Learning strategies in modelling economic growth

Cornerstone economic growth models as the Solow-Swan model and their modern extensions normally assume the rate of population growth as exogenous without any explanation of the links between economic growth and most important demographic variables. Recently, some articles have presented models to explain many phenomena of population dynamics, including evolution and ageing. This paper is a first exercise to include endogenous population dynamics and learning strategies as ingredients of an economic growth model. The model includes two ways of learning that determinate economic growth: individual and social learning. We study the dynamics through computer simulations and we show that the model reflects some features of real economies.Economic Growth, Learning Strategies, Human Capital, Penna model

A Control Plane Enabling Automated and Fully Adaptive Network Traffic Monitoring With eBPF

The extended Berkeley Packet Filter (eBPF) enables the dynamic injection of user-defined processing logic at run-time in the Linux networking stack without disrupting any active monitoring process. This enables the selective extraction of only the traffic features that are needed in a given instant of time, which is what we define fully adaptive network traffic monitoring. However, eBPF programs require ad-hoc control plane routines for each specific scenario in order to orchestrate the underlying data plane and export the required metrics, resulting in potentially duplicated source codes to maintain, and creating the risk of deploying, at runtime, unverified user-defined code that controls the devices running the monitoring process. This paper presents a control plane that automatically adapts both its management tasks and data extraction methodologies based on the underlying data plane provided by the user, who can merely focus on the monitoring logic definition. The paper evaluates the performance of the control plane's modules and demonstrates the advantages, in terms of processing speed and memory consumption, of a fully-adaptive monitoring approach with respect to nProbe (a state-of-the-art solution), an adaptive and a non-adaptive methodology in eBPF. Experiments prove that the control plane monitoring options do not significantly affect the underlying data plane (0.15% degraded throughput) and leverage the most efficient extraction primitives (20x faster execution time). Moreover, the fully-adaptive monitoring leads to a higher number of processed packets (10x) and significantly lower memory occupancy (10x) when extracting the smallest set of features

A proof-of-concept 5G mobile gateway with eBPF

In this poster we propose the first proof-of-concept open-source implementation of a 5G Mobile Gateway based on eBPF/XDP and present benchmarks that compare its performance with alternative technologies. We show how it outperforms other in-kernel solutions (e.g., OvS) and is comparable with DPDK-based platforms

Providing Telco-oriented Network Services with eBPF: The Case for a 5G Mobile Gateway

Although several technologies exist for high-speed data plane processing, such as DPDK, the above technologies require a rigid partitioning of the resources of the system, such as dedicated CPU cores and network interfaces. Unfortunately, this is not always possible when running at the edge of the network, in which a few servers are available in each cluster and a mixture of data and control plane services must coexist on the same hardware. In this respect, eBPF can become a better alternative thanks to its integration in the vanilla Linux kernel, which enables contemporary support for data and control plane services, hence enabling a more efficient usage of the (scarce) computing resources. This paper proposes the first proof-of-concept open-source implementation of a 5G Mobile Gateway based on eBPF/XDP, highlighting the possible challenges (e.g., to create traffic policers, as buffering is not available in eBPF) and the resulting architecture. The result is characterized in terms of performance and scalability and compared with alternative technologies, showing that it outperforms other in-kernel solutions (e.g., Open vSwitch) and is comparable with DPDK-based platforms

Why New Car Dealers Sell Used Cars: A Structural Analysis of the Impact of Used Car Markets on the Automobile Distribution Channel

Most new car dealers also sell used cars from the same physical location. Used cars sold by these dealers are relatively good substitutes for new cars and thus, could compete with the new cars sold by the dealers. Previous empirical research on the automobile market has mostly ignored the presence of the used car market while the analytical literature provides ambivalent suggestions. In this paper, we study how the availability of used cars at new car dealers affects the substitution between new and used cars as well as how it affects the margins and profits obtained by the dealer and manufacturer. Using a transaction level dataset which contains both new and used car transactions, we perform a detailed empirical analysis to understand how the existence of the used car markets affect the new car market as well as the channel members. We build a full equilibrium structural model of new and used car competition with profit maximizing manufacturers and dealers. Using the estimated model we quantify the substitutability between new and used cars and compare it with a more conventional demand model which considers new cars only. We then proceed to analyze whether dealers consider the substitutability between new and used cars to shed light on how dealers price their cars. We then contrast the distribution of profits between the manufacturer and dealer to understand how the used markets affect the distribution of power in the channel. Our results indicate that the new car prices have a higher impact on used car demand than used car prices have on new car demand. We also find that the ability to price and sell used cars gives the dealer higher margins on new cars and increases their power in the channel

Automatic Configuration of Opaque Network Functions in CMS

Cloud Management Systems (CMS) such as OpenStack are commonly used to manage IT resources such as computing and storage in large datacenters. Recently, CMS are starting to offer customers also the possibility to customize their network infrastructure, allowing each tenant to build his virtual network made of elementary blocks such as traffic monitors, switches, routers, firewalls, and more. However, tenants have to choose those network services among the list of services made available by the CMS and have no possibilities to customize the applications they want. This paper examines some of the modifications required in CMS to support a tenant-centric network service model, in which each tenant can install and configure their preferred network functions, without being limited to use only the list provided by the CMS. A prototype implementation validates the proposed approach and demonstrates the extent of the modifications in terms of languages and software components