Experimental comparison of migration strategies for MEC-assisted 5G-V2X applications

The 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.acceptedVersio

5G-MEC Testbeds for V2X Applications

Fifth-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.publishedVersio

5G Multi-access Edge Computing: Security, Dependability, and Performance

The main innovation of the Fifth Generation (5G) of mobile networks is the ability to provide novel services with new and stricter requirements. One of the technologies that enable the new 5G services is the Multi-access Edge Computing (MEC). MEC is a system composed of multiple devices with computing and storage capabilities that are deployed at the edge of the network, i.e., close to the end users. MEC reduces latency and enables contextual information and real-time awareness of the local environment. MEC also allows cloud offloading and the reduction of traffic congestion. Performance is not the only requirement that the new 5G services have. New mission-critical applications also require high security and dependability. These three aspects (security, dependability, and performance) are rarely addressed together. This survey fills this gap and presents 5G MEC by addressing all these three aspects. First, we overview the background knowledge on MEC by referring to the current standardization efforts. Second, we individually present each aspect by introducing the related taxonomy (important for the not expert on the aspect), the state of the art, and the challenges on 5G MEC. Finally, we discuss the challenges of jointly addressing the three aspects.Comment: 33 pages, 11 figures, 15 tables. This paper is under review at IEEE Communications Surveys & Tutorials. Copyright IEEE 202

The impact of the access point power model on the energy-efficient management of infrastructured wireless LANs

The reduction of the energy footprint of large and mid-sized IEEE 802.11 access networks is gaining momentum. When operating at the network management level, the availability of an accurate power model of the APs becomes of paramount importance, because different detail levels have a non-negligible impact on the performance of the optimisation algorithms. The literature is plentiful of AP power models, and choosing the right one is not an easy task. In this paper we report the outcome of a thorough study on the impact that various inflections of the AP power model have when minimising the energy consumption of the infrastructure side of an enterprise wireless LAN. Our study, performed on several network scenarios and for various device energy profiles, reveals that simple one- and two-component models can provide excellent results in practically all cases. Conversely, employing accurate and detailed power models rarely offers substantial advantages in terms of power reduction, but, on the other hand, makes the solving algorithms much slower to execute

Power-Aware Routing and Network Design with Bundled Links: Solutions and Analysis

The paper deeply analyzes a novel network-wide power management problem, called Power-Aware Routing and Network Design with Bundled Links (PARND-BL), which is able to take into account both the relationship between the power consumption and the traffic throughput of the nodes and to power off both the chassis and even the single Physical Interface Card (PIC) composing each link. The solutions of the PARND-BL model have been analyzed by taking into account different aspects associated with the actual applicability in real network scenarios: (i) the time for obtaining the solution, (ii) the deployed network topology and the resulting topology provided by the solution, (iii) the power behavior of the network elements, (iv) the traffic load, (v) the QoS requirement, and (vi) the number of paths to route each traffic demand. Among the most interesting and novel results, our analysis shows that the strategy of minimizing the number of powered-on network elements through the traffic consolidation does not always produce power savings, and the solution of this kind of problems, in some cases, can lead to spliting a single traffic demand into a high number of paths

Joint multi-objective MEH selection and traffic path computation in 5G-MEC systems

Multi-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.publishedVersio

Experimental Evaluation of Handover Strategies in 5G-MEC Scenario by using AdvantEDGE

The 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

Optimal Access Point Power Management for Green IEEE 802.11 Networks

In this paper, we present an approach and an algorithm aimed at minimising the energy consumption of enterprise Wireless Local Area Networks (WLANs) during periods of low user activity. We act on two network management aspects: powering off some Access Points (APs), and choosing the level of transmission power of each AP. An efficient technique to allocate the user terminals to the various APs is the key to achieving this goal. The approach has been formulated as an integer programming problem with nonlinear constraints, which comes from a general but accurate characterisation of the WLAN. This general problem formulation has two implications: the formulation is widely applicable, but the nonlinearity makes it NP-hard. To solve this problem to optimality, we devised an exact algorithm based on a customised version of Benders’ decomposition method. The computational results proved the ability to obtain remarkable power savings. In addition, the good performance of our algorithm in terms of solving times paves the way for its future deployment in real WLANs.publishedVersio

Neurotransmitter evaluation in the hippocampus of rats after intracerebral injection of TsTX scorpion toxin

TsTX is an a-type sodium channel toxin that stimulates the discharge of neurotransmitters from neurons. In the present study we investigated which neurotransmitters are released in the hippocampus after TsTX injection and if they are responsible for electrographic or histopathological effects. Microdialysis revealed that the toxin increased glutamate extracellular levels in the hippocampus; however, levels of gamma-aminobutyric acid (GABA), glycine, 5-hydroxyindoleacetic acid (5-HIAA), homovanillic acid (HVA) and 3,4-dihydroxyphenylacetic acid (DOPAC) were not significantly altered. Neurodegeneration in pyramidal cells of hippocampus and electroencephalographic alterations caused by the toxin were blocked by pretreatment with riluzole, a glutamate release inhibitor. The present results suggest a specific activity of TsTX in the hippocampus which affects only glutamate releas