Application, validation and comparison in different geographical contexts of an integrated model for the design of ecological networks

The issue of the fragmentation of natural habitats is increasingly at the core of the scientific debate, yet it is not taken into account in planning tools, with particular reference to the dynamism and complexity of landscapes. As it has been recognised at a European level, in order to enable different species to remain in good functional status, a network of green infrastructures is required. The concept of “ecological island” is no longer sufficient to adequately protect the fauna and the ecosystem it lives in. As a consequence, ecological islands must turn into ecological networks. The Ecological connectivity refers to the way habitats are physically connected to each other and how easy it is for species to move in. Good ecological connectivity is fundamental to the effective conservation of biodiversity considering that most species and ecological functions provided by ecosystems (ecosystem services) require a much wider space than that available within the boundaries of a single protected area. The main objective of this paper is to critically compare the application of a model for the design of ecological networks to two very different environmental contexts. This model was first tested in a Mediterranean area (the Province of Reggio Calabria) in 2008; the goal was to integrate the traditional (physiographic and functional) approaches into the design of ecological networks by taking into account biological and orographic elements as well as the anthropic structure of the territory. In 2011, within the ECONNECT European project, the model was applied to the pilot region of South-Western Alps (including the French region of Provence-Alpes - Côte d’Azur and the Italian regions Piedmont and Liguria), which is one of the richest transnational districts in Europe in terms of biodiversity. In such a region, the issue of multidisciplinary ecological connectivity was tackled in order to provide a series of proposals aiming at the development of the ecological potential of the area. The two applications allowed to further investigate the strengths and weaknesses of the implemented model by integrating its validation with information on faunal presence, which obviated one of the major limitations occurred in the first application

Experimental Evaluation of Dynamic Resource Orchestration in Multi-Layer (Packet over Flexi-Grid Optical) Networks?

This paper has been presented at : ONDM 2019 23rd Conference on Optical Network Design and ModellingIn future 5G infrastructures, network services will be de- ployed through sets of Virtual Network Functions (VNFs) leveraging the advantages of both Software Defined Networking (SDN) and Net- work Function Virtualization (NFV). A network service is composed of an ordered sequence of VNFs, i.e., VNF Forwarding Graph (VNFFG), deployed across distributed data centers (DCs). Herein, we present a Cloud/Network Orchestrator which dynamically processes and accom- modates VNFFG requests over a pool of DCs interconnected by a multi- layer (packet/flexi-grid optical) transport network infrastructure. We propose two different cloud and network resource allocation algorithms aiming at: i) minimizing the distance between the selected DCs, and ii) minimizing the load (i.e., consumed cloud resources) of the chosen DCs. Both algorithms run on a Cloud/Network Orchestrator and are ex- perimentally validated and benchmarked on the CTTC ADRENALINE testbed.This work is partially funded by the EU H2020 5G TRANSFORMER project (761536) and the Spanish AURORAS project (RTI2018-099178

Modeling microevolution in a changing environment: The evolving quasispecies and the Diluted Champion Process

Several pathogens use evolvability as a survival strategy against acquired immunity of the host. Despite their high variability in time, some of them exhibit quite low variability within the population at any given time, a somehow paradoxical behavior often called the evolving quasispecies. In this paper we introduce a simplified model of an evolving viral population in which the effects of the acquired immunity of the host are represented by the decrease of the fitness of the corresponding viral strains, depending on the frequency of the strain in the viral population. The model exhibits evolving quasispecies behavior in a certain range of its parameters, ans suggests how punctuated evolution can be induced by a simple feedback mechanism.Comment: 15 pages, 12 figures. Figures redrawn, some additional clarifications in the text. To appear in Journal of Statistical Mechanics: Theory and Experimen

A new data-driven framework to select the optimal replenishment strategy in complex supply chains

- Part of special issue: 10th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2022: Nantes, France, 22-24 June 2022. Edited by Alain Bernard, Alexandre Dolgui, Hichem Haddou Benderbal, Dmitry Ivanov, David Lemoine, Fabio Sgarbossa - Copyright © 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)Motivated by the high variability of markets occurred in the last years, which in turns determined significant uncertainty in lead times and supply chain dynamics, this paper introduces a data-driven framework based on machine learning and metaheuristic optimization to dynamically select the most suitable replenishment strategy for a complex two-echelon (supplier-inventory-factory) supply chain (SC) problem with perishable product and stochastic lead times. Since the supplier dispatches the product (i.e., the raw material) with a fixed expiration date, the product shelf-life strictly depends on the related delivery lead time, which is subject to uncertainty. In addition, a minimum order quantity has to be fulfilled and the time between two consecutive orders cannot be less than one month. The aim of the work is to select the most suitable replenishment strategy able to minimize the average stock level, which is a surrogate cost metric, while respecting a target fill rate. Considering a smoothing order-up-to policy, the data-driven prediction-optimization framework makes use of Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to select the best replenishment parameters (i.e., forecasting factor, proportional controller and safety stock factor) able to dynamically enhance the SC economic performance under the fill rate constraint. The ability of the framework under the predictive and the optimization perspective is assessed and a sensitivity analysis on the influence of replenishment parameters is presented as well

Experimental Evaluation of Orchestrating Inter-DC Quality-enabled VNFFG Services in Packet/Flexi-Grid Optical Networks

44th European Conference on Optical Communications (ECOC 2018)An implemented Cloud/Network Orchestrator to dynamically serve VNFFGs in remote DCs through a Multi-Layer Network (packet/flexi-grid optical) is evaluated. Two network information and path computation approaches are adopted by the Orchestrator being experimentally benchmarked with a number of performance metrics.This work is partially funded by the Spanish MINECO DESTELLO project (TEC2015-69256-R) and the EU H2020 5G TRANSFORMER project (761536)

Latency-Aware Network Service Orchestration over an SDN-Controlled Multi-Layer Transport Infrastructure

In this paper, we present latency-aware orchestration strategies that jointly consider satisfying both the allocation of computing resources (in distributed DCs) and the bandwidth and latency networks requirements, which are experimentally evaluated within a Multi-Layer (Packet over Optical Flexi-Grid) Transport Network and considering different DC set-ups and capabilities.This work is partially funded by the EU H2020 5G TRANSFORMER project (761536)

Latency-aware resource orchestration in SDN-based packet over optical flexi-grid transport networks

In the upcoming 5G networks and following the emerging Software Defined Network/Network Function Virtualization (SDN/NFV) paradigm, demanded services will be composed of a number of virtual network functions that may be spread across the whole transport infrastructure and allocated in distributed Data Centers (DCs). These services will impose stringent requirements such as bandwidth and end-to-end latency that the transport network will need to fulfill. In this paper, we present an orchestration system devised to select and allocate virtual resources in distributed DCs connected through a multi-layer (Packet over flexi-grid optical) network. Three different on-line orchestration algorithms are conceived to accommodate the incoming requests by satisfying computing, bandwidth and end-to-end latency constraints, setting up multi-layer connections. We addressed end-to-end latency requirements by considering both network (due to propagation delay) and processing delay components. The proposed algorithms have been extensively evaluated and assessed (via a number of figures of merit) through experimental tests carried out in a Packet over Optical Flexi-Grid Network available in the ADRENALINE testbed with emulated DCs connected to it.This work has been partially funded by the EC H2020 5GTransformer Project (grant No. 761536)

Spatio-temporal analysis of the urban–rural gradient structure: an application in a Mediterranean mountainous landscape (Serra San Bruno, Italy)

Abstract. The most recent and significant transformations of European landscapes have occurred as a consequence of a series of diffused, varied and often connected phenomena: urban growth and sprawl, agricultural intensification in the most suitable areas and agricultural abandonment in marginal areas. These phenomena can affect dramatically ecosystems' structure and functioning, since certain modifications cause landscape fragmentation while others tend to increase homogeneity. Thus, a thorough comprehension of the evolution trends of landscapes, in particular those linked to urban-rural relations, is crucial for a sustainable landscape planning. In this framework, the main objectives of the present paper are: (a) to investigate Land Use/Land Cover (LULC) transformations and dynamics that occurred over the period 1955–2006 in the municipality of Serra San Bruno (Calabria, Italy), an area particularly representative of the Mediterranean mountainous landscape; (b) to compare the settlement growth with the urban planning tools in charge in the study area; (c) to examine the relationship between urban–rural gradient, landscape metrics, demographic and physical variables; (d) to investigate the evolution of urban–rural gradient composition and configuration along significant axes of landscape changes. Data with a high level of detail (minimum mapping unit 0.2 ha) were obtained through the digitisation of historical aerial photographs and digital orthophotos identifying LULC classes according to the Corine Land Cover legend. The investigated period was divided into four significant time intervals, which were specifically analysed to detect LULC changes. Differently from previous studies, in the present research the spatio-temporal analysis of urban–rural gradient was performed through three subsequent steps: (1) kernel density analysis of settlements; (2) analysis of landscape structure by means of metrics calculated using a moving window method; (3) analysis of composition and configuration of the urban–rural gradient within three landscape profiles located along significant axes of LULC change. The use of thematic overlays and transition matrices enabled a precise identification of the LULC changes that had taken place over the examined period. As a result, a detailed description and mapping of the landscape dynamics were obtained. Furthermore, landscape profiling technique, using continuous data, allowed an innovative and valuable approach for analysing and interpreting urban–rural gradient structure over space and time