TANGO: Transparent heterogeneous hardware Architecture deployment for eNergy Gain in Operation

The paper is concerned with the issue of how software systems actually use Heterogeneous Parallel Architectures (HPAs), with the goal of optimizing power consumption on these resources. It argues the need for novel methods and tools to support software developers aiming to optimise power consumption resulting from designing, developing, deploying and running software on HPAs, while maintaining other quality aspects of software to adequate and agreed levels. To do so, a reference architecture to support energy efficiency at application construction, deployment, and operation is discussed, as well as its implementation and evaluation plans.Comment: Part of the Program Transformation for Programmability in Heterogeneous Architectures (PROHA) workshop, Barcelona, Spain, 12th March 2016, 7 pages, LaTeX, 3 PNG figure

Risk-driven proactive fault-tolerant operation of IaaS providers

In order to improve service execution in Clouds, the management of Cloud Infrastructure has to take measures to adhere to Service Level Agreements and Business Level Objectives, from the application layer through to how services are supported at the lowest hardware levels. In this paper a risk model methodology and holistic management approach is developed specific to the operation of the Cloud Infrastructure Provider and is applied through improvements to SLA fault tolerance in Cloud Infrastructure. Risk assessments are used to analyse execution specific data from the Cloud Infrastructure and linked to a business driven holistic management component that is part of a Cloud Manager. Initial results show improved eco-efficiency, virtual machine availability and reductions in SLA failure across the whole Cloud infrastructure by applying our combined risk-based fault tolerance approach.Postprint (author’s final draft

Risk driven Smart Home resource management using cloud services

In order to fully exploit the concept of Smart Home, challenges associated with multiple device management in consumer facing applications have to be addressed. Specific to this is the management of resource usage in the home via the improved utilization of devices, this is achieved by integration with the wider environment they operate in. The traditional model of the isolated device no longer applies, the future home will be connected with services provided by third parties ranging from supermarkets to domestic appliance manufacturers. In order to achieve this risk based integrated device management and contextualization is explored in this paper based on the cloud computing model. We produce an architecture and evaluate risk models to assist in this management of devices from a security, privacy and resource management perspective. We later propose an expansion on the risk based approach to wider data sharing between the home and external services using the key indicators of TREC (Trust, Risk, Eco-efficiency and Cost). The paper contributes to Smart Home research by defining how Cloud service management principles of risk and contextualization for virtual machines can produce solutions to emerging challenges facing a new generation of Smart Home devices

Energy efficiency embedded service lifecycle: Towards an energy efficient cloud computing architecture

The paper argues the need to provide novel methods and tools to support software developers aiming to optimise energy efficiency and minimise the carbon footprint resulting from designing, developing, deploying and running software in Clouds, while maintaining other quality aspects of software to adequate and agreed levels. A cloud architecture to support energy efficiency at service construction, deployment, and operation is discussed, as well as its implementation and evaluation plans.Postprint (published version

Energy-Aware Profiling for Cloud Computing Environments

Cloud Computing has changed the way in which people use the IT resources today. Now, instead of buying their own IT resources, they can use the services offered by Cloud Computing with reasonable costs based on a "pay-per-use" model. However, with the wide adoption of Cloud Computing, the costs for maintaining the Cloud infrastructure have become a vital issue for the providers, especially with the large input of energy costs to underpin these resources. Thus, this paper proposes a system architecture that can be used for profiling the resources usage in terms of the energy consumption. From the profiled data, the application developers can enhance their energy-aware decisions when creating or optimising the applications to be more energy efficient. This paper also presents an adapted existing Cloud architecture to enable energy-aware profiling based on the proposed system. The results of the conducted experiments show energy-awareness at physical host and virtual machine levels

Enhancing quality of service in cloud computing through novel resource management

Distributed Systems as an area of research has seen a gradual evolution over the last few decades fuelled by the application of new use cases to technological developments. Cloud Computing is one such paradigm that has evolved from the adoption of Utility Computing, Virtualization and Service Oriented Architectures. Cloud Computing can be distinguished from other distributed paradigms though the provisioning of resources, data and software to users on demand in a similar fashion to the services provided by the electric power industry. Commercial Cloud offerings are expected to meet the Quality of Service (QoS) requirements of a consumer via Service Level Agreements (SLA). In reality, Cloud providers rarely provide QoS beyond best effort as the intrinsic fault tolerant nature of currently deployed applications require little more. Nevertheless, with enhancements to QoS in Cloud Computing the range of deployable applications can be improved and thus advance the overall adoption of the paradigm. This thesis tackles the shortcoming of QoS in Cloud Computing though novel enhancements to Cloud resource management. Since QoS is a broad subject area, the scope of research within has been narrowed down to two specific areas of interest: performance and scalability. In this thesis, the performance and scalability of Cloud technology are ascertained through performance evaluations on Hypervisor (such as XEN and KVM) and Cloud Infrastructure Managers (such as OpenNebula and Nimbus). Recommendations are made on how to resolve performance bottlenecks and on the suitability of certain technology for specific Cloud applications. Contextualisation and Re-contextualization mechanisms are introduced for self-configuring virtual Cloud resources at operation time while managing resources and software dependencies at the infrastructure and platform layer of the Cloud software stack. In addition, the thesis aims to improve the adoption of the Cloud by exploring novel techniques for composing, configuring and deploying Grid Middleware onto Cloud resources. The core contributions of this thesis are as follows: i) A prototype software tool for the (re-)contextualization of Cloud applications, platforms, infrastructures and resource dependencies that enables improvements to performance, scalability and fault tolerance. ii) Performance results and recommendations on the topic of Virtual Machine (VM) image propagation delay in Cloud infrastructure technology, Paravirtualized block device drivers and VM image standards in Hypervisor technology, for the purpose of ascertaining current limitations in Cloud QoS. iii) A software prototype system of an interoperable self-configuring Virtual Grid infrastructure, deployable on to a range of Cloud providers, to enhance the QoS achievable by Grid applications

A risk assessment framework for cloud computing

Cloud service providers offer access to their resources through formal service level agreements (SLA), and need well-balanced infrastructures so that they can maximise the quality of service (QoS) they offer and minimise the number of SLA violations. This paper focuses on a specific aspect of risk assessment as applied in cloud computing: methods within a framework that can be used by cloud service providers and service consumers to assess risk during service deployment and operation. It describes the various stages in the service lifecycle whereas risk assessment takes place, and the corresponding risk models that have been designed and implemented. The impact of risk on architectural components, with special emphasis on holistic management support at service operation, is also described. The risk assessor is shown to be effective through the experimental evaluation of the implementation, and is already integrated in a cloud computing toolkit.Peer Reviewe

Risk-driven proactive fault-tolerant operation of IaaS providers

In order to improve service execution in Clouds, the management of Cloud Infrastructure has to take measures to adhere to Service Level Agreements and Business Level Objectives, from the application layer through to how services are supported at the lowest hardware levels. In this paper a risk model methodology and holistic management approach is developed specific to the operation of the Cloud Infrastructure Provider and is applied through improvements to SLA fault tolerance in Cloud Infrastructure. Risk assessments are used to analyse execution specific data from the Cloud Infrastructure and linked to a business driven holistic management component that is part of a Cloud Manager. Initial results show improved eco-efficiency, virtual machine availability and reductions in SLA failure across the whole Cloud infrastructure by applying our combined risk-based fault tolerance approach