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Cloud Computing has started to become a viable option for computing centers and mobile consumers seeking to reduce cost overhead, power consumption, and increase software services available within their platform. For instance distributed memory constrained mobile devices can expand their ability to share real time data by utilizing virtual memory located within the cloud. Cloud memory services can be configured to restrict read and write access to the shared memory pool on a partner by partner basis. Utilization of such resources in turn reduces hardware requirements on mobile devices while lessening power consumption for each physical resource. Within the Cloud Computing paradigm, computing resources are provisioned to consumers on demand and guaranteed through service level agreements. Although the idea of a computing utility is not new, its realization has come to pass as researchers and corporate companies embark on a journey of implementing highly scalable cloud environments. As new solutions and architectures are proposed, additional use cases and consumer concerns have been revealed. These issues range from consumer security, adequate service level agreements and vendor interoperability, to cloud technology standardizations. Further, the current state of the art does not adequately address these needs for mobile consumers, where services need to be guaranteed even as consumers dynamically change locations. Due to the rapid adoption of virtualization stacks and the dramatic increase of mobile computing devices, cloud providers must be able to handle logical and physical mobility of consumers. As consumers move throughout geographical regions, there exists the probability that a consumer’s new locale may hinder a producer’s ability to uphold service level agreements. This inability is due to the fact that a producer may not have physical resources located relatively close to a mobile consumer’s new locale. As a consequence, producers must either continue to provide degraded resource consumption or migrate workloads to third party producers in order to ensure service level agreements are maintained. The goal of this report is to research existing architectures that provide the ability to adequately uphold service level agreements as mobile consumers move from locale to locale. Further we propose an architecture that can be implemented along with existing solutions in order to ensure consumers receive adequate service levels regardless of locality. We believe this architecture will lead to increased cloud interoperability and decreased consumer to producer platform coupling. / text

Smartphones have become crucial enablers for users to exploit online services such as learning, leisure, communicating, and socializing. The user-perceived quality of applications and services is an important factor to consider, in order to achieve lean resource management, to prevent user churn and revenue depletion of service or network providers. This is often studied within the scope of Quality of Experience (QoE), which has attracted researchers both in academia and industry. The objective of this thesis is to study the most important factors influencing QoE on smartphones and synthesize solutions for intervention. The temporal impairments during a real-time energy-hungry video streaming are studied. The aim is to quantify the influence of temporal impairments on the user-perceived video QoE at the network and application level together with energy measurements, and also to propose solutions to reduce smartphone energy consumption without degrading the user’s QoE on the smartphone for both user-interactive, e.g., video, and non-interactive cases. QoE measurements on smartphones are performed throughout in-the-wild user studies. A set of quantitative Quality of Experience (QoE) assessment tools are implemented and deployed for automatic data logging at the network- and application-level. Online momentary survey, Experience Sampling Method (ESM) software, and Day Reconstruction Method (DRM) along weekly face-to-face user interviews are employed. The subjective QoE is obtained through qualitative feedback including Mean Opinion Score (MOS) as well as in-situ indications of poor experiences by users. Additionally, energy measurements on smartphones are conducted in controlled-lab environment with the Monsoon device. The QoE of smartphone applications and services perceived by users depends on many factors including anomalies in the network, application, and also the energy consumption. At the network-level, high packet delay variation causes long video freezes that eventually impact negatively the end-user perceived quality. The freezes can be quantified as large time gaps in-between the displayed pictures during a video stream at the application-level. We show that the inter-picture time in cellular-based video stream can be represented via two-state exponential ON/OFF models. We show models representing the non-linear relationship between the QoE and the mean inter-picture time. It is shown that energy measurements help to reveal the temporal impairments in video stream enabling energy consumption as a QoE indicator. Next, energy waste and saving during temporal impairments are identified. Additionally, other video streaming use cases, e.g., “download first and watch later”, are studied and appropriate energy-saving download scheduling mechanisms are recommended. The possibility for decreasing energy consumption when the smartphone screen is OFF, while maintaining QoE, is revealed. We first show exponential models to represent user’s interaction with smartphone, then propose a NyxEnergySaver software, to control the cellular network interface in a personalized manner to save smartphone energy. According to our findings, more than 30% smartphone energy can be saved without impacting the user-perceived QoE.

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