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

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

Energy Efficient Virtual Machine Migration in Cloud Data Centers

Cloud computing services have been on the rise over the past few decades, which has led to an increase in the number of data centers worldwide which increasingly consume more and more amount of energy for their operation, leading to high carbon dioxide emissions and also high operation costs. Cloud computing infrastructures are designed to support the accessibility and deployment of various service oriented applications by the users. The resources are the major source of the power consumption in data centers along with air conditioning and cooling equipment. Moreover the energy consumption in the cloud is proportional to the resource utilization and data centers are almost the worlds highest consumers of electricity. It is therefore, the need of the hour to devise efficient consolidation schemes for the cloud model to minimize energy and increase Return of Investment(ROI) for the users by decreasing the operating costs. The consolidation problem is NP-complete in nature, which requires heuristic techniques to get a sub-optimal solution. The complexity of the problem increases with increase in cloud infrastructure. We have proposed a new consolidation scheme for the virtual machines(VMs) by improving the host overload detection phase of the scheme. The resulting scheme is effective in reducing the energy and the level of Service Level Agreement(SLA) violations both, to a considerable extent. For testing the performance of our implementation on cloud we need a simulation environment that can provide us an environment with system and behavioural modelling of the actual cloud computing components, and can generate results that can help us in the analysis so that we can deploy them on actual clouds. CloudSim is one such simulation toolkit that allows us to test and analyse our allocation and selection algorithms. In this thesis we have used CloudSim version 3.0.3 to test and analyse our policies and modifications in the current policies. The advantages of using CloudSim 3.0.3 is that it takes very less effort and time to implement cloud-based application and we can test the performance of application services in heterogeneous Cloud environments. The observations are validated by simulating the experiment using the CLoudSim framework and the data provided by PlanetLab