Enhancing cloud computing environments using a cluster as a service

The emergence of cloud computing has caused a significant change in how IT infrastructures are provided to research and business organizations. Instead of paying for expensive hardware and incur excessive maintenance costs, it is now possible to rent the IT infrastructure of other organizations for a minimal fee. While the existence of cloud computing is new. The elements used to create clouds have been around for some time. Cloud computing systems have been made possible through the use of large-scale clusters, service-oriented architecture (SOA), Web services, and virtualization. While the idea of offering resources via Web services is commonplace in cloud computing, little attention has been paid to the clients themselves specifically, human operators. Despite that clouds host a variety of resources which in turn are accessible to a variety of clients, support for human users is minimal.

Modeling a dynamic data replication strategy to increase system availability in cloud computing environments

Failures are normal rather than exceptional in the cloud computing environments. To improve system avai-lability, replicating the popular data to multiple suitable locations is an advisable choice, as users can access the data from a nearby site. This is, however, not the case for replicas which must have a fixed number of copies on several locations. How to decide a reasonable number and right locations for replicas has become a challenge in the cloud computing. In this paper, a dynamic data replication strategy is put forward with a brief survey of replication strategy suitable for distributed computing environments. It includes: 1) analyzing and modeling the relationship between system availability and the number of replicas; 2) evaluating and identifying the popular data and triggering a replication operation when the popularity data passes a dynamic threshold; 3) calculating a suitable number of copies to meet a reasonable system byte effective rate requirement and placing replicas among data nodes in a balanced way; 4) designing the dynamic data replication algorithm in a cloud. Experimental results demonstrate the efficiency and effectiveness of the improved system brought by the proposed strategy in a cloud.

Microhabitat selection by sea turtles in a dynamic thermal marine environment

1Reproductive fitness is often compromised at the margins of a species’ range due to sub-optimal conditions.2Set against this backdrop, the Mediterranean's largest loggerhead sea turtle (Caretta caretta) rookery at Zakynthos (Greece) presents a conundrum, being at a very high latitude for this species, yet hosting a high concentration of nesting.3We used visual surveys combined with global positioning system (GPS) tracking to show that at the start of the breeding season, individuals showed microhabitat selection, with females residing in transient patches of warm water. As the sea warmed in the summer, this selection was no longer evident.4As loggerhead turtles are ectothermic, this early season warm-water selection presumably speeds up egg maturation rates before oviposition, thereby allowing more clutches to be incubated when sand conditions are optimal during the summer.5Active selection of warm waters may allow turtles to initiate nesting at an earlier date.

Dynamic path determination policy for distributed multimedia content adaptation

Multimedia content adaptation allows the ever increasing variety of handheld devices such as Smartphones to access distributed rich media resources available on the Internet today. Path planning and determination is a fundamental problem in enhancing performance of distributed multimedia content adaptation systems. Most of the existing path determination mechanisms use static path determination criteria based solely on associating a path with a single behavior aggregate score. However, some criteria such as availability are best represented using different functionality rather than being accumulated into the aggregate score. Moreover, since selection criteria have different behavior towards the score, this principle need to be considered. In this paper, we propose a dynamic multi-criteria path determination policy that selects an optimal path to the content adaptation services that best meet the user preferences and QoS requirements. The performance of the proposed approach is studied in terms of score’s fairness and reliability under different variations. The results indicate that the proposed policy performs substantially better than the baseline policy.

Australian pre-service secondary teacher education courses : challenges and Dilemmas

Service and cloud computing supporting genomic analysis of the mammalian species

 This research focused on building Software as a Service clouds to support mammalian genomic applications such as personalized medicine. Outcomes of this research included a Software as a Service cloud framework, the Uncinus research cloud and novel genomic analysis software. Results have been published in high ranking peer-reviewed international journals.

A survey of cloud-based service computing solutions for mammalian genomics

Cloud-based service computing has started to change the way how research in science, in particular biology, medicine, and engineering, is being carried out. Researchers in the area of mammalian genomics have taken advantage of cloud computing technology to cost-effectively process large amounts of data and speed up discovery. Mammalian genomics is limited by the cost and complexity of analysis, which require large amounts of computational resources to analyse huge amount of data and biology specialists to interpret results. On the other hand the application of this technology requires computing knowledge, in particular programming and operations management skills to develop high performance computing (HPC) applications and deploy them on HPC clouds. We carried out a survey of cloud-based service computing solutions, as the most recent and promising instantiations of distributed computing systems, in the context their use in research of mammalian genomic analysis. We describe our most recent research and development effort which focuses on building Software as a Service (SaaS) clouds to simplify the use of HPC clouds for carrying out mammalian genomic analysis.

Adaptable, model-driven security engineering for SaaS cloud-based applications

Software-as-a-service (SaaS) multi-tenancy in cloud-based applications helps service providers to save cost, improve resource utilization, and reduce service customization and maintenance time. This is achieved by sharing of resources and service instances among multiple "tenants" of the cloud-hosted application. However, supporting multi-tenancy adds more complexity to SaaS applications required capabilities. Security is one of these key requirements that must be addressed when engineering multi-tenant SaaS applications. The sharing of resources among tenants - i.e. multi-tenancy - increases tenants' concerns about the security of their cloud-hosted assets. Compounding this, existing traditional security engineering approaches do not fit well with the multi-tenancy application model where tenants and their security requirements often emerge after the applications and services were first developed. The resultant applications do not usually support diverse security capabilities based on different tenants' needs, some of which may change at run-time i.e. after cloud application deployment. We introduce a novel model-driven security engineering approach for multi-tenant, cloud-hosted SaaS applications. Our approach is based on externalizing security from the underlying SaaS application, allowing both application/service and security to evolve at runtime. Multiple security sets can be enforced on the same application instance based on different tenants' security requirements. We use abstract models to capture service provider and multiple tenants' security requirements and then generate security integration and configurations at runtime. We use dependency injection and dynamic weaving via Aspect-Oriented Programming (AOP) to integrate security within critical application/service entities at runtime. We explain our approach, architecture and implementation details, discuss a usage example, and present an evaluation of our approach on a set of open source web applications.

Signaling in dynamic markets with adverse selection

Nesta dissertação, consideram-se trocas em mercados descentralizados com seleção adversa. Diferentemente da literatura até o momento, supomos que vendedores informados (e não compradores desinformados) fazem ofertas take-it-or-leave-it, de forma que sinalização através de preços é possível. Estabelecemos uma caracterização parcial do conjunto de equilíbrio, encontramos condições necessárias e suficientes para a existência de um equilíbrio e mostramos que todo equilíbrio apresenta sinalização se o problema de seleção adversa for suficientemente severo. Além disso, provamos o resultado surpreendente que o maior bem-estar atingido em equilíbrio é invariante às fricções do mercado. Também apresentamos condições necessárias e suficientes para a existência de equilíbrios separantes, que caracterizamos completamente. Mostramos que o conjunto de payoffs associados a equilíbrios separantes é invariante às fricções. Concluímos com uma caracterização completa do conjunto de equilíbrio com apenas dois tipos, e comparamos nossos resultados com os de Moreno e Wooders (2010), que analisam o caso em que compradores têm todo o poder de mercado. Nossos resultados mostram que sinalização através dos preços tem um impacto não trivial tanto nos resultados do mercado quanto no bem-estar.

Selection of dynamic comparative advantages

Considera diversos factores para examinar cómo modifican el principio simple de las ventajas comparativas estáticas y de mercado.

Coordination as a Service (CaaS) in the Cloud

Nel primo capitolo si è studiata la nuova tecnologia del Cloud Computing, fornendo una semplice analisi di tutte le caratteristiche principali, gli attori coinvolti e i relativi metodi di distribuzione e servizi offerti. Nel secondo capitolo si è introdotta la nozione di coordination as a service, discutendone le relative astrazioni che compongono l'architettura logica. Successivamente si è preso in considerazione il modello di coordinazione TuCSoN definendo cosa si intende per nodo, agente, centro di tuple e agent coordination context ed è stato analizzato il relativo linguaggio di coordinazione attraverso il quale essi interagiscono. Nel terzo capitolo sono state riviste ed estese le nozioni di TuCSoN, precedentemente acquisite, nell'ambito del Cloud Computing ed è stato fornito un modello astratto ed una possibile architettura di TuCSoN in the Cloud. Sono stati analizzati anche gli aspetti di un possibile servizio di tale genere nello scenario di servizio pay-per-use. Infine nel quarto ed ultimo capitolo si è sviluppato un caso di studio in cui si è implementata un'interfaccia per l'attuale CLI di TuCSoN sottoforma di applet, che è stata poi inserita nel Cloud attraverso la piattaforma PaaS Cloudify.

Sviluppo storico ed economico del cloud computing: Cloud foundry come esempio di platform as a service

Il Cloud Computing è una realtà sempre più diffusa e discussa nel nostro periodo storico, ma probabilmente non è ancora chiaro a tutti di cosa si tratta e le potenzialità che possiede. Infatti, non esiste ancora una definizione univoca e condivisa e questo può creare confusione. Oggi le grandi compagnie nella comunità informatica spingono sempre di più per affermare i servizi Cloud a livello mondiale, non solo per le aziende del settore, ma anche per tutte le altre. Ed è così che le aziende di tutto il mondo si muovono per imparare e adottare questa nuova tecnologia, per spostare i loro centri dati e le loro applicazioni nel Cloud. Ma dove e quando nasce il Cloud Computing? Quali sono realmente i benefici per le aziende che adottano questa tecnologia? Questo è l'obiettivo della mia tesi: cercare di far chiarezza sulla sua definizione, indagare sulla sua nascita e fare un quadro economico del suo sviluppo, analizzando i benefici per le aziende e le opportunità offerte. Come caso di studio ho scelto la piattaforma Cloud Foundry perchè in questo momento è in forte espansione e sta facendo un grosso lavoro per cercare di rendere il suo prodotto uno standard per il Cloud Computing. Come esempio particolare di piattaforma basata su Cloud Foundry si parlerà di Bluemix, la piattaforma Cloud offerta da IBM, una delle più grandi aziende nel settore informatico.

Elastic computing on Cloud resources for the CMS experiment

Nowadays, data handling and data analysis in High Energy Physics requires a vast amount of computational power and storage. In particular, the world-wide LHC Com- puting Grid (LCG), an infrastructure and pool of services developed and deployed by a ample community of physicists and computer scientists, has demonstrated to be a game changer in the efficiency of data analyses during Run-I at the LHC, playing a crucial role in the Higgs boson discovery. Recently, the Cloud computing paradigm is emerging and reaching a considerable adoption level by many different scientific organizations and not only. Cloud allows to access and utilize not-owned large computing resources shared among many scientific communities. Considering the challenging requirements of LHC physics in Run-II and beyond, the LHC computing community is interested in exploring Clouds and see whether they can provide a complementary approach - or even a valid alternative - to the existing technological solutions based on Grid. In the LHC community, several experiments have been adopting Cloud approaches, and in particular the experience of the CMS experiment is of relevance to this thesis. The LHC Run-II has just started, and Cloud-based solutions are already in production for CMS. However, other approaches of Cloud usage are being thought of and are at the prototype level, as the work done in this thesis. This effort is of paramount importance to be able to equip CMS with the capability to elastically and flexibly access and utilize the computing resources needed to face the challenges of Run-III and Run-IV. The main purpose of this thesis is to present forefront Cloud approaches that allow the CMS experiment to extend to on-demand resources dynamically allocated as needed. Moreover, a direct access to Cloud resources is presented as suitable use case to face up with the CMS experiment needs. Chapter 1 presents an overview of High Energy Physics at the LHC and of the CMS experience in Run-I, as well as preparation for Run-II. Chapter 2 describes the current CMS Computing Model, and Chapter 3 provides Cloud approaches pursued and used within the CMS Collaboration. Chapter 4 and Chapter 5 discuss the original and forefront work done in this thesis to develop and test working prototypes of elastic extensions of CMS computing resources on Clouds, and HEP Computing “as a Service”. The impact of such work on a benchmark CMS physics use-cases is also demonstrated.