Big Data and Large-scale Data Analytics: Efficiency of Sustainable Scalability and Security of Centralized Clouds and Edge Deployment Architectures

One of the significant shifts of the next-generation computing technologies will certainly be in the development of Big Data (BD) deployment architectures. Apache Hadoop, the BD landmark, evolved as a widely deployed BD operating system. Its new features include federation structure and many associated frameworks, which provide Hadoop 3.x with the maturity to serve different markets. This dissertation addresses two leading issues involved in exploiting BD and large-scale data analytics realm using the Hadoop platform. Namely, (i)Scalability that directly affects the system performance and overall throughput using portable Docker containers. (ii) Security that spread the adoption of data protection practices among practitioners using access controls. An Enhanced Mapreduce Environment (EME), OPportunistic and Elastic Resource Allocation (OPERA) scheduler, BD Federation Access Broker (BDFAB), and a Secure Intelligent Transportation System (SITS) of multi-tiers architecture for data streaming to the cloud computing are the main contribution of this thesis study

Adaptive object management for distributed systems

This thesis describes an architecture supporting the management of pluggable software components and evaluates it against the requirement for an enterprise integration platform for the manufacturing and petrochemical industries. In a distributed environment, we need mechanisms to manage objects and their interactions. At the least, we must be able to create objects in different processes on different nodes; we must be able to link them together so that they can pass messages to each other across the network; and we must deliver their messages in a timely and reliable manner. Object based environments which support these services already exist, for example ANSAware(ANSA, 1989), DEC's Objectbroker(ACA,1992), Iona's Orbix(Orbix,1994)Yet such environments provide limited support for composing applications from pluggable components. Pluggability is the ability to install and configure a component into an environment dynamically when the component is used, without specifying static dependencies between components when they are produced. Pluggability is supported to a degree by dynamic binding. Components may be programmed to import references to other components and to explore their interfaces at runtime, without using static type dependencies. Yet thus overloads the component with the responsibility to explore bindings. What is still generally missing is an efficient general-purpose binding model for managing bindings between independently produced components. In addition, existing environments provide no clear strategy for dealing with fine grained objects. The overhead of runtime binding and remote messaging will severely reduce performance where there are a lot of objects with complex patterns of interaction. We need an adaptive approach to managing configurations of pluggable components according to the needs and constraints of the environment. Management is made difficult by embedding bindings in component implementations and by relying on strong typing as the only means of verifying and validating bindings. To solve these problems we have built a set of configuration tools on top of an existing distributed support environment. Specification tools facilitate the construction of independent pluggable components. Visual composition tools facilitate the configuration of components into applications and the verification of composite behaviours. A configuration model is constructed which maintains the environmental state. Adaptive management is made possible by changing the management policy according to this state. Such policy changes affect the location of objects, their bindings, and the choice of messaging system

Adaptive hypertext and hypermedia : workshop : proceedings, 3rd, Sonthofen, Germany, July 14, 2001 and Aarhus, Denmark, August 15, 2001

This paper presents two empirical usability studies based on techniques from Human-Computer Interaction (HeI) and software engineering, which were used to elicit requirements for the design of a hypertext generation system. Here we will discuss the findings of these studies, which were used to motivate the choice of adaptivity techniques. The results showed dependencies between different ways to adapt the explanation content and the document length and formatting. Therefore, the system's architecture had to be modified to cope with this requirement. In addition, the system had to be made adaptable, in addition to being adaptive, in order to satisfy the elicited users' preferences

Adaptive hypertext and hypermedia : workshop : proceedings, 3rd, Sonthofen, Germany, July 14, 2001 and Aarhus, Denmark, August 15, 2001

This paper presents two empirical usability studies based on techniques from Human-Computer Interaction (HeI) and software engineering, which were used to elicit requirements for the design of a hypertext generation system. Here we will discuss the findings of these studies, which were used to motivate the choice of adaptivity techniques. The results showed dependencies between different ways to adapt the explanation content and the document length and formatting. Therefore, the system's architecture had to be modified to cope with this requirement. In addition, the system had to be made adaptable, in addition to being adaptive, in order to satisfy the elicited users' preferences

User modeling servers - requirements, design, and evaluation

Softwaresysteme, die ihre Services an Charakteristika individueller Benutzer anpassen haben sich bereits als effektiver und/oder benutzerfreundlicher als statische Systeme in mehreren Anwendungsdomänen erwiesen. Um solche Anpassungsleistungen anbieten zu können, greifen benutzeradaptive Systeme auf Modelle von Benutzercharakteristika zurück. Der Aufbau und die Verwaltung dieser Modelle wird durch dezidierte Benutzermodellierungskomponenten vorgenommen. Ein wichtiger Zweig der Benutzermodellierungsforschung beschäftigt sich mit der Entwicklung sogenannter ?Benutzermodellierungs-Shells?, d.h. generischen Benutzermodellierungssystemen, die die Entwicklung anwendungsspezifischer Benutzermodellierungskomponenten erleichtern. Die Bestimmung des Leistungsumfangs dieser generischen Benutzermodellierungssysteme und deren Dienste bzw. Funktionalitäten wurde bisher in den meisten Fällen intuitiv vorgenommen und/oder aus Beschreibungen weniger benutzeradaptiver Systeme in der Literatur abgeleitet. In der jüngeren Vergangenheit führte der Trend zur Personalisierung im World Wide Web zur Entwicklung mehrerer kommerzieller Benutzermodellierungsserver. Die für diese Systeme als wichtig erachteten Eigenschaften stehen im krassen Gegensatz zu denen, die bei der Entwicklung der Benutzermodellierungs-Shells im Vordergrund standen und umgekehrt. Vor diesem Hintergrund ist das Ziel dieser Dissertation (i) Anforderungen an Benutzermodellierungsserver aus einer multi-disziplinären wissenschaftlichen und einer einsatzorientierten (kommerziellen) Perspektive zu analysieren, (ii) einen Server zu entwerfen und zu implementieren, der diesen Anforderungen genügt, und (iii) die Performanz und Skalierbarkeit dieses Servers unter der Arbeitslast kleinerer und mittlerer Einsatzumgebungen gegen die diesbezüglichen Anforderungen zu überprüfen. Um dieses Ziel zu erreichen, verfolgen wir einen anforderungszentrierten Ansatz, der auf Erfahrungen aus verschiedenen Forschungsbereichen aufbaut. Wir entwickeln eine generische Architektur für einen Benutzermodellierungsserver, die aus einem Serverkern für das Datenmanagement und modular hinzufügbaren Benutzermodellierungskomponenten besteht, von denen jede eine wichtige Benutzermodellierungstechnik implementiert. Wir zeigen, dass wir durch die Integration dieser Benutzermodellierungskomponenten in einem Server Synergieeffekte zwischen den eingesetzten Lerntechniken erzielen und bekannte Defizite einzelner Verfahren kompensieren können, beispielsweise bezüglich Performanz, Skalierbarkeit, Integration von Domänenwissen, Datenmangel und Kaltstart. Abschließend präsentieren wir die wichtigsten Ergebnisse der Experimente, die wir durchgeführt haben um empirisch nachzuweisen, dass der von uns entwickelte Benutzermodellierungsserver zentralen Performanz- und Skalierbarkeitskriterien genügt. Wir zeigen, dass unser Benutzermodellierungsserver die vorbesagten Kriterien in Anwendungsumgebungen mit kleiner und mittlerer Arbeitslast in vollem Umfang erfüllt. Ein Test in einer Anwendungsumgebung mit mehreren Millionen Benutzerprofilen und einer Arbeitslast, die als repräsentativ für größere Web Sites angesehen werden kann bestätigte, dass die Performanz der Benutzermodellierung unseres Servers keine signifikante Mehrbelastung für eine personalisierte Web Site darstellt. Gleichzeitig können die Anforderungen an die verfügbare Hardware als moderat eingestuft werden

Proceedings of the Conference on Production Systems and Logistics: CPSL 2022

[no abstract available

New Design Techniques for Dynamic Reconfigurable Architectures

L'abstract è presente nell'allegato / the abstract is in the attachmen

A comprehensive survey of V2X cybersecurity mechanisms and future research paths

Recent advancements in vehicle-to-everything (V2X) communication have notably improved existing transport systems by enabling increased connectivity and driving autonomy levels. The remarkable benefits of V2X connectivity come inadvertently with challenges which involve security vulnerabilities and breaches. Addressing security concerns is essential for seamless and safe operation of mission-critical V2X use cases. This paper surveys current literature on V2X security and provides a systematic and comprehensive review of the most relevant security enhancements to date. An in-depth classification of V2X attacks is first performed according to key security and privacy requirements. Our methodology resumes with a taxonomy of security mechanisms based on their proactive/reactive defensive approach, which helps identify strengths and limitations of state-of-the-art countermeasures for V2X attacks. In addition, this paper delves into the potential of emerging security approaches leveraging artificial intelligence tools to meet security objectives. Promising data-driven solutions tailored to tackle security, privacy and trust issues are thoroughly discussed along with new threat vectors introduced inevitably by these enablers. The lessons learned from the detailed review of existing works are also compiled and highlighted. We conclude this survey with a structured synthesis of open challenges and future research directions to foster contributions in this prominent field.This work is supported by the H2020-INSPIRE-5Gplus project (under Grant agreement No. 871808), the ”Ministerio de Asuntos Económicos y Transformacion Digital” and the European Union-NextGenerationEU in the frameworks of the ”Plan de Recuperación, Transformación y Resiliencia” and of the ”Mecanismo de Recuperación y Resiliencia” under references TSI-063000-2021-39/40/41, and the CHIST-ERA-17-BDSI-003 FIREMAN project funded by the Spanish National Foundation (Grant PCI2019-103780).Peer ReviewedPostprint (published version