Le infrastrutture viarie dismesse o declassate ed il progetto di paesaggio

Paesaggio ed infrastrutture viarie sono un binomio molto forte: il primo ha insito il concetto di accessibilità, in quanto non può esistere senza la presenza di un osservatore; la strada, invece, trova i fattori che la connotano nel suo rapporto con la morfologia su cui insiste. Le infrastrutture viarie sono elemento strutturale e strutturante non solo di un territorio, ma anche di un paesaggio. Le attuali esigenze di mobilità portano oggi a ripensare ed adeguare molte infrastrutture viarie: laddove è possibile si potenziano le strutture esistenti, in diversi casi si ricorre a nuovi tracciati o a varianti di percorso. Porsi il problema di conservare itinerari testimoni della cultura materiale ed economica di una società implica considerazioni articolate, che travalicano i limiti del sedime: una via è un organismo più complesso della semplice linea di trasporto in quanto implica tutta una serie di manufatti a supporto della mobilità e soprattutto il corridoio infrastrutturale che genera e caratterizza, ovvero una porzione variabile di territorio definita sia dal tracciato che dalla morfologia del contesto. L’evoluzione dei modelli produttivi ed economici, che oggi porta quote sempre maggiori di popolazione a passare un tempo sempre minore all’interno del proprio alloggio, rende la riflessione sulle infrastrutture viarie dismesse o declassate occasione per la progettazione di spazi per l’abitare collettivo inseriti in contesti paesaggistici, tanto urbani che rurali, tramite reti di percorsi pensate per assorbire tagli di mobilità specifici e peculiari. Partendo da queste riflessioni la Tesi si articola in: Individuazioni del contesto teorico e pratico: Lo studio mette in evidenza come la questione delle infrastrutture viarie e del loro rapporto con il paesaggio implichi riflessioni incrociate a diversi livelli e tramite diverse discipline. La definizione dello spazio fisico della strada passa infatti per la costruzione di un itinerario, un viaggio che si appoggia tanto ad elementi fisici quanto simbolici. La via è un organismo complesso che travalica il proprio sedime per coinvolgere una porzione ampia di territorio, un corridoio variabile ed articolato in funzione del paesaggio attraversato. Lo studio propone diverse chiavi di lettura, mettendo in luce le possibili declinazioni del tema, in funzione del taglio modale, del rapporto con il contesto, del regime giuridico, delle implicazioni urbanistiche e sociali. La mobilità dolce viene individuata quale possibile modalità di riuso, tutela e recupero, del patrimonio diffuso costituito dalle diversi reti di viabilità. Antologia di casi studio: Il corpo principale dello studio si basa sulla raccolta, analisi e studio dello stato dell’arte nel settore; gli esempi raccolti sono presentati in due sezioni: la prima dedicata alle esperienze più significative ed articolate, che affrontano il recupero delle infrastrutture viarie a più livelli ed in modo avanzato non concentrandosi solo sulla conversione del sedime, ma proponendo un progetto che coinvolga tutto il corridoio attraversato dall’infrastruttura; la seconda parte illustra la pratica corrente nelle diverse realtà nazionali, ponendo in evidenza similitudini e differenze tra i vari approcci.

Energy-efficient virtual machine placement in data centers by genetic algorithm

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.

A hybrid genetic algorithm for the energy-efficient virtual machine placement problem in data centers

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation technology. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches consider the energy consumption by physical machines only, but do not consider the energy consumption in communication network, in a data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement. In our preliminary research, we have proposed a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both physical machines and the communication network in a data center. Aiming at improving the performance and efficiency of the genetic algorithm, this paper presents a hybrid genetic algorithm for the energy-efficient virtual machine placement problem. Experimental results show that the hybrid genetic algorithm significantly outperforms the original genetic algorithm, and that the hybrid genetic algorithm is scalable.

Remote sensing and core data needed to support planning and policy decision making

A variety of sustainable development research efforts and related activities are attempting to reconcile the issues of conserving our natural resources without limiting economic motivation while also improving our social equity and quality of life. Land use/land cover change, occurring on a global scale, is an aggregate of local land use decisions and profoundly impacts our environment. It is therefore the local decision making process that should be the eventual target of many of the ongoing data collection and research efforts which strive toward supporting a sustainable future. Satellite imagery data is a primary source of data upon which to build a core data set for use by researchers in analyzing this global change. A process is necessary to link global change research, utilizing satellite imagery, to the local land use decision making process. One example of this is the NASA-sponsored Regional Data Center (RDC) prototype. The RDC approach is an attempt to integrate science and technology at the community level. The anticipated result of this complex interaction between research and the decision making communities will be realized in the form of long-term benefits to the public.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

Using genetic algorithm in profile-based assignment of applications to virtual machines for greener data centers

The increase in data center dependent services has made energy optimization of data centers one of the most exigent challenges in today's Information Age. The necessity of green and energy-efficient measures is very high for reducing carbon footprint and exorbitant energy costs. However, inefficient application management of data centers results in high energy consumption and low resource utilization efficiency. Unfortunately, in most cases, deploying an energy-efficient application management solution inevitably degrades the resource utilization efficiency of the data centers. To address this problem, a Penalty-based Genetic Algorithm (GA) is presented in this paper to solve a defined profile-based application assignment problem whilst maintaining a trade-off between the power consumption performance and resource utilization performance. Case studies show that the penalty-based GA is highly scalable and provides 16% to 32% better solutions than a greedy algorithm.

Cost-efficient virtual machine management in data centers

Virtual Machine (VM) management is an obvious need in today's data centers for various management activities and is accomplished in two phases— finding an optimal VM placement plan and implementing that placement through live VM migrations. These phases result in two research problems— VM placement problem (VMPP) and VM migration scheduling problem (VMMSP). This research proposes and develops several evolutionary algorithms and heuristic algorithms to address the VMPP and VMMSP. Experimental results show the effectiveness and scalability of the proposed algorithms. Finally, a VM management framework has been proposed and developed to automate the VM management activity in cost-efficient way.