Balancing Interactive Performance and Budgeted Resources in Mobile Computing.

Balancing Interactive Performance and Budgeted Resources in Mobile Computing;Mobile Computing;Interactive Performance;Budgeted Resources;Computer Science;Engineering;Computer Science and Engineering

Higgins, Brett DouglasMao, Z. Morley ;

University of Michigan

关键词: Balancing Interactive Performance and Budgeted Resources in Mobile Computing;    Mobile Computing;    Interactive Performance;    Budgeted Resources;    Computer Science;    Engineering;    Computer Science and Engineering;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/108956/brettdh_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

In this dissertation, we explore the various limited resources involved in mobile applications --- battery energy, cellular data usage, and, critically, user attention --- and we devise principled methods for managing the tradeoffs involved in creating a good user experience. Building quality mobile applications requires developers to understand complex interactions between network usage, performance, and resource consumption.Because of thisdifficulty, developers commonly choose simple but suboptimal approaches that strictly prioritize performance or resource conservation.These extremes are symptoms of a lack of system-provided abstractions for managing the complexity inherent in managing performance/resource tradeoffs. By providing abstractions that help applications manage these tradeoffs, mobile systems can significantly improve user-visible performance without exhausting resource budgets. This dissertation explores three such abstractions in detail. We first present IntentionalNetworking, a system that provides synchronization primitives and intelligent scheduling for multi-network traffic. Next, we present Informed Mobile Prefetching, a system that helps applications decide when to prefetch data and how aggressively to spend limited battery energy and cellular data resources toward that end. Finally, we present Meatballs, a library that helps applications consider the cloudy nature of predictions when making decisions, selectively employing redundancy to mitigate uncertainty and provide morereliable performance. Overall, experiments show that these abstractions can significantly reduce interactive delay without overspending the available energy and data resources.