Cloud computing enables the delivery of remote computing, software and storage services through web browsers following pay-as-you-go model. In addition to successful commercial applications, many research efforts including DOE Magellan Cloud project focus on discovering the opportunities and challenges arising from the computing and data-intensive scientific applications that are not well addressed by the current supercomputers, Linux clusters and Grid technologies. The elastic resource provision, noninterfering resource sharing and flexible customized configuration provided by the Cloud infrastructure has shed light on efficient execution of many scientific applications modeled as Directed Acyclic Graph (DAG) structured workflows to enforce the intricate dependency among a large number of different processing tasks. Meanwhile, the Cloud environment poses various challenges. Cloud providers and Cloud users pursue different goals. Providers aim to maximize profit by achieving higher resource utilization and users want to minimize expenses while meeting their performance requirements. Moreover, due to the expanding Cloud services and emerging newer technologies, the ever-increasing heterogeneity of the Cloud environment complicates the challenges for both parties. In this thesis, we address the workflow scheduling problem from different applications and various objectives. For batch applications, due to the increasing deployment of many data centers and computer servers around the globe escalated by the higher electricity price, the energy cost on running the computing, communication and cooling together with the amount of CO2 emissions have skyrocketed. In order to maintain sustainable Cloud computing facing with ever-increasing problem complexity and big data size in the next decades, we design and develop energy-aware scientific workflow scheduling algorithm to minimize energy consumption and CO2 emission while still satisfying certain Quality of Service (QoS) such as response time specified in Service Level Agreement (SLA). Furthermore, the underlying Cloud hardware/Virtual Machine (VM) resource availability is time-dependent because of the dual operation modes namely on-demand and reservation instances at various Cloud data centers. We also apply techniques such as Dynamic Voltage and Frequency Scaling (DVFS) and DNS scheme to further reduce energy consumption within acceptable performance bounds. Our multiple-step resource provision and allocation algorithm achieves the response time requirement in the step of forward task scheduling and minimizes the VM overhead for reduced energy consumption and higher resource utilization rate in the backward task scheduling step. We also evaluate the candidacy of multiple data centers from the energy and performance efficiency perspectives as different data centers have various energy and cost related parameters. For streaming applications, we formulate scheduling problems with two different objectives, namely one is to maximize the throughput under a budget constraint while another is to minimize execution cost under a minimum throughput constraint. Two different algorithms named as Budget constrained RATE (B-RATE) and Budget constrained SWAP (B-SWAP) are designed under the first objective; Another two algorithms, namely Throughput constrained RATE (TP-RATE) and Throughput constrained SWAP (TP-SWAP) are developed under the second objective.

Esta tese de Doutorado tem como objetivo apresentar uma arquitetura para metaescalonamento verde com provisão de qualidade de serviço em uma nuvem privada denominada GreenMACC. Essa nova arquitetura oferece a automatização na escolha de políticas em quatro estágios de escalonamento de uma nuvem privada, permitindo cumprir a negociação que foi estabelecida com o usuário. Devido a essa função, é possível garantir que o GreenMACC se comporte seguindo os princípios da computação verde sem deixar de se preocupar com a qualidade do serviço. Nesta tese o GreenMACC é apresentado, detalhado, discutido, validado e avaliado. Com os resultados apresentados pode-se concluir que a arquitetura proposta mostrou-se consistente, permitindo a execução dos serviços requisitados com diversas políticas de escalonamento em todos os seus estágios. Além disso, demonstrou flexibilidade em receber novas políticas, com focos verde e de qualidade de serviço, e eficiência na escolha das políticas de escalonamento de acordo com a negociação feita com o usuário. / This PhD thesis aims to present an architecture for green metascheduling with provision of quality of service in a private cloud called GreenMACC. This new architecture offers the possibility of choosing automatically the four stage scheduling policies of a private cloud, allowing to reach the users negotiation. As a result of this function, it is possible to ensure that GreenMACCs behavior follows the green computing principles and also is worried about the quality of the service. In this thesis Green- MACC is presented, particularized, discussed, validated and evaluated. The results show that the proposed architecture is consistent, allowing the execution of the requested services considering various scheduling policies in the stages. Moreover, GreenMACC proves to be flexible as allows new policies, focusing on green and quality of service, and to be efficient as chooses the scheduling policies following the users negotiation.

Esta tese de Doutorado tem como objetivo apresentar uma arquitetura para metaescalonamento verde com provisão de qualidade de serviço em uma nuvem privada denominada GreenMACC. Essa nova arquitetura oferece a automatização na escolha de políticas em quatro estágios de escalonamento de uma nuvem privada, permitindo cumprir a negociação que foi estabelecida com o usuário. Devido a essa função, é possível garantir que o GreenMACC se comporte seguindo os princípios da computação verde sem deixar de se preocupar com a qualidade do serviço. Nesta tese o GreenMACC é apresentado, detalhado, discutido, validado e avaliado. Com os resultados apresentados pode-se concluir que a arquitetura proposta mostrou-se consistente, permitindo a execução dos serviços requisitados com diversas políticas de escalonamento em todos os seus estágios. Além disso, demonstrou flexibilidade em receber novas políticas, com focos verde e de qualidade de serviço, e eficiência na escolha das políticas de escalonamento de acordo com a negociação feita com o usuário. / This PhD thesis aims to present an architecture for green metascheduling with provision of quality of service in a private cloud called GreenMACC. This new architecture offers the possibility of choosing automatically the four stage scheduling policies of a private cloud, allowing to reach the users negotiation. As a result of this function, it is possible to ensure that GreenMACCs behavior follows the green computing principles and also is worried about the quality of the service. In this thesis Green- MACC is presented, particularized, discussed, validated and evaluated. The results show that the proposed architecture is consistent, allowing the execution of the requested services considering various scheduling policies in the stages. Moreover, GreenMACC proves to be flexible as allows new policies, focusing on green and quality of service, and to be efficient as chooses the scheduling policies following the users negotiation.

Molntjänster är ett snabbt växande område och utgör en viktig funktion i samhället och för verksamheter. Det som driver molntjänster är storskaliga datacenter som samlar tusentals servrar med infrastruktur. Dessa datacenter kräver en hög energianvändning för att drivas vilket utgör ett stort koldioxidutsläpp. Leverantörer upplever ökade krav i hållbarhetsfrågor och arbetar aktivt för att möta dessa krav. Verksamheter har därför en betydande roll i hur leverantörer arbetar med hållbarhet genom att ställa hållbarhetskrav. Det finns däremot utmaningar med att ställa hållbarhetskrav vilket är brist på kunskap, strategier och resurser.  Studien avser att identifiera de ekologiska hållbarhetsaspekter som verksamheter kan kravställa mot molntjänstleverantörer. Syftet med studien var att förmedla kunskap om vilka ekologiska hållbarhetsaspekter som kan appliceras i verksamheters kravspecifikation mot molntjänstleverantörer. Tidigare forskning beskriver hållbarhetsaspekter som molntjänstleverantörer kan applicera för att minska sitt koldioxidutsläpp. Dessa aspekter är: miljöcertifiering, nyckeltal, förnybar energi och energieffektiviserade strategier. Studien antog en kvalitativ forskningsansats. Datainsamlingen utfördes genom semistrukturerade intervjuer. Analysen utfördes med en tematisk analysmetod och det identifierades tre teman vilket är kunskapslucka, prioritering och resursbehov. Studien diskuterar dessa teman i relation till tidigare forskning kring hållbarhetsaspekterna och utmaningar.  Slutsatsen av studien är fem identifierade hållbarhetsaspekter som är: miljöcertifiering, nyckeltal, förnybar energi, geografisk plats och energieffektiviserade strategier. Dessa hållbarhetsaspekter kan verksamheter kravställa mot molntjänstleverantörer och kan reducera utmaningarna med att identifiera hållbarhetskrav. / Cloud services are a rapidly growing field and play a crucial role in society and businesses. What drives cloud services are large-scale data centers that house thousands of servers with infrastructure. These data centers require high energy consumption to operate, resulting in significant carbon emissions. Providers are facing increased demands for sustainability and actively working to meet these requirements. Businesses, therefore, have a significant role in influencing how providers approach sustainability by setting sustainability criteria. However, there are challenges in setting sustainability requirements due to a lack of knowledge, strategies, and resources. This study aims to identify the ecological sustainability aspects that businesses can demand from cloud service providers. The purpose of the study was to provide knowledge about the ecological sustainability aspects that can be included in businesses' specifications when selecting cloud service providers. Previous research describes sustainability aspects that cloud service providers can implement to reduce their carbon emissions. These aspects include environmental certification, key performance indicators, renewable energy, and energy-efficient strategies. The study adopted a qualitative research approach. Data collection was conducted through semi-structured interviews. The analysis was performed using thematic analysis, and three themes were identified: knowledge gap, prioritization, and resource requirements. The study discusses these themes in relation to previous research on sustainability aspects and challenges. The conclusion of the study highlights five identified sustainability aspects: environmental certification, key performance indicators, renewable energy, geographical location, and energy-efficient strategies. These sustainability aspects can be demanded by businesses from cloud service providers and can help address the challenges of identifying sustainability requirements.