Search for dissertations about: "Resource management in cloud computing"
Showing result 1 - 5 of 38 swedish dissertations containing the words Resource management in cloud computing.
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1. Energy-efficient cloud computing : autonomic resource provisioning for datacenters
Abstract : Energy efficiency has become an increasingly important concern in data centers because of issues associated with energy consumption, such as capital costs, operating expenses, and environmental impact. While energy loss due to suboptimal use of facilities and non-IT equipment has largely been reduced through the use of best-practice technologies, addressing energy wastage in IT equipment still requires the design and implementation of energy-aware resource management systems. READ MORE
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2. Cost- and Performance-Aware Resource Management in Cloud Infrastructures
Abstract : High availability, cost effectiveness and ease of application deployment have accelerated the adoption rate of cloud computing. This fast proliferation of cloud computing promotes the rapid development of large-scale infrastructures. READ MORE
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3. Dynamic Cloud Resource Management : Scheduling, Migration and Server Disaggregation
Abstract : A key aspect of cloud computing is the promise of infinite, scalable resources, and that cloud services should scale up and down on demand. This thesis investigates methods for dynamic resource allocation and management of services in cloud datacenters, introducing new approaches as well as improvements to established technologies. READ MORE
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4. Managing cloud resource scarcity
Abstract : According to the Infrastructure-as-a-Service conceptualization of cloud computing, Infrastructure Providers offer utility-like pay-as-you-go access to computing resources (e.g., data processing, networks, and storage) to Service Providers, who use those resources to host applications for the benefit of end users. READ MORE
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5. Application-aware resource management for datacenters
Abstract : High Performance Computing (HPC) and Cloud Computing datacenters are extensively used to steer and solve complex problems in science, engineering, and business, such as calculating correlations and making predictions. Already in a single datacenter server, there are thousands of hardware and software metrics – Key Performance Indicators (KPIs) – that individually and aggregated can give insight in the performance, robustness, and efficiency of the datacenter and the provisioned applications. READ MORE