devices as much as possible, while sending heavy jobs to the remote cloud. When fog-computing nodes cannot be powered by the main electric grid, some environmental-friendly solutions, such as the use of solar- or wind-based generators could be adopted. Their relatively unpredictable power output makes it necessary to include an energy storage system in order to provide power, when a peak of work occurs during periods of low-power generation. An optimized management of such an energy storage system in a green fog-computing node is necessary in order to improve the system performance, allowing the system to cope with high job arrival peaks even during low-power generation periods. In this perspective, this paper adopts reinforcement learning to choose a server activation policy that ensures the minimum job loss probability. A case study is presented to show how the proposed system works, and an extensive performance analysis of a fog-computing node highlights the importance of optimizing battery management according to the size of the Renewable-Energy Generator system and the number of available servers