Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges

Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.Comment: 12 pages, 5 figures,Proceedings of the 2010 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA 2010), Las Vegas, USA, July 12-15, 201

Market Driven Multi-domain Network Service Orchestration in 5G Networks

The advent of a new breed of enhanced multimedia services has put network operators into a position where they must support innovative services while ensuring both end-to-end Quality of Service requirements and profitability. Recently, Network Function Virtualization (NFV) has been touted as a cost-effective underlying technology in 5G networks to efficiently provision novel services. These NFV-based services have been increasingly associated with multi-domain networks. However, several orchestration issues, linked to cross-domain interactions and emphasized by the heterogeneity of underlying technologies and administrative authorities, present an important challenge. In this paper, we tackle the cross-domain interaction issue by proposing an intelligent and profitable auction-based approach to allow inter-domains resource allocation

Power Management Techniques for Data Centers: A Survey

With growing use of internet and exponential growth in amount of data to be stored and processed (known as 'big data'), the size of data centers has greatly increased. This, however, has resulted in significant increase in the power consumption of the data centers. For this reason, managing power consumption of data centers has become essential. In this paper, we highlight the need of achieving energy efficiency in data centers and survey several recent architectural techniques designed for power management of data centers. We also present a classification of these techniques based on their characteristics. This paper aims to provide insights into the techniques for improving energy efficiency of data centers and encourage the designers to invent novel solutions for managing the large power dissipation of data centers.Comment: Keywords: Data Centers, Power Management, Low-power Design, Energy Efficiency, Green Computing, DVFS, Server Consolidatio

Ресурсозберігаючий розподіл навантаження для ефективного управління центром обробки даних із хмарними обчисленнями

Survey of research in resource-efficient computing and architectural principles forresource-efficient management of Clouds are offered in this article. Resource-efficient resource allocation policies and scheduling algorithms considering QoS expectations and power usage characteristics of the devices are defined.Определены  архитектурные рамки и принципы энергосберегающих облачных вычислений. Рассмотрены алгоритмы распределения для энергоэффективного управления в Cloud-вычислительных средах. Показаны ресурсосберегающие возможности центров обработки данных для предоставления эвристики распределения клиентских приложений, чтобы повысить эффективность энергопотребления центра обработки данных и определить согласованное качество обслуживания QoS. Приведен обзор исследований ресурсоэффективних вычислений. Предложены архитектурные принципы энергосберегающего управления облаками, политика распределения ресурсоэффективних возможностей и алгоритмы планирования с учетом ожидания QoS, особенности характеристик использования устройств, научно-исследовательские задачи, используя которые можно получить существенные выгоды для поставщиков и потребителей ресурсов.Визначено архітектурні рамки і принципи енергозберігаючих хмарних обчислень. Розглянуто алгоритми розподілу для енергоефективного управління в Cloud-обчислювальних середовищах. Показано ресурсозберігаючі можливості центрів обробки даних для надання евристики розподілу клієнтських додатків, щоб підвищити ефективність енергоспоживання центру обробки даних і визначити узгоджену якість обслуговування QoS. Подано огляд досліджень iз ресурсоефективних обчислень. Запропоновано архітектурні принципи енергозберігаючого управління хмарами, політика розподілу ресурсоефективних можливостей і алгоритми планування з урахуванням очікування QoS, особливості характеристик використання пристроїв, науково-дослідні завдання, використовуючи які можна отримати істотні вигоди для постачальників і споживачів ресурсів

Challenges in real-time virtualization and predictable cloud computing

Cloud computing and virtualization technology have revolutionized general-purpose computing applications in the past decade. The cloud paradigm offers advantages through reduction of operation costs, server consolidation, flexible system configuration and elastic resource provisioning. However, despite the success of cloud computing for general-purpose computing, existing cloud computing and virtualization technology face tremendous challenges in supporting emerging soft real-time applications such as online video streaming, cloud-based gaming, and telecommunication management. These applications demand real-time performance in open, shared and virtualized computing environments. This paper identifies the technical challenges in supporting real-time applications in the cloud, surveys recent advancement in real-time virtualization and cloud computing technology, and offers research directions to enable cloud-based real-time applications in the future

Software-Defined Cloud Computing: Architectural Elements and Open Challenges

The variety of existing cloud services creates a challenge for service providers to enforce reasonable Software Level Agreements (SLA) stating the Quality of Service (QoS) and penalties in case QoS is not achieved. To avoid such penalties at the same time that the infrastructure operates with minimum energy and resource wastage, constant monitoring and adaptation of the infrastructure is needed. We refer to Software-Defined Cloud Computing, or simply Software-Defined Clouds (SDC), as an approach for automating the process of optimal cloud configuration by extending virtualization concept to all resources in a data center. An SDC enables easy reconfiguration and adaptation of physical resources in a cloud infrastructure, to better accommodate the demand on QoS through a software that can describe and manage various aspects comprising the cloud environment. In this paper, we present an architecture for SDCs on data centers with emphasis on mobile cloud applications. We present an evaluation, showcasing the potential of SDC in two use cases-QoS-aware bandwidth allocation and bandwidth-aware, energy-efficient VM placement-and discuss the research challenges and opportunities in this emerging area.Comment: Keynote Paper, 3rd International Conference on Advances in Computing, Communications and Informatics (ICACCI 2014), September 24-27, 2014, Delhi, Indi

Service Level Agreements in Cloud Computing and Big Data

Now-a-days Most of the industries are having large volumes of data. Data has range of Tera bytes to Peta byte. Organizations are looking to handle the growth of data. Enterprises are using cloud deployments to address the big data and analytics with respect to the interaction between cloud and big data. This paper presents big data issues and research directions towards the ongoing work of processing of big data in the distributed environments

ON-DEMAND OPTIMUM RESOURCE PROVISIONING ON CLOUD

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