Competitive Cloud Resource Procurements via Cloud Brokerage

In current IaaS cloud markets, tenant consumers non-cooperatively compete for cloud resources via demand quantities, and the service quality is offered in a best effort manner. To better exploit tenant demand correlation, cloud brokerage services provide cloud resource multiplexing so as to earn profits by receiving volume discounts from cloud providers. A fundamental but daunting problem facing a tenant consumer is competitive resource procurements via cloud brokerage. In this paper, we investigate this problem via non-cooperative game modeling. In the static game, to maximize the experienced surplus, tenants judiciously select optimal demand responses given pricing strategies of cloud brokers and complete information of the other tenants' demands. We also derive Nash equilibrium of the non-cooperative game for competitive resource procurements. Performance evaluation on Nash equilibrium reveals insightful observations for both theoretical analysis and practical cloud resource procurements scheme design.published_or_final_versio

Competitive Bandwidth Reservation via Cloud Brokerage for Video Streaming Applications

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Measuring the Business Value of Cloud Computing

The importance of demonstrating the value achieved from IT investments is long established in the Computer Science (CS) and Information Systems (IS) literature. However, emerging technologies such as the ever-changing complex area of cloud computing present new challenges and opportunities for demonstrating how IT investments lead to business value. Recent reviews of extant literature highlights the need for multi-disciplinary research. This research should explore and further develops the conceptualization of value in cloud computing research. In addition, there is a need for research which investigates how IT value manifests itself across the chain of service provision and in inter-organizational scenarios. This open access book will review the state of the art from an IS, Computer Science and Accounting perspective, will introduce and discuss the main techniques for measuring business value for cloud computing in a variety of scenarios, and illustrate these with mini-case studies

Measuring the Business Value of Cloud Computing

The importance of demonstrating the value achieved from IT investments is long established in the Computer Science (CS) and Information Systems (IS) literature. However, emerging technologies such as the ever-changing complex area of cloud computing present new challenges and opportunities for demonstrating how IT investments lead to business value. Recent reviews of extant literature highlights the need for multi-disciplinary research. This research should explore and further develops the conceptualization of value in cloud computing research. In addition, there is a need for research which investigates how IT value manifests itself across the chain of service provision and in inter-organizational scenarios. This open access book will review the state of the art from an IS, Computer Science and Accounting perspective, will introduce and discuss the main techniques for measuring business value for cloud computing in a variety of scenarios, and illustrate these with mini-case studies

At the crossroads of big science, open science, and technology transfer

Les grans infraestructures científiques s’enfronten a demandes creixents de responsabilitat pública, no només per la seva contribució al descobriment científic, sinó també per la seva capacitat de generar valor econòmic secundari. Per construir i operar les seves infraestructures sofisticades, sovint generen tecnologies frontereres dissenyant i construint solucions tècniques per a problemes d’enginyeria complexos i sense precedents. En paral·lel, la dècada anterior ha presenciat la ràpida irrupció de canvis tecnològics que han afectat la manera com es fa i es comparteix la ciència, cosa que ha comportat l’emergència del concepte d’Open Science (OS). Els governs avancen ràpidament vers aquest paradigma de OS i demanen a les grans infraestructures científiques que "obrin" els seus processos científics. No obstant, aquestes dues forces s'oposen, ja que la comercialització de tecnologies i resultats científics requereixen normalment d’inversions financeres importants i les empreses només estan disposades a assumir aquest cost si poden protegir la innovació de la imitació o de la competència deslleial. Aquesta tesi doctoral té com a objectiu comprendre com les noves aplicacions de les TIC afecten els resultats de la recerca i la transferència de tecnologia resultant en el context de les grans infraestructures científiques. La tesis pretén descobrir les tensions entre aquests dos vectors normatius, així com identificar els mecanismes que s’utilitzen per superar-les. La tesis es compon de quatre estudis: 1) Un estudi que aplica un mètode de recerca mixt que combina dades de dues enquestes d’escala global realitzades online (2016, 2018), amb dos cas d’estudi de dues comunitats científiques en física d’alta energia i biologia molecular que avaluen els factors explicatius darrere les pràctiques de compartir dades per part dels científics; 2) Un estudi de cas d’Open Targets, una infraestructura d’informació basada en dades considerades bens comuns, on el Laboratori Europeu de Biologia Molecular-EBI i empreses farmacèutiques col·laboren i comparteixen dades científiques i eines tecnològiques per accelerar el descobriment de medicaments; 3) Un estudi d’un conjunt de dades únic de 170 projectes finançats en el marc d’ATTRACT (un nou instrument de la Comissió Europea liderat per les grans infraestructures científiques europees) que té com a objectiu comprendre la naturalesa del procés de serendipitat que hi ha darrere de la transició de tecnologies de grans infraestructures científiques a aplicacions comercials abans no anticipades. ; i 4) un cas d’estudi sobre la tecnologia White Rabbit, un hardware sofisticat de codi obert desenvolupat al Consell Europeu per a la Recerca Nuclear (CERN) en col·laboració amb un extens ecosistema d’empreses.Las grandes infraestructuras científicas se enfrentan a crecientes demandas de responsabilidad pública, no solo por su contribución al descubrimiento científico sino también por su capacidad de generar valor económico para la sociedad. Para construir y operar sus sofisticadas infraestructuras, a menudo generan tecnologías de vanguardia al diseñar y construir soluciones técnicas para problemas de ingeniería complejos y sin precedentes. Paralelamente, la década anterior ha visto la irrupción de rápidos cambios tecnológicos que afectan la forma en que se genera y comparte la ciencia, lo que ha llevado a acuñar el concepto de Open Science (OS). Los gobiernos se están moviendo rápidamente hacia este nuevo paradigma y están pidiendo a las grandes infraestructuras científicas que "abran" el proceso científico. Sin embargo, estas dos fuerzas se oponen, ya que la comercialización de tecnología y productos científicos generalmente requiere importantes inversiones financieras y las empresas están dispuestas a asumir este coste solo si pueden proteger la innovación de la imitación o la competencia desleal. Esta tesis doctoral tiene como objetivo comprender cómo las nuevas aplicaciones de las TIC están afectando los resultados científicos y la transferencia de tecnología resultante en el contexto de las grandes infraestructuras científicas. La tesis pretende descubrir las tensiones entre estas dos fuerzas normativas e identificar los mecanismos que se emplean para superarlas. La tesis se compone de cuatro estudios: 1) Un estudio que emplea un método mixto de investigación que combina datos de dos encuestas de escala global realizadas online (2016, 2018), con dos caso de estudio sobre dos comunidades científicas distintas -física de alta energía y biología molecular- que evalúan los factores explicativos detrás de las prácticas de intercambio de datos científicos; 2) Un caso de estudio sobre Open Targets, una infraestructura de información basada en datos considerados como bienes comunes, donde el Laboratorio Europeo de Biología Molecular-EBI y compañías farmacéuticas colaboran y comparten datos científicos y herramientas tecnológicas para acelerar el descubrimiento de fármacos; 3) Un estudio de un conjunto de datos único de 170 proyectos financiados bajo ATTRACT, un nuevo instrumento de la Comisión Europea liderado por grandes infraestructuras científicas europeas, que tiene como objetivo comprender la naturaleza del proceso fortuito detrás de la transición de las tecnologías de grandes infraestructuras científicas a aplicaciones comerciales previamente no anticipadas ; y 4) un estudio de caso de la tecnología White Rabbit, un sofisticado hardware de código abierto desarrollado en el Consejo Europeo de Investigación Nuclear (CERN) en colaboración con un extenso ecosistema de empresas.Big science infrastructures are confronting increasing demands for public accountability, not only within scientific discovery but also their capacity to generate secondary economic value. To build and operate their sophisticated infrastructures, big science often generates frontier technologies by designing and building technical solutions to complex and unprecedented engineering problems. In parallel, the previous decade has seen the disruption of rapid technological changes impacting the way science is done and shared, which has led to the coining of the concept of Open Science (OS). Governments are quickly moving towards the OS paradigm and asking big science centres to "open up” the scientific process. Yet these two forces run in opposition as the commercialization of scientific outputs usually requires significant financial investments and companies are willing to bear this cost only if they can protect the innovation from imitation or unfair competition. This PhD dissertation aims at understanding how new applications of ICT are affecting primary research outcomes and the resultant technology transfer in the context of big and OS. It attempts to uncover the tensions in these two normative forces and identify the mechanisms that are employed to overcome them. The dissertation is comprised of four separate studies: 1) A mixed-method study combining two large-scale global online surveys to research scientists (2016, 2018), with two case studies in high energy physics and molecular biology scientific communities that assess explanatory factors behind scientific data-sharing practices; 2) A case study of Open Targets, an information infrastructure based upon data commons, where European Molecular Biology Laboratory-EBI and pharmaceutical companies collaborate and share scientific data and technological tools to accelerate drug discovery; 3) A study of a unique dataset of 170 projects funded under ATTRACT -a novel policy instrument of the European Commission lead by European big science infrastructures- which aims to understand the nature of the serendipitous process behind transitioning big science technologies to previously unanticipated commercial applications; and 4) a case study of White Rabbit technology, a sophisticated open-source hardware developed at the European Council for Nuclear Research (CERN) in collaboration with an extensive ecosystem of companies

Generic Methods for Adaptive Management of Service Level Agreements in Cloud Computing

The adoption of cloud computing to build and deliver application services has been nothing less than phenomenal. Service oriented systems are being built using disparate sources composed of web services, replicable datastores, messaging, monitoring and analytics functions and more. Clouds augment these systems with advanced features such as high availability, customer affinity and autoscaling on a fair pay-per-use cost model. The challenge lies in using the utility paradigm of cloud beyond its current exploit. Major trends show that multi-domain synergies are creating added-value service propositions. This raises two questions on autonomic behaviors, which are specifically ad- dressed by this thesis. The first question deals with mechanism design that brings the customer and provider(s) together in the procurement process. The purpose is that considering customer requirements for quality of service and other non functional properties, service dependencies need to be efficiently resolved and legally stipulated. The second question deals with effective management of cloud infrastructures such that commitments to customers are fulfilled and the infrastructure is optimally operated in accordance with provider policies. This thesis finds motivation in Service Level Agreements (SLAs) to answer these questions. The role of SLAs is explored as instruments to build and maintain trust in an economy where services are increasingly interdependent. The thesis takes a wholesome approach and develops generic methods to automate SLA lifecycle management, by identifying and solving relevant research problems. The methods afford adaptiveness in changing business landscape and can be localized through policy based controls. A thematic vision that emerges from this work is that business models, services and the delivery technology are in- dependent concepts that can be finely knitted together by SLAs. Experimental evaluations support the message of this thesis, that exploiting SLAs as foundations for market innovation and infrastructure governance indeed holds win-win opportunities for both cloud customers and cloud providers

Using Workload Prediction and Federation to Increase Cloud Utilization

The wide-spread adoption of cloud computing has changed how large-scale computing infrastructure is built and managed. Infrastructure-as-a-Service (IaaS) clouds consolidate different separate workloads onto a shared platform and provide a consistent quality of service by overprovisioning capacity. This additional capacity, however, remains idle for extended periods of time and represents a drag on system efficiency.The smaller scale of private IaaS clouds compared to public clouds exacerbates overprovisioning inefficiencies as opportunities for workload consolidation in private clouds are limited. Federation and cycle harvesting capabilities from computational grids help to improve efficiency, but to date have seen only limited adoption in the cloud due to a fundamental mismatch between the usage models of grids and clouds. Computational grids provide high throughput of queued batch jobs on a best-effort basis and enforce user priorities through dynamic job preemption, while IaaS clouds provide immediate feedback to user requests and make ahead-of-time guarantees about resource availability.We present a novel method to enable workload federation across IaaS clouds that overcomes this mismatch between grid and cloud usage models and improves system efficiency while also offering availability guarantees. We develop a new method for faster-than-realtime simulation of IaaS clouds to make predictions about system utilization and leverage this method to estimate the future availability of preemptible resources in the cloud. We then use these estimates to perform careful admission control and provide ahead-of-time bounds on the preemption probability of federated jobs executing on preemptible resources. Finally, we build an end-to-end prototype that addresses practical issues of workload federation and evaluate the prototype's efficacy using real-world traces from big data and compute-intensive production workloads

Digital Transformation. Understanding Business Goals, Risks, Processes, and Decisions

Whilst digitisation is far from a new concept, many assume that simply introducing automation and information systems in various forms will be enough to make their organisation’s operations more efficient. This misconception can often lead to disarray and costly mistakes. Digital Transformation: Understanding Business Goals, Risks, Processes, and Decisions shows how to avoid such issues via careful consideration of what an enterprise really needs. Unlike many other books on digital transformation, the authors do not dwell on database design or the details of implementing information systems. Instead, they emphasise the importance of a clear understanding of all aspects of an organisation in order to effectively implement and manage digital systems, from business goals and strategies to structuring information and making decisions, risk assessments, project management, organising, and procuring services and products. Organised in eleven chapters, and drawing on examples from all over the world, this book will be of interest to university students of business administration, management, information systems, and computer science, as well as practitioners seeking to better understand how to handle digital transformation in their own organisation

Rethinking the digital transformation using technology space analysis

The world is in the midst of a digital transformation. An intensified prevalence and use of digital technologies is fundamentally changing organizations and economies. However, the notion of 'digital transformation' is both theoretically and empirically underspecified. This paper rethinks the digital transformation narrative theoretically by embedding the concept in concurrent debates about technological revolutions and neo-Schumpeterian innovation theory. Empirically, the paper specifies the digital transformation by analysing the technological composition of key start-up and scale-up companies in the knowledge-intensive services sector. Undertaking a technology space analysis of 40,754 start-up and scale-up companies derived from the near real-time Dealroom.co database, we analyse which technologies and application domains are currently converging, distilling of key elements of the digital transformation. The paper concludes that the transmission of digital technologies is often indirect through ‘key enabling technology clusters’ that connect the technological vanguard to application domains