ADDRESSING SELFISHNESS IN THE DESIGN OF COOPERATIVE SYSTEMS

I sistemi distribuiti cooperativi, tra cui in particolare i sistemi peer-to-peer, sono oggi alla base di applicazioni Internet di larga diffusione come file-sharing e media streaming, nonch\ue9 di tecnologie emergenti quali Blockchain e l'Internet of Things. Uno dei fattori chiave per il successo di un sistema cooperativo \ue8 che i nodi che vi partecipano mettano a disposizione della comunit\ue0 una parte delle proprie risorse (es. capacit\ue0 di calcolo, banda, spazio disco). Alcuni nodi, poich\ue9 controllati da agenti autonomi e indipendenti, potrebbero tuttavia agire egoisticamente e scegliere di non condividere alcuna risorsa, spinti dall'obiettivo di massimizzare la propria utilit\ue0 anche se a danno delle prestazioni dell'intero sistema. Affrontare l'egoismo dei nodi rappresenta dunque un'attivit\ue0 imprescindibile per lo sviluppo di un sistema cooperativo affidabile e performante. Nonostante il grande numero di tecniche ed approcci presenti in letteratura, tale attivit\ue0 richiede elaborazioni complesse, manuali e laboriose, nonch\ue9 conoscenze approfondite in vari domini di applicazione. Obiettivo di questa tesi \ue8 di fornire strumenti sia pratici che teorici per semplificare lo studio e il contrasto dei comportamenti egoistici nei sistemi cooperativi. Il primo contributo, basato su un'analisi esaustiva dello stato dell'arte sull'egoismo in sistemi distribuiti, presenta un framework di classificazione finalizzato all'identificazione e comprensione dei comportamenti egoistici pi\uf9 importanti su cui concentrarsi durante la progettazione di un sistema cooperativo. Come secondo contributo, presentiamo RACOON, un framework per la progettazione e configurazione di sistemi cooperativi resilienti all'egoismo dei nodi. L'obiettivo di RACOON \ue8 di semplificare tali attivit\ue0 fornendo una metodologia generale e semi-automatica, capace di integrare in un dato sistema pratici meccanismi di incentivo alla cooperazione, attentamente calibrati in modo da raggiungere gli obiettivi di resilienza e performance desiderati. A tal fine, RACOON impiega sia strumenti analitici appartenenti alla teoria dei giochi che metodi simulativi, che vengono utilizzati per fare previsioni sul comportamento del sistema in presenza di nodi egoisti. In questa tesi presentiamo inoltre una versione estesa del framework, chiamata RACOON++, sviluppata per migliorare l'accuratezza, flessibilit\ue0 e usabilit\ue0 del framework originale. Infine, come ultimo contributo del lavoro di tesi, presentiamo SEINE, un framework per la rapida modellazione e analisi sperimentale di vari tipi di comportamenti egoistici in un dato sistema cooperativo. Il framework \ue8 basato su un nuovo linguaggio specifico di dominio (SEINE-L) sviluppato per la descrizione degli scenari di egoismo da analizzare. SEINE fornisce inoltre supporto semi-automatico per l'implementazione e lo studio di tali scenari in un simulatore di sistemi distribuiti selezionato dallo stato dell'arte.Cooperative distributed systems, particularly peer-to-peer systems, are the basis of several mainstream Internet applications (e.g., file-sharing, media streaming) and the key enablers of new and emerging technologies, including blockchain and the Internet of Things. Essential to the success of cooperative systems is that nodes are willing to cooperate with each other by sharing part of their resources, e.g., network bandwidth, CPU capability, storage space. However, as nodes are autonomous entities, they may be tempted to behave in a selfish manner by not contributing their fair share, potentially causing system performance degradation and instability. Addressing selfish nodes is, therefore, key to building efficient and reliable cooperative systems. Yet, it is a challenging task, as current techniques for analysing selfishness and designing effective countermeasures remain manual and time-consuming, requiring multi-domain expertise. In this thesis, we aim to provide practical and conceptual tools to help system designers in dealing with selfish nodes. First, based on a comprehensive survey of existing work on selfishness, we develop a classification framework to identify and understand the most important selfish behaviours to focus on when designing a cooperative system. Second, we propose RACOON, a unifying framework for the selfishness-aware design and configuration of cooperative systems. RACOON provides a semi-automatic methodology to integrate a given system with practical and finely tuned mechanisms to meet specified resilience and performance objectives, using game theory and simulations to predict the behaviour of the system when subjected to selfish nodes. An extension of the framework (RACOON++) is also proposed to improve the accuracy, flexibility, and usability of RACOON. Finally, we propose SEINE, a framework for fast modelling and evaluation of various types of selfish behaviour in a given cooperative system. SEINE relies on a domain-specific language for describing the selfishness scenario to evaluate and provides semi-automatic support for its implementation and study in a state-of-the-art simulator.Les syst\ue8mes distribu\ue9s collaboratifs, en particulier les syst\ue8mes pair-\ue0-pair, forment l\u2019infrastructure sous-jacente de nombreuses applications Internet, certaines parmi les plus populaires (ex\ua0: partage de fichiers, streaming multim\ue9dia). Ils se situent \ue9galement \ue0 la base d\u2019un ensemble de technologies \ue9mergentes telles que la blockchain et l\u2019Internet des Objets. Le succ\ue8s de ces syst\ue8mes repose sur la contribution volontaire, de la part des n\u153uds participants, aux ressources partag\ue9es (ex : bande passante r\ue9seau, puissance de calcul, stockage de donn\ue9es). Or ces n\u153uds sont des entit\ue9s autonomes qui peuvent consid\ue9rer comme plus avantageux de se comporter de mani\ue8re \ue9go\uefste, c\u2019est-\ue0- dire de refuser de collaborer. De tels comportements peuvent fortement impacter les performances et la stabilit\ue9 op\ue9rationnelles du syst\ue8me cible. Prendre en compte et pr\ue9venir les comportements \ue9go\uefstes des n\u153uds est donc essentiel pour garantir l\u2019efficacit\ue9 et la fiabilit\ue9 des syst\ue8mes coop\ue9ratifs. Cependant, cela exige du d\ue9veloppeur, en d\ue9pit de la grande quantit\ue9 de techniques et d\u2019approches propos\ue9es dans la litt\ue9rature, des connaissances multisectorielles approfondies. L'objectif de cette th\ue8se est de concevoir et \ue9tudier de nouveaux outils th\ue9oriques et pratiques pour aider les concepteurs de syst\ue8mes distribu\ue9s collaboratifs \ue0 faire face \ue0 des n\u153uds \ue9go\uefstes. La premi\ue8re contribution, bas\ue9e sur une analyse exhaustive de la litt\ue9rature sur les comportements \ue9go\uefstes dans les syst\ue8mes distribu\ue9s, propose un mod\ue8le de classification pour identifier et analyser les comportements \ue9go\uefstes les plus importants sur lesquels il est important de se concentrer lors de la conception d'un syst\ue8me coop\ue9ratif. Dans la deuxi\ue8me contribution, nous proposons RACOON, un framework pour la conception et la configuration de syst\ue8mes coop\ue9ratifs r\ue9silients aux comportements \ue9go\uefstes. Outre un ensemble de m\ue9canismes d'incitation \ue0 la coop\ue9ration, RACOON fournit une m\ue9thodologie semi-automatique d\u2019int\ue9gration et de calibration de ces m\ue9canismes de mani\ue8re \ue0 garantir le niveau de performance souhait\ue9. RACOON s\u2019appuie sur une analyse du syst\ue8me cible fond\ue9e sur la th\ue9orie des jeux et sur des simulations pour pr\ue9dire l\u2019existence de n\u153uds \ue9go\uefstes dans le syst\ue8me. RACOON a \ue9t\ue9 \ue9tendu en un deuxi\ue8me framework, RACOON++. Plus pr\ue9cis, plus flexible, RACOON++ offre \ue9galement une plus grande facilit\ue9 d'utilisation. Une derni\ue8re contribution, SEINE, propose un framework pour la mod\ue9lisation et l'analyse des diff\ue9rents types de comportements \ue9go\uefstes dans un syst\ue8me coop\ue9ratif. Bas\ue9 sur un langage d\ue9di\ue9, d\ue9velopp\ue9 pour d\ue9crire les sc\ue9narios de comportement \ue9go\uefstes, SEINE fournit un support semi-automatique pour la mise en \u153uvre et l'\ue9tude de ces sc\ue9narios dans un simulateur choisi sur la base de l\u2019\ue9tat de l\u2019art (PeerSim)

Maritime expressions:a corpus based exploration of maritime metaphors

This study uses a purpose-built corpus to explore the linguistic legacy of Britain’s maritime history found in the form of hundreds of specialised ‘Maritime Expressions’ (MEs), such as TAKEN ABACK, ANCHOR and ALOOF, that permeate modern English. Selecting just those expressions commencing with ’A’, it analyses 61 MEs in detail and describes the processes by which these technical expressions, from a highly specialised occupational discourse community, have made their way into modern English. The Maritime Text Corpus (MTC) comprises 8.8 million words, encompassing a range of text types and registers, selected to provide a cross-section of ‘maritime’ writing. It is analysed using WordSmith analytical software (Scott, 2010), with the 100 million-word British National Corpus (BNC) as a reference corpus. Using the MTC, a list of keywords of specific salience within the maritime discourse has been compiled and, using frequency data, concordances and collocations, these MEs are described in detail and their use and form in the MTC and the BNC is compared. The study examines the transformation from ME to figurative use in the general discourse, in terms of form and metaphoricity. MEs are classified according to their metaphorical strength and their transference from maritime usage into new registers and domains such as those of business, politics, sports and reportage etc. A revised model of metaphoricity is developed and a new category of figurative expression, the ‘resonator’, is proposed. Additionally, developing the work of Lakov and Johnson, Kovesces and others on Conceptual Metaphor Theory (CMT), a number of Maritime Conceptual Metaphors are identified and their cultural significance is discussed