Ces dernières années ont vu le développement du cloud computing. Le principe fondateur est de déporter la gestion des services informatique des entreprises dans des centres d'hébergement gérés par des entreprise tiers. Ce déport a pour principal avantage une réduction des coûts pour l'entreprise cliente, les moyens nécessaires à la gestion de ces services étant mutualisés entre clients et gérés par l'entreprise hébergeant ces services. Cette évolution implique la gestion de structures d'hébergement à grande échelle, que la dimension et la complexité rendent difficiles à administrer. Avec le développement des infrastructures de calcul de type cluster ou grille ont émergé des système fournissant un support pour l'administration automatisée de ces environnements. Ces systèmes sont désignés sous le terme Systèmes d'Administration Autonomes (SAA). Ils visent à fournir des services permettant d'automatiser les tâches d'administration comme le déploiement des logiciels, la réparation en cas de panne ou leur dimensionnement dynamique en fonction de la charge. Ainsi, il est naturel d'envisager l'utilisation des SAA pour l'administration d'une infrastructure d'hébergement de type clouds. Cependant, nous remarquons que les SAA disponibles à l'heure actuelle ont été pour la plupart conçus pour répondre aux besoins d'un domaine applicatif particulier. Un SAA doit pouvoir être adapté en fonction du domaine considéré, en particulier celui de l'administration d'un cloud. De plus, dans le domaine du cloud, différents besoins doivent être pris en compte : ceux de l'administrateur du centre d'hébergement et ceux de l'utilisateur du centre d'hébergement qui déploie ses applications dans le cloud. Ceci implique qu'un SAA doit pouvoir être adapté pour répondre à ces besoins divers. Dans cette thèse, nous étudions la conception et l'implantation d'un SAA adaptable. Un tel SAA doit permettre d'adapter les services qu'il offre aux besoins des domaines dans lesquels il est utilisé. Nous montrons ensuite comment ce SAA adaptable peut être utilisé pour l'administration autonome d'un environnement de cloud. / Last years have seen the development of cloud computing. The main underlying principle of to externalize the management of companies' IT services in hosting centers which are managed by third party companies. This externalization allows saving costs for the client company, since the resources required to manage these services are mutualized between clients and managed by the hosting company. This orientation implies the management of large scale hosting centers, whose dimension and complexity make them difficult to manage. With the developement of computing infrastructures such as clusters or grids, researchers investigated the design of systems which provides support of an automatized management of these environments. We refer to these system as Autonomic Management Systems (AMS). They aim at providing services which automate administration tasks such as software deployment, fault repair or dynamic dimensioning according to a load. Therefore, in this context, it is natural to consider the use of AMS for the administration of a cloud infrastructure. However, we observe that currently available AMS have been designed to address the requirements of a particular application domain. It should be possible to adapt an AMS according to the considered domain, in particular that of the cloud. Moreover, in the cloud computing area, different requirements have to be accounted : those of the administrator of the hosting center and those of the user of the hosting center (who deploys his application in the cloud). Therefore, an AMS should be adaptable to fulfill such various needs. In this thesis, we investigate the design and implementation of an adaptable AMS. Such an AMS must allow adaptation of all the services it provides, according to the domains where it is used. We next describe the application of this adaptable AMS for the autonomic management of a cloud environment.

This thesis tests a technique based on objectively identified tropical cloud regimes, in which some cloud characteristics are extrapolated from a single site in the tropics to the entire tropics. Information on cloud top pressure, cloud optical thickness and total cloud cover from 1985-2000 has been derived from the ISCCP D1 data set and has been used to create maps of tropical cloud regimes and maps of total cloud cover over the tropics. The distribution and characteristics of the tropical cloud regimes has been discussed after which total cloud cover values were extrapolated to the cloud regimes over the tropics. After a qualitative and quantitative assessment was used to evaluate the success of the extrapolating method, it was found that the method worked especially well for time averaged extrapolated data sets using the median values of total cloud cover values. / I detta magisterexamensarbete testas en metod som baseras på objektivt framtagna molnregimer, där några molnegenskaper extrapoleras från en plats i tropikerna till resten av tropikerna. Informationen om molntoppstrycket, molnens optiska djup och det totala molntäcket från 1985-2000 har hämtats från ISCCP D1 data set och har använts till att skapa kartor för tropiska molnregimer och för det totala molntäcket över tropikerna. Distributionen och egenskaperna av de tropiska molnregimerna har diskuterats och användes sedan för att extrapolera det totala molntäcket över tropikerna. En kvalitativ och kvantitativ undersökning användes för att utvärdera framgångarna med extrapoleringsmetoden. Det framkom att metoden fungerade särskilt bra för extrapolerade data set med median totala molntäcksvärden över längre tidsperioder.

Approved for public release; distribution is unlimited. / An established cloud analysis routine has been modified for use in the Arctic. The separation of clouds from the snow and sea ice backgrounds is accomplished through a multispectral technique which utilizes VHRR channel 2 (visible), channel 3 (near infrared) and channel 4 (infrared) data. The primary means of cloud identification is based on a derived channel 3 reflectance image. At this wavelength, a significant contrast exists between liquid clouds and the arctic backgrounds, unlike in the standard visible and infrared images. The channel 3 reflectance is obtained by first using the channel 4 emission temperature to estimate the thermal emission component of the total channel 3 radiance. This thermal emission component is subsequently removed from the total radiance, leaving only the solar reflectance component available for analysis. Since many ice clouds do not exhibit a substantially greater reflectance is channel 3, the routine exploits differences in transmissive characteristics between channels 3 and 4 for identification. The routine was applied to six case studies which had been analyzed by three independent experts to establish 'ground truth'. Verification of the cloud analysis results, through a comparison to the subjective analyses, yielded impressive statistics. A success rate of 77.9% was obtained with an arguably small data base of 131 undisputed scenes / http://archive.org/details/objectivetechniq00barr / Lieutenant, United States Navy

The adoption of cloud computing has increased dramatically in recent years due to at- tractive features such as flexibility, cost reductions, scalability, and pay per use. Shifting towards cloud computing is attracting not only industry but also government and academia. However, given their stringent privacy and security policies, this shift is still hindered by many security concerns related to the cloud computing features, namely shared resources, virtualization and multi-tenancy. These security concerns vary from privacy threats and lack of transparency to intrusions from within and outside the cloud infrastructure. There- fore, to overcome these concerns and establish a strong trust in cloud computing, there is a need to develop adequate security mechanisms for effectively handling the threats faced in the cloud. Intrusion Detection Systems (IDSs) represent an important part of such mech- anisms. Developing cloud based IDS that can capture suspicious activity or threats, and prevent attacks and data leakage from both inside and outside the cloud environment is paramount. However, cloud computing is faced with a multidimensional and rapidly evolv- ing threat landscape, which makes cloud based IDS more challenging. Moreover, one of the most significant hurdles for developing such cloud IDS is the lack of publicly available datasets collected from a real cloud computing environment. In this dissertation, we intro- duce the first public dataset of its kind, named ISOT Cloud Intrusion Dataset (ISOT-CID), for cloud intrusion detection. The dataset consists of several terabytes of data, involving normal activities and a wide variety of attack vectors, collected over multiple phases and periods of time in a real cloud environment. We also introduce a new hypervisor-based cloud intrusion detection system (HIDS) that uses online multivariate statistical change analysis to detect anomalous network behaviors. As a departure from the conventional monolithic network IDS feature model, we leverage the fact that a hypervisor consists of a collection of instances, to introduce an instance-oriented feature model that exploits indi- vidual as well as correlated behaviors of instances to improve the detection capability. The proposed approach is evaluated using ISOT-CID and the experiments along with results are presented. / Graduate / 2020-08-14

Le Cloud computing a gagné beaucoup de popularité et a reçu beaucoup d'attention des deux mondes, industriel et académique, puisque cela les libère de la charge et le coût de la gestion de centres de données locaux. Toutefois, le principal facteur motivant l'utilisation du Cloud est sa capacité de fournir des ressources en fonction des besoins du client. Ce concept est appelé l’élasticité. Adapter les applications Cloud lors de leur exécution en fonction des variations de la demande est un grand défi. En outre, l'élasticité de Cloud est diverse et hétérogène car elle englobe différentes approches, stratégies, objectifs, etc. Nous sommes intéressés à étudier: Comment résoudre le problème de sur/sous-approvisionnement? Comment garantir la disponibilité des ressources et surmonter les problèmes d'hétérogénéité et de granularité des ressources? Comment standardiser, unifier les solutions d'élasticité et de modéliser sa diversité à un haut niveau d'abstraction? Dans cette thèse, trois majeures contributions ont été proposées: Tout d’abord, un état de l’art à jour de l’élasticité du Cloud ; cet état de l’art passe en revue les différents travaux relatifs à l’élasticité des machines virtuelles et des conteneurs. Deuxièmement, ElasticDocker, une approche permettant de gérer l’élasticité des conteneurs, notamment l’élasticité verticale, la migration et l’élasticité combinée. Troisièmement, MoDEMO, un nouveau cadre de gestion d'élasticité unifié, basé sur un standard, dirigé par les modèles, hautement extensible et reconfigurable, supportant plusieurs stratégies, différents types d’élasticité, différentes techniques de virtualisation et plusieurs fournisseurs de Cloud. / Cloud computing has been gaining popularity and has received a great deal of attention from both industrial and academic worlds since it frees them from the burden and cost of managing local data centers. However, the main factor motivating the use of cloud is its ability to provide resources according to the customer needs or what is referred to as elasticity. Adapting cloud applications during their execution according to demand variation is a challenging task. In addition, cloud elasticity is diverse and heterogeneous because it encompasses different approaches, policies, purposes, etc. We are interested in investigating: How to overcome the problem of over-provisioning/under-provisioning? How to guaranty the resource availability and overcome the problems of heterogeneity and resource granularity? How to standardize, unify elasticity solutions and model its diversity at a high level of abstraction? In this thesis, we solved such challenges and we investigated many aspects of elasticity to manage efficiently the resources in the cloud. Three contributions are proposed. Firstly, an up-to-date state-of-the-art of the cloud elasticity, this state of art reviews different works related to elasticity for both Virtual Machines and containers. Secondly, ElasticDocker, an approach to manage container elasticity including vertical elasticity, live migration, and elasticity combination between different virtualization techniques. Thirdly, MoDEMO, a new unified standard-based, model-driven, highly extensible and reconfigurable framework that supports multiple elasticity policies, vertical and horizontal elasticity, different virtualization techniques and multiple cloud providers.

De nos jours, de nombreuses entreprises choisissent de plus en plus d'adopter le cloud computing. Plus précisément, en tant que clients, elles externalisent la gestion de leur infrastructure physique vers des centres de données (ou plateformes de cloud computing). La consommation d'énergie est une préoccupation majeure pour la gestion des centres de données (datacenter, DC). Son impact financier représente environ 80% du coût total de possession et l'on estime qu'en 2020, les DCs américains dépenseront à eux seuls environ 13 milliards de dollars en factures énergétiques. Généralement, les serveurs de centres de données sont conçus de manière à atteindre une grande efficacité énergétique pour des utilisations élevées. Pour diminuer le coût de calcul, les serveurs de centre de données devraient maximiser leur utilisation. Afin de lutter contre l'utilisation historiquement faible des serveurs, le cloud computing a adopté la virtualisation des serveurs. Cette dernière permet à un serveur physique d'exécuter plusieurs serveurs virtuels (appelés machines virtuelles) de manière isolée. Avec la virtualisation, le fournisseur de cloud peut regrouper (consolider) l'ensemble des machines virtuelles (VM) sur un ensemble réduit de serveurs physiques et ainsi réduire le nombre de serveurs actifs. Même ainsi, les serveurs de centres de données atteignent rarement des utilisations supérieures à 50%, ce qui signifie qu'ils fonctionnent avec des ensembles de ressources majoritairement inutilisées (appelés «trous»). Ma première contribution est un système de gestion de cloud qui divise ou fusionne dynamiquement les machines virtuelles de sorte à ce qu'elles puissent mieux remplir les trous. Cette solution n'est efficace que pour des applications élastiques, c'est-à-dire des applications qui peuvent être exécutées et reconfigurées sur un nombre arbitraire de machines virtuelles. Cependant, la fragmentation des ressources provient d'un problème plus fondamental. On observe que les applications cloud demandent de plus en plus de mémoire, tandis que les serveurs physiques fournissent plus de CPU. Dans les DC actuels, les deux ressources sont fortement couplées puisqu'elles sont liées à un serveur physique. Ma deuxième contribution est un moyen pratique de découpler la paire CPU-mémoire, qui peut être simplement appliquée à n'importe quel serveur. Ainsi, les deux ressources peuvent varier indépendamment, en fonction de leur demande. Ma troisième et ma quatrième contribution montrent un système pratique qui exploite la deuxième contribution. La sous-utilisation observée sur les serveurs physiques existe également pour les machines virtuelles. Il a été démontré que les machines virtuelles ne consomment qu'une petite fraction des ressources allouées car les clients du cloud ne sont pas en mesure d'estimer correctement la quantité de ressources nécessaire à leurs applications. Ma troisième contribution est un système qui estime la consommation de mémoire (c'est-à-dire la taille du working set) d'une machine virtuelle, avec un surcoût faible et une grande précision. Ainsi, nous pouvons maintenant consolider les machines virtuelles en fonction de la taille de leur working set (plutôt que leur mémoire réservée). Cependant, l'inconvénient de cette approche est le risque de famine de mémoire. Si une ou plusieurs machines virtuelles ont une forte augmentation de la demande en mémoire, le serveur physique peut manquer de mémoire. Cette situation n'est pas souhaitable, car la plate-forme cloud est incapable de fournir au client la mémoire qu'il a payée. Finalement, ma quatrième contribution est un système qui permet à une machine virtuelle d'utiliser la mémoire distante fournie par un autre serveur du rack. Ainsi, dans le cas d'un pic de la demande en mémoire, mon système permet à la VM d'allouer de la mémoire sur un serveur physique distant. / Nowadays, many organizations choose to increasingly implement the cloud computing approach. More specifically, as customers, these organizations are outsourcing the management of their physical infrastructure to data centers (or cloud computing platforms). Energy consumption is a primary concern for datacenter (DC) management. Its cost represents about 80% of the total cost of ownership and it is estimated that in 2020, the US DCs alone will spend about $13 billion on energy bills. Generally, the datacenter servers are manufactured in such a way that they achieve high energy efficiency at high utilizations. Thereby for a low cost per computation all datacenter servers should push the utilization as high as possible. In order to fight the historically low utilization, cloud computing adopted server virtualization. The latter allows a physical server to execute multiple virtual servers (called virtual machines) in an isolated way. With virtualization, the cloud provider can pack (consolidate) the entire set of virtual machines (VMs) on a small set of physical servers and thereby, reduce the number of active servers. Even so, the datacenter servers rarely reach utilizations higher than 50% which means that they operate with sets of longterm unused resources (called 'holes'). My first contribution is a cloud management system that dynamically splits/fusions VMs such that they can better fill the holes. This solution is effective only for elastic applications, i.e. applications that can be executed and reconfigured over an arbitrary number of VMs. However the datacenter resource fragmentation stems from a more fundamental problem. Over time, cloud applications demand more and more memory but the physical servers provide more an more CPU. In nowadays datacenters, the two resources are strongly coupled since they are bounded to a physical sever. My second contribution is a practical way to decouple the CPU-memory tuple that can simply be applied to a commodity server. Thereby, the two resources can vary independently, depending on their demand. My third and my forth contribution show a practical system which exploit the second contribution. The underutilization observed on physical servers is also true for virtual machines. It has been shown that VMs consume only a small fraction of the allocated resources because the cloud customers are not able to correctly estimate the resource amount necessary for their applications. My third contribution is a system that estimates the memory consumption (i.e. the working set size) of a VM, with low overhead and high accuracy. Thereby, we can now consolidate the VMs based on their working set size (not the booked memory). However, the drawback of this approach is the risk of memory starvation. If one or multiple VMs have an sharp increase in memory demand, the physical server may run out of memory. This event is undesirable because the cloud platform is unable to provide the client with the booked memory. My fourth contribution is a system that allows a VM to use remote memory provided by a different rack server. Thereby, in the case of a peak memory demand, my system allows the VM to allocate memory on a remote physical server.

Business intelligence (BI) has emerged as a key technology to be hosted on Cloud computing. BI offers a method to analyse data thereby enabling informed decision making to improve business performance and profitability. However, within the shared domains of Cloud computing, BI is exposed to increased security and privacy threats because an unauthorised user may be able to gain access to highly sensitive, consolidated business information. The business process contains collaborating services and users from multiple Cloud systems in different security realms which need to be engaged dynamically at runtime. If the heterogamous Cloud systems located in different security realms do not have direct authentication relationships then it is technically difficult to enable a secure collaboration. In order to address these security challenges, a new authentication framework is required to establish certain trust relationships among these BI service instances and users by distributing a common session secret to all participants of a session. The author addresses this challenge by designing and implementing a multiparty authentication framework for dynamic secure interactions when members of different security realms want to access services. The framework takes advantage of the trust relationship between session members in different security realms to enable a user to obtain security credentials to access Cloud resources in a remote realm. This mechanism can help Cloud session users authenticate their session membership to improve the authentication processes within multi-party sessions. The correctness of the proposed framework has been verified by using BAN Logics. The performance and the overhead have been evaluated via simulation in a dynamic environment. A prototype authentication system has been designed, implemented and tested based on the proposed framework. The research concludes that the proposed framework and its supporting protocols are an effective functional basis for practical implementation testing, as it achieves good scalability and imposes only minimal performance overhead which is comparable with other state-of-art methods.

E-handelsföretagen försöker ständigt sträva efter expansion. Samtidigt så vill de ha en IT-lösning som är så kostnadseffektiv som möjligt. Säkerhet är också någonting som företagen värderar väldigt högt. Cloud services är något som kan användas för detta. Men e-handelsföretagen måste först och främst känna att de har någonting att utvinna av dessa. Säkerheten är här ett hinder. Efter våra intervjuer med e-handelsföretagen inom klädesbranschen i Borås så betonade samtliga företag hur viktigt det var att hemlig företagsinformation absolut inte fick läcka ut. Det är säkerhet som är den största frågan med moln. Ansvaret för säkerheten ligger just på företaget som köper tjänstens sida. Även om en cloud provider erbjuder säkerhet, backup och bra upptid, så är det fortfarande upp till företaget att se till att de levererar detta. Samtidigt så går det mycket diskussion kring ämnet och många menar att det är nytt och bristen på kunskap som gör att företagen är rädda för riskerna. Vill företaget absolut inte att utomstående ska få komma åt viktig företagsinformation, då kan de välja att ha en kombination av privata och publika moln i det som kallas hybridmoln. Detta beror på att privata moln är byggda och driftade inom företaget. På så vis är data som finns lagrat i det privata molnet inte delat med andra företag. Det viktiga är för företaget att själva se vad de själva har för krav på säkerhet. Finns det krav på säkerhet på vissa delar men inte på andra, så kan hybridmoln vara en lösning. Genom att intervjua tre av de största e-handelsföretagen i Borås så har vi sett en tendens till detta.Det finns många områden som de företag vi intervjuat skulle kunna använda sig av cloud services på. Vi har fokuserat på kärnverksamheten, de stödsystem som de använde, webbsidan, kommunikation och kontorsprogram. Anledningen till detta är att företagen som vi intervjuat tyckte att dessa delar var viktigast. / Program: Kandidatutbildning i informatik

Studien avser att beskriva om och hur faktorernakärnkompetens, osäkerhet, nyttoaspekter och kontroll/flexibilitet påverkat besluten vid inköp av cloud-tjänsten SaaS. Uppsatsen är en kvalitativ studie som är baserad på semistruktuerade intervjuer med nyckelpersoner på två små IT-företag samt vetenskapliga artiklar och litteratur inom ämnesområdet. Studiens slutsats är att de båda företagen påverkats av några eller alla faktorer vid inköpen av cloud-tjänsten. Faktorn nyttoaspekter påverkade båda företagens inköpsbeslut i hög grad. Faktorerna osäkerhet och kontroll/flexibilitet påverkade inte alls inköpsbeslutet hos det ena företaget medan de till stor del påverkade inköpsbeslutet hos det andra företaget. Faktorn kärnverksamhet påverkade det ena företagets inköpsbeslut till en viss del och det andra företaget till en stor del.

A Differential Mobility Analyzer/Tandem Differential Mobility Analyzer (DMA/TDMA) system was used to measure simultaneously the size distribution and hygroscopicity of the ambient aerosol population. The system was operated aboard the National Center for Atmospheric Research/National Science Foundation (NCAR/NSF) C-130 during the 2006 Megacity Initiative: Local and Global Research Observations (MILAGRO) field campaign followed by the 2006 Intercontinental Chemical Transport Experiment – Phase B (INTEX-B) field campaign. The research flights for the MILAGRO campaign were conducted within the Mexico City basin and the region to the northeast within the pollution plume. The aerosol within the basin is dominated by organics with an average measured kappa value of 0.21 /- 0.18, 0.13 /- 0.09, 0.09 /- 0.06, 0.14 /- 0.07, and 0.17 /- 0.04 for dry particle diameters of 0.025, 0.050, 0.100, 0.200, and 0.300 mu m, respectively. As the aerosols are transported away from the Mexico City Basin, secondary organic aerosol formation through oxidation and condensation of sulfate on the aerosols surface rapidly increases the solubility of the aerosol. The most pronounced change occurs for a 0.100 mu m diameter aerosol where, after 6 hours of transport, the average kappa value increased by a factor of 3 to a kappaof 0.29 /- 0.13. The rapid increase in solubility increases the fraction of the aerosol size distribution that could be activated within a cloud. The research flights for the INTEX-B field campaign investigated the evolution of the physicochemical properties of the Asian aerosol plume after 3 to 7 days of transport. The Asian aerosol within the free troposphere exhibited a bimodal growth distribution roughly 50 percent of the time. The more soluble mode of the growth distribution contributed between 67-80 percent of the overall growth distribution and had an average kappabetween 0.40 and 0.53 for dry particle diameters of 0.025, 0.050, 0.100, and 0.300 mu m. The secondary mode was insoluble with an average kappabetween 0.01 and 0.05 for all dry particle diameters. Cloud condensation nuclei closure was attained at a supersaturation of 0.2 percent for all particles within the free troposphere by either assuming a pure ammonium bisulfate composition or a binary composition of ammonium bisulfate and an insoluble organic.