FERNÁNDEZ CERERO , Damián

Esta Tesis Doctoral, que se presenta como compendio de artículos de investigación, se centra en la eficiencia en la utilización de los recursos en centros de datos de internet. Este problema ha sido abordado esencialmente desarrollando diferentes estrategias de eficiencia energética, gestión y distribución de recursos, así como todas las...

The management and processing of the data generated by healthcare systems is getting more and more attention because of the digitalization of a traditionally analogical sector such as healthcare. Various data management frameworks and solutions have emerged to face some of the multiple challenges present in this environment, includ ing: (a)...

Carbon emissions, greenhouse gases and pollution in general are usually related to traditional factories, so the most modern computing factories have gone unnoticed for the general-public opinion. We empirically show through extensive and realistic simulation that: 1) energy consumption, and consequently CO2 emissions, could be reduced from...

Information technologies must be made aware of the sustainability of cost reduction. Data centers may reach energy consumption levels comparable to many industrial facilities and small-sized towns. Therefore, innovative and transparent energy policies should be applied to improve energy consumption and deliver the best performance. This paper...

Cloud computing and data centers that support this paradigm are rapidly evolving in order to satisfy new demands. These ever-growing needs represent an energy-related challenge to achieve sustainability and cost reduction. In this paper, we define an expert and intelligent system that applies various en ergy policies. These policies are...

Energy-awareness remains one of the main concerns for today's cloud computing (CC) operators. The optimisation of energy consumption in both cloud computational clusters and computing servers is usually related to scheduling problems. The definition of an optimal scheduling policy which does not negatively impact to system performance and task...

The quality of services in Cloud Computing (CC) depends on the scheduling strategies selected for processing of the complex workloads in the physical cloud clusters. Using the scheduler of the single type does not guarantee of the optimal mapping of jobs onto cloud resources, especially in the case of the processing of the big data workloads....

Energy-awareness remians the important problem in today's cloud computing (CC). Optimization of the energy consumed in cloud data centers and computing servers is usually related to the scheduling prob lems. It is very difficult to define an optimal schedul ing policy without negoative influence into the system performance and task completion...

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Cloud computing (CC) systems are the most popular computational environments for providing elastic and scalable services on a massive scale. The nature of such systems often results in energy-related problems that have to be solved for sustainability, cost reduction, and environment protection. In this paper we defined and developed a set of...

Data centres constitute the engine of the Internet, and run a major portion of large web and mobile applications, content delivery and sharing platforms, and Cloud-computing business models. The high performance of such infrastructures is therefore critical for their correct functioning. This work focuses on the improvement of data-centre...

Data centres increase their size and complexity due to the increasing amount of heterogeneous work loads and patterns to be served. Such a mix of various purpose workloads makes the optimisation of resource management systems according to temporal or application-level patterns difficult. Data centre operators have developed multiple...

Data centres are quickly evolving to support new demands for Cloud-Computing services. Extreme workload peaks represent a challenge for the maintenance of the performance and service level agreements, even more when operation costs need to be minimised. In this paper, we first present an extensive analysis of the impact of extreme workloads...

Achieving efficiency both in terms of resource utilisation and energy consumption is acomplex challenge, especially in large-scale wide-purpose data centers that serve cloud- computing services. Simulation presents an appropriate solution for the development andtesting of strategies that aim to improve efficiency problems before their...

Edge computing constitutes a key paradigm to address the new requirements of areas such as smart cars, industry 4.0, and health care, where massive amounts of heterogeneous data from continuous geographically-distributed sources have to be processed and computed near real-time. To this end, new distributed infrastructures consisting on small...

The spread of cloud computing has increased recent data center size and usage. Because of this, the op­timization of data centers is becoming the focus of most important companies in this sector. In order to improve data cenler energy efficiency, we propose a software infrastructure for minimizing power us­age of data centers based on policies...

The number of connected sensors and devices is expected to increase to billions in the near future. However, centralised cloud-computing data centres present various challenges to meet the requirements inherent to Internet of Things (IoT) workloads, such as low latency, high throughput and bandwidth constraints. Edge computing is becoming the...

In order to evaluate AAL systems, virtual environments help to reduce costs and time, but these environments do not include hyper-realistic human movements. This is something crucial to evaluate activity recognition systems. The present work in progress describes how it is looking for a way to solve this problem and its development using a...

Social media have emerged in the last decade as a viable and ubiquitous means of communication. The ease of user content generation within these platforms, e.g. check-in information, multimedia data, etc., along with the proliferation of Global Positioning System (GPS)-enabled, always-connected capture devices lead to data streams of...

The fear experienced by data center administrators presents an ongoing problem due to the low percentage of machines that they are willing to switch off in order to save energy. This risk aversion can be assessed from acognitive system. The purpose of this paper is to demonstrate the extra costs in curred by maintaining all the machines of a...

Data centres have become the backbone of large Cloud services and applica-tions, providing virtually unlimited elastic and scalable computational and storage resources. The search for the efficiency and optimisation of resources is one of the current key aspects for large Cloud Service Providers and is becoming more and more challenging,...

In this paper, we propose a new methodology to compare and promote efficient driving by providing feedback to the user. The proposed methodology uses Data Envelopment Analysis (DEA) to enable comparisons between drivers and vehicles, by including parameters retrieved from vehicle as inputs or output for DEA method. Providing feedback to the...

Deep-learning object-detection architectures are gaining attraction, as they are used for critical tasks in relevant environments such as health, self-driving, industry, security, and robots. Notwithstanding, the available architectures provide variable performance results depending on the scenario under consideration. Challenges are usually...

This chapter presents the authors' work for the Case Study entitled "Delivering Social Media with Scalability" within the framework of High-Performance Modelling and Simulation for Big Data Applications (cHiPSet) COST Action 1406. We identify some core research areas and give an outline of the publications we came up within the framework of the...