208 research outputs found
Architectures for the Future Networks and the Next Generation Internet: A Survey
Networking research funding agencies in the USA, Europe, Japan, and other countries are encouraging research on revolutionary networking architectures that may or may not be bound by the restrictions of the current TCP/IP based Internet. We present a comprehensive survey of such research projects and activities. The topics covered include various testbeds for experimentations for new architectures, new security mechanisms, content delivery mechanisms, management and control frameworks, service architectures, and routing mechanisms. Delay/Disruption tolerant networks, which allow communications even when complete end-to-end path is not available, are also discussed
Engineering Self-Adaptive Collective Processes for Cyber-Physical Ecosystems
The pervasiveness of computing and networking is creating significant opportunities for building valuable socio-technical systems. However, the scale, density, heterogeneity, interdependence, and QoS constraints of many target systems pose severe operational and engineering challenges. Beyond individual smart devices, cyber-physical collectives can provide services or solve complex problems by leveraging a âsystem effectâ while coordinating and adapting to context or environment change. Understanding and building systems exhibiting collective intelligence and autonomic capabilities represent a prominent research goal, partly covered, e.g., by the field of collective adaptive systems. Therefore, drawing inspiration from and building on the long-time research activity on coordination, multi-agent systems, autonomic/self-* systems, spatial computing, and especially on the recent aggregate computing paradigm, this thesis investigates concepts, methods, and tools for the engineering of possibly large-scale, heterogeneous ensembles of situated components that should be able to operate, adapt and self-organise in a decentralised fashion. The primary contribution of this thesis consists of four main parts. First, we define and implement an aggregate programming language (ScaFi), internal to the mainstream Scala programming language, for describing collective adaptive behaviour, based on field calculi. Second, we conceive of a âdynamic collective computationâ abstraction, also called aggregate process, formalised by an extension to the field calculus, and implemented in ScaFi. Third, we characterise and provide a proof-of-concept implementation of a middleware for aggregate computing that enables the development of aggregate systems according to multiple architectural styles. Fourth, we apply and evaluate aggregate computing techniques to edge computing scenarios, and characterise a design pattern, called Self-organising Coordination Regions (SCR), that supports adjustable, decentralised decision-making and activity in dynamic environments.Con lo sviluppo di informatica e intelligenza artificiale, la diffusione pervasiva di device computazionali e la crescente interconnessione tra elementi fisici e digitali, emergono innumerevoli opportunitĂ per la costruzione di sistemi socio-tecnici di nuova generazione. Tuttavia, l'ingegneria di tali sistemi presenta notevoli sfide, data la loro complessitĂ âsi pensi ai livelli, scale, eterogeneitĂ , e interdipendenze coinvolti. Oltre a dispositivi smart individuali, collettivi cyber-fisici possono fornire servizi o risolvere problemi complessi con un âeffetto sistemaâ che emerge dalla coordinazione e l'adattamento di componenti fra loro, l'ambiente e il contesto. Comprendere e costruire sistemi in grado di esibire intelligenza collettiva e capacitĂ autonomiche Ăš un importante problema di ricerca studiato, ad esempio, nel campo dei sistemi collettivi adattativi. PerciĂČ, traendo ispirazione e partendo dall'attivitĂ di ricerca su coordinazione, sistemi multiagente e self-*, modelli di computazione spazio-temporali e, specialmente, sul recente paradigma di programmazione aggregata, questa tesi tratta concetti, metodi, e strumenti per l'ingegneria di
ensemble di elementi situati eterogenei che devono essere in grado di lavorare, adattarsi, e auto-organizzarsi in modo decentralizzato. Il contributo di questa tesi consiste in quattro parti principali. In primo luogo, viene definito e implementato un linguaggio di programmazione aggregata (ScaFi), interno al linguaggio Scala, per descrivere comportamenti collettivi e adattativi secondo l'approccio dei campi computazionali. In secondo luogo, si propone e caratterizza l'astrazione di processo aggregato per rappresentare computazioni collettive dinamiche concorrenti, formalizzata come estensione al field calculus e implementata in ScaFi. Inoltre, si analizza e implementa un prototipo di middleware per sistemi aggregati, in grado di supportare piĂč stili architetturali. Infine, si applicano e valutano tecniche di programmazione aggregata in scenari di edge computing, e si propone un pattern, Self-Organising Coordination Regions, per supportare, in modo decentralizzato, attivitĂ decisionali e di regolazione in ambienti dinamici
A COGNITIVE ARCHITECTURE FOR AMBIENT INTELLIGENCE
LâAmbient Intelligence (AmI) Ăš caratterizzata dallâuso di sistemi pervasivi per
monitorare lâambiente e modificarlo secondo le esigenze degli utenti e rispettando
vincoli definiti globalmente. Questi sistemi non possono prescindere da requisiti
come la scalabilitĂ e la trasparenza per lâutente. Una tecnologia che consente di
raggiungere questi obiettivi Ăš rappresentata dalle reti di sensori wireless (WSN),
caratterizzate da bassi costi e bassa intrusivitĂ . Tuttavia, sebbene in grado di
effettuare elaborazioni a bordo dei singoli nodi, le WSN non hanno da sole le capacitĂ
di elaborazione necessarie a supportare un sistema intelligente; dâaltra parte
senza questa attivitĂ di pre-elaborazione la mole di dati sensoriali puĂČ facilmente
sopraffare un sistema centralizzato con unâeccessiva quantitĂ di dettagli superflui.
Questo lavoro presenta unâarchitettura cognitiva in grado di percepire e controllare
lâambiente di cui fa parte, basata su un nuovo approccio per lâestrazione
di conoscenza a partire dai dati grezzi, attraverso livelli crescenti di astrazione.
Le WSN sono utilizzate come strumento sensoriale pervasivo, le cui capacitĂ computazionali
vengono utilizzate per pre-elaborare i dati rilevati, in modo da consentire
ad un sistema centralizzato intelligente di effettuare ragionamenti di alto
livello.
Lâarchitettura proposta Ăš stata utilizzata per sviluppare un testbed dotato degli
strumenti hardware e software necessari allo sviluppo e alla gestione di applicazioni
di AmI basate su WSN, il cui obiettivo principale sia il risparmio energetico. Per
fare in modo che le applicazioni di AmI siano in grado di comunicare con il mondo
esterno in maniera affidabile, per richiedere servizi ad agenti esterni, lâarchitettura
Ăš stata arricchita con un protocollo di gestione distribuita della reputazione.
Ă stata inoltre sviluppata unâapplicazione di esempio che sfrutta le caratteristiche
del testbed, con lâobiettivo di controllare la temperatura in un ambiente
lavorativo. Questâapplicazione rileva la presenza dellâutente attraverso un modulo
per la fusione di dati multi-sensoriali basato su reti bayesiane, e sfrutta questa
informazione in un controllore fuzzy multi-obiettivo che controlla gli attuatori sulla
base delle preferenze dellâutente e del risparmio energetico.Ambient Intelligence (AmI) systems are characterized by the use of pervasive
equipments for monitoring and modifying the environment according to usersâ
needs, and to globally defined constraints. Furthermore, such systems cannot ignore
requirements about ubiquity, scalability, and transparency to the user. An
enabling technology capable of accomplishing these goals is represented by Wireless
Sensor Networks (WSNs), characterized by low-costs and unintrusiveness. However,
although provided of in-network processing capabilities, WSNs do not exhibit
processing features able to support comprehensive intelligent systems; on the other
hand, without this pre-processing activities the wealth of sensory data may easily
overwhelm a centralized AmI system, clogging it with superfluous details.
This work proposes a cognitive architecture able to perceive, decide upon, and
control the environment of which the system is part, based on a new approach to
knowledge extraction from raw data, that addresses this issue at different abstraction
levels. WSNs are used as the pervasive sensory tool, and their computational
capabilities are exploited to remotely perform preliminary data processing. A central
intelligent unit subsequently extracts higher-level concepts in order to carry on
symbolic reasoning. The aim of the reasoning is to plan a sequence of actions that
will lead the environment to a state as close as possible to the usersâ desires, taking
into account both implicit and explicit feedbacks from the users, while considering
global system-driven goals, such as energy saving. The proposed conceptual architecture
was exploited to develop a testbed providing the hardware and software
tools for the development and management of AmI applications based on WSNs,
whose main goal is energy saving for global sustainability. In order to make the
AmI system able to communicate with the external world in a reliable way, when
some services are required to external agents, the architecture was enriched with
a distributed reputation management protocol.
A sample application exploiting the testbed features was implemented for addressing
temperature control in a work environment. Knowledge about the userâs
presence is obtained through a multi-sensor data fusion module based on Bayesian
networks, and this information is exploited by a multi-objective fuzzy controller
that operates on actuators taking into account usersâ preference and energy consumption
constraints
Trustworthy autonomic architecture (TAArch): Implementation and empirical investigation
This paper presents a new architecture for trustworthy autonomic systems. This trustworthy autonomic architecture is different from the traditional autonomic computing architecture and includes mechanisms and instrumentation to explicitly support run-time self-validation and trustworthiness. The state of practice does not lend itself robustly enough to support trustworthiness and system dependability. For example, despite validating system's decisions within a logical boundary set for the system, thereâs the possibility of overall erratic behaviour or inconsistency in the system emerging for example, at a different logical level or on a different time scale. So a more thorough and holistic approach, with a higher level of check, is required to convincingly address the dependability and trustworthy concerns. Validation alone does not always guarantee trustworthiness as each individual decision could be correct (validated) but overall system may not be consistent and thus not dependable. A robust approach requires that validation and trustworthiness are designed in and integral at the architectural level, and not treated as add-ons as they cannot be reliably retro-fitted to systems. This paper analyses the current state of practice in autonomic architecture, presents a different architectural approach for trustworthy autonomic systems, and uses a datacentre scenario as the basis for empirical analysis of behaviour and performance. Results show that the proposed trustworthy autonomic architecture has significant performance improvement over existing architectures and can be relied upon to operate (or manage) almost all level of datacentre scale and complexity
Ubiquitous and context-aware computing modelling : study of devices integration in their environment
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementIn an almost imperceptible way, ubiquitous and context-aware computing make part
of our everyday lives, as the world has developed in an interconnected way between
humans and technological devices. This interconnectedness raises the need to
integrate humansâ interaction with the different devices they use in different social
contexts and environments. In the proposed research, it is suggested the
development of new scenario building based on a current ubiquitous computing
model dedicated to the environment context-awareness. We will also follow previous
research made on the formal structure computation model based on social paradigm
theory, dedicated to embed devices into different context environments with social
roles developed by Santos (2012/2015). Furthermore, several socially relevant context
scenarios are to be identified and studied. Once identified, we gather and document
the requirements that devices should have, according to the model, in order to
achieve a correct integration in their contextual environment
Hydrodynamics-Biology Coupling for Algae Culture and Biofuel Production
International audienceBiofuel production from microalgae represents an acute optimization problem for industry. There is a wide range of parameters that must be taken into account in the development of this technology. Here, mathematical modelling has a vital role to play. The potential of microalgae as a source of biofuel and as a technological solution for CO2 fixation is the subject of intense academic and industrial research. Large-scale production of microalgae has potential for biofuel applications owing to the high productivity that can be attained in high-rate raceway ponds. We show, through 3D numerical simulations, that our approach is capable of discriminating between situations where the paddle wheel is rapidly moving water or slowly agitating the process. Moreover, the simulated velocity fields can provide lagrangian trajectories of the algae. The resulting light pattern to which each cell is submitted when travelling from light (surface) to dark (bottom) can then be derived. It will then be reproduced in lab experiments to study photosynthesis under realistic light patterns
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