33,849 research outputs found

    Managerial decisions to recover from Covid-19 disruption: A multi-objective optimization approach applied to public transport operators

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    The resilience of transport systems, facing natural or man-made disruptions, has been widely discussed in literature in terms of recovery capabilities concerning infrastructures, suggesting solutions to provide users an acceptable level of service along the interrupted network. However, in the context of the Covid-19 outbreak, the disruption has stressed the resilience of transport systems not on the supply side but rather at organizational level for transport service providers. Indeed, the sudden and drastic decrease in users due to the restrictions imposed by governments to limit the pandemic spread has implicated severe economic consequences in the running of transport companies. In this paper, attention has been focused on the public transport sector to analyse the effects of different initiatives, which companies could undertake in response to the demand shock caused by the Covid-19 emergency. Notably, an optimization procedure has been developed with the aim of determining feasible Pareto-front solutions, which correspond to trade-off conditions for the concurrent maximization of the company profit and the minimization of outsourcing services. The time span necessary to implement the examined recovery measures has been considered together with the limitation to appropriate threshold values for the main cost and income items influencing the company operations management. The proposed approach has been applied to the case study of an Italian public transport company to appraise different post-Covid-19 resilience strategies

    Semantic reasoning for intelligent emergency response applications

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    Emergency response applications require the processing of large amounts of data, generated by a diverse set of sensors and devices, in order to provide for an accurate and concise view of the situation at hand. The adoption of semantic technologies allows for the definition of a formal domain model and intelligent data processing and reasoning on this model based on generated device and sensor measurements. This paper presents a novel approach to emergency response applications, such as fire fighting, integrating a formal semantic domain model into an event-based decision support system, which supports reasoning on this model. The developed model consists of several generic ontologies describing concepts and properties which can be applied to diverse context-aware applications. These are extended with emergency response specific ontologies. Additionally, inference on the model performed by a reasoning engine is dynamically synchronized with the rest of the architectural components. This allows to automatically trigger events based on predefined conditions. The proposed ontology and developed reasoning methodology is validated on two scenarios, i.e. (i) the construction of an emergency response incident and corresponding scenario and (ii) monitoring of the state of a fire fighter during an emergency response

    Putting Gross National Happiness in the Service of Good Development

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    Gross National Happiness (GNH) has only recently appeared on the international stage, yet it was immediately met with sympathy by scholars, political activists, and politicians around the world. What is the reason for this strong appeal of this concept

    Monitoring of a virtual infrastructure testbed

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    This paper presents a SNMP-based Monitoring Agents for Multi-Constrain Resource Scheduling in Grids (SBLOMARS) as an effective solution for resource usage monitoring in virtual network environments. SBLOMARS is different to current large-scale distributed monitoring systems in three essential aspects: Firstly, it reaches a high level of generality by the integration of the SNMP protocol and thus, facilitates to handle heterogeneous operating platforms. Secondly, it is able to self-configure the polling periods of the resources to be monitored depending of network context and finally, it makes use of dynamic software structures to interface with third parties, allowing to be deployed in a wide range of devices, from simple mobile access devices to robust multiprocessor systems or clusters with even multiple hard disks and storage partitions. SBLOMARS has been deployed in EmanicsLab, a virtual laboratory constituted by fourteen nodes distributed in seven European Universities. Although the research is not yet concluded, available results confirm its suitability to deal with the challenges of monitoring virtual networks.Postprint (published version

    An analysis of the possible causes of product market malfunctioning in the EU: First results for manufacturing and service sectors

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    Within the context of the follow-up to the Single Market Review, the European Commission has screened EU manufacturing and service sectors for problems of market malfunctioning. This paper investigates the nature of these problems in the selected sectors and focuses on the following four dimensions of market functioning: regulation, integration, competition and innovation. In spite of the data limitations, regulation appears to be a cross cutting factor affecting market functioning in many sectors. The service sectors, in particular, show signs of an unexploited potential in terms of market integration and competition pressures. In all selected sectors there are indications of an unsatisfactory innovation performance. Overall, the analysis appears to confirm the results of the initial sector screening.European economy, economic integration, regulation, competition, innovation, Internal Market, Single Market, structural policy, manufacturing sectors, service sectors, Ilzkovitz, Dierx, Sousa

    A comparison of resource allocation process in grid and cloud technologies

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    Grid Computing and Cloud Computing are two different technologies that have emerged to validate the long-held dream of computing as utilities which led to an important revolution in IT industry. These technologies came with several challenges in terms of middleware, programming model, resources management and business models. These challenges are seriously considered by Distributed System research. Resources allocation is a key challenge in both technologies as it causes the possible resource wastage and service degradation. This paper is addressing a comprehensive study of the resources allocation processes in both technologies. It provides the researchers with an in-depth understanding of all resources allocation related aspects and associative challenges, including: load balancing, performance, energy consumption, scheduling algorithms, resources consolidation and migration. The comparison also contributes an informal definition of the Cloud resource allocation process. Resources in the Cloud are being shared by all users in a time and space sharing manner, in contrast to dedicated resources that governed by a queuing system in Grid resource management. Cloud Resource allocation suffers from extra challenges abbreviated by achieving good load balancing and making right consolidation decision

    Ontology Based Repository for Specifying Investment Advisory Services as a Knowledge Product

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    This paper presents a repository for the product design of investment advice in wealth management using an ontology-based knowledge representation and service marketing methods; the repository is exemplified through a prototype implemented in Protégé. The aims of the repository are: (1) to support the specification of investment advisory services as knowledge products based on service modules, (2) to enable a solution-oriented product strategy serving behavioral customer segments and to facilitate external communications about service characteristics, (3) to foster a common ground for the internal communication between marketing experts and investment advisors, and for this purpose (4) to provide a visual representation of investment advisory services with service blueprints for a collaborative product specification. The specification of investment advice uses service modules, which combine investment process and advisory process for representing both the financial know-how and the interaction between customer and advisor. Consequently marketers can model and analyze the core features of investment advice. The repository supports the success factors for the service to be designed, being a differentiated product, the overall quality of the service, product fit, internal marketing and the use of technology. Recognizing investment advice as a knowledge product permits the transformation of advisory support systems into a shared knowledge base

    Edge computing infrastructure for 5G networks: a placement optimization solution

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    This thesis focuses on how to optimize the placement of the Edge Computing infrastructure for upcoming 5G networks. To this aim, the core contributions of this research are twofold: 1) a novel heuristic called Hybrid Simulated Annealing to tackle the NP-hard nature of the problem and, 2) a framework called EdgeON providing a practical tool for real-life deployment optimization. In more detail, Edge Computing has grown into a key solution to 5G latency, reliability and scalability requirements. By bringing computing, storage and networking resources to the edge of the network, delay-sensitive applications, location-aware systems and upcoming real-time services leverage the benefits of a reduced physical and logical path between the end-user and the data or service host. Nevertheless, the edge node placement problem raises critical concerns regarding deployment and operational expenditures (i.e., mainly due to the number of nodes to be deployed), current backhaul network capabilities and non-technical placement limitations. Common approaches to the placement of edge nodes are based on: Mobile Edge Computing (MEC), where the processing capabilities are deployed at the Radio Access Network nodes and Facility Location Problem variations, where a simplistic cost function is used to determine where to optimally place the infrastructure. However, these methods typically lack the flexibility to be used for edge node placement under the strict technical requirements identified for 5G networks. They fail to place resources at the network edge for 5G ultra-dense networking environments in a network-aware manner. This doctoral thesis focuses on rigorously defining the Edge Node Placement Problem (ENPP) for 5G use cases and proposes a novel framework called EdgeON aiming at reducing the overall expenses when deploying and operating an Edge Computing network, taking into account the usage and characteristics of the in-place backhaul network and the strict requirements of a 5G-EC ecosystem. The developed framework implements several placement and optimization strategies thoroughly assessing its suitability to solve the network-aware ENPP. The core of the framework is an in-house developed heuristic called Hybrid Simulated Annealing (HSA), seeking to address the high complexity of the ENPP while avoiding the non-convergent behavior of other traditional heuristics (i.e., when applied to similar problems). The findings of this work validate our approach to solve the network-aware ENPP, the effectiveness of the heuristic proposed and the overall applicability of EdgeON. Thorough performance evaluations were conducted on the core placement solutions implemented revealing the superiority of HSA when compared to widely used heuristics and common edge placement approaches (i.e., a MEC-based strategy). Furthermore, the practicality of EdgeON was tested through two main case studies placing services and virtual network functions over the previously optimally placed edge nodes. Overall, our proposal is an easy-to-use, effective and fully extensible tool that can be used by operators seeking to optimize the placement of computing, storage and networking infrastructure at the users’ vicinity. Therefore, our main contributions not only set strong foundations towards a cost-effective deployment and operation of an Edge Computing network, but directly impact the feasibility of upcoming 5G services/use cases and the extensive existing research regarding the placement of services and even network service chains at the edge
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