1,720,977 research outputs found
Social Network. Facebook, Twitter, YouTube e gli altri
No full textCosa sappiamo davvero dei social network del Web, ormai 2.5? Come hanno cambiato il nostro modo di concepire relazioni, lavoro, vita quotidiana? Da Facebook a YouTube, da Twitter a Flickr, un viaggio alla scoperta delle sempre più popolate piazze virtuali.What do we really know about Web 2.5Social Network. How did they change our attitudes towards relationships, business, everyday life? From Facebook to YouTube, from Twitter to Flickr, a journey discovering our more and more overcrowded virtual places
Social Network
No full textL'articolo descrive il contributo dei Soial Network di Internet all'evoluzione di nuove forme estetiche.The article describes the contribution of Internet Social Network to the shaping of new aesthetic forms
Using Distributed Reinforcement Learning for Resource Orchestration in a Network Slicing Scenario
Get PDFThe 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 slice 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 agent training is carried out following the Advantage Actor Critic algorithm, which permits 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
Design and Performance Evaluation of Service Overlay Networks Topologies
No full textNowadays, Internet still lacks of adequate support for QoS-sensitive applications, such as VoIP, Videoconference, and Video-on-Demand. In a large extent, this is due to the fact that Internet was originally designed to provide only a best-effort packet delivery service. In recent years, Service Overlay Networks (SONs) have emerged as a profitable way to leverage these issues without changing the underlying infrastructure. In this paper, we address the topology design problem of a SON from a performance point of view. Since the analytical solution of the problem is too computationally complex, we compare the performance of some well-known topologies and we also propose a new traffic demand aware overlay topology. Through extensive simulations, we investigate the performance of each overlay topology in different network scenarios, taking into account overhead and accepted traffic between the overlay nodes
5G-MEC Testbeds for V2X Applications
No full textFifth-generation (5G) mobile networks fulfill the demands of critical applications, such as Ultra-Reliable Low-Latency Communication (URLLC), particularly in the automotive industry. Vehicular communication requires low latency and high computational capabilities at the network's edge. To meet these requirements, ETSI standardized Multi-access Edge Computing (MEC), which provides cloud computing capabilities and addresses the need for low latency. This paper presents a generalized overview for implementing a 5G-MEC testbed for Vehicle-to-Everything (V2X) applications, as well as the analysis of some important testbeds and state-of-the-art implementations based on their deployment scenario, 5G use cases, and open source accessibility. The complexity of using the testbeds is also discussed, and the challenges researchers may face while replicating and deploying them are highlighted. Finally, the paper summarizes the tools used to build the testbeds and addresses open issues related to implementing the testbeds
Joint multi-objective MEH selection and traffic path computation in 5G-MEC systems
No full textMulti-access Edge Computing (MEC) is an emerging technology that allows to reduce the service latency and traffic congestion and to enable cloud offloading and context awareness. MEC consists in deploying computing devices, called MEC Hosts (MEHs), close to the user. Given the mobility of the user, several problems rise. The first problem is to select a MEH to run the service requested by the user. Another problem is to select the path to steer the traffic from the user to the selected MEH. The paper jointly addresses these two problems. First, the paper proposes a procedure to create a graph that is able to capture both network-layer and application-layer performance. Then, the proposed graph is used to apply the Multi-objective Dijkstra Algorithm (MDA), a technique used for multi-objective optimization problems, in order to find solutions to the addressed problems by simultaneously considering different performance metrics and constraints. To evaluate the performance of MDA, the paper implements a testbed based on AdvantEDGE and Kubernetes to migrate a VideoLAN application between two MEHs. A controller has been realized to integrate MDA with the 5G-MEC system in the testbed. The results show that MDA is able to perform the migration with a limited impact on the network performance and user experience. The lack of migration would instead lead to a severe reduction of the user experience
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Experimental Evaluation of Handover Strategies in 5G-MEC Scenario by using AdvantEDGE
No full textThe 5G-MEC architecture increases the heterogene-ity and dynamicity of the available resources, presenting unique and competing challenges to researchers, network designers, and application developers. Recent studies indicate AdvantEDGE as an interesting emulation platform to investigate these challenges. The paper presents a particular example of AdvantEDGE usage. A testbed composed of the emulated 5G-MEC architecture and the VideoLAN application allows to analyse the performance of alternative handover strategies, developed by using a multi-objective approach. The study shows how AdvantEDGE allows a deep analysis of the behaviour of the different strategies during the emulated user mobility, giving the possibility of measuring performance parameters at different layers, i.e. IP, application, and end-user
Experimental comparison of migration strategies for MEC-assisted 5G-V2X applications
Get PDFThe introduction of 5G technology enables new V2X services requiring reliable and extremely low latency communications. To satisfy these requirements computing elements need to be located at the edge of the network, according to the Multi-access Edge Computing (MEC) paradigm. The user mobility and the MEC approach lead to the need to carefully analysing the procedures for the migration of applications necessary to maintain the service proximity, fundamental to guarantee low latency. The paper provides an experimental comparison of three different migration strategies. The comparison is performed considering three different containerized MEC applications that can be used for developing V2X services. The experimental study is carried out by means of a testbed where the user mobility is emulated by the ETSI MEC Sandbox. The three strategies are compared considering the viability, the observed service downtime, and the amount of state preserved after the migration. The obtained results point out some trade-offs to consider in any migration scenario
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