Bridging the gap between mobile CPU design and user satisfaction via crowdsourcing

This report aims to provide an understanding of how the mobile CPU designs have evolved and its influence on end-user satisfaction. To that end, a quantitative performance analysis is conducted across ten cutting-edge mobile CPU designs studied within top-selling off-the-shelf smartphones released over the past seven years. This analysis is then used to guide a large-scale user study spanning over 25,000 participants via crowdsourcing on the Amazon Mechanical Turk service. The user study asks participants to assess the responsiveness of interactive application use cases for a set of current-generation applications (e.g. Angry Birds and FaceBook) and next-generation applications (i.e. face recognition and augmented reality) relative to the performance capabilities of the devices studied. This framework allows us to quantitatively link how the mobile CPU designs studied impacted end-user satisfaction. The study results indicate that mobile CPU designs have exhibited signifiant performance improvements through aggressive core scaling techniques prevalent in desktop CPUs. Just as was observed in desktop CPU design, these same techniques have lead to excessive mobile CPU power consumption. However, from an end-user perspective this power consumption was not without success. Mobile CPUs have evolved to provide satisfactory experiences for the studied current- generation applications. The reason is that many of these applications rely heavily on single-threaded performance. Other, more recent applications, actually multi-thread user-critical parts of the applications, which also demonstrates that multi- core mobile CPUs are an important design consideration – contrary to conventional wisdom. However, looking ahead, the same mobile CPUs where not able to provide satisfactory experiences for many of the next-generation applications studied, questioning the sustainability of these power-hungry design techniques in future mobile CPU designs.Electrical and Computer Engineerin

Energy-Saving Strategies for Mobile Web Apps and their Measurement: Results from a Decade of Research (Preprint)

In 2022, over half of the web traffic was accessed through mobile devices. By reducing the energy consumption of mobile web apps, we can not only extend the battery life of our devices, but also make a significant contribution to energy conservation efforts. For example, if we could save only 5% of the energy used by web apps, we estimate that it would be enough to shut down one of the nuclear reactors in Fukushima. This paper presents a comprehensive overview of energy-saving experiments and related approaches for mobile web apps, relevant for researchers and practitioners. To achieve this objective, we conducted a systematic literature review and identified 44 primary studies for inclusion. Through the mapping and analysis of scientific papers, this work contributes: (1) an overview of the energy-draining aspects of mobile web apps, (2) a comprehensive description of the methodology used for the energy-saving experiments, and (3) a categorization and synthesis of various energy-saving approaches.Comment: Preprint for 2023 IEEE/ACM 10th International Conference on Mobile Software Engineering and Systems (MOBILESoft): Energy-Saving Strategies for Mobile Web Apps and their Measurement: Results from a Decade of Researc

A Survey of Performance Optimization for Mobile Applications

Nowadays there is a mobile application for almost everything a user may think of, ranging from paying bills and gathering information to playing games and watching movies. In order to ensure user satisfaction and success of applications, it is important to provide high performant applications. This is particularly important for resource constraint systems such as mobile devices. Thereby, non-functional performance characteristics, such as energy and memory consumption, play an important role for user satisfaction. This paper provides a comprehensive survey of non-functional performance optimization for Android applications. We collected 155 unique publications, published between 2008 and 2020, that focus on the optimization of non-functional performance of mobile applications. We target our search at four performance characteristics, in particular: responsiveness, launch time, memory and energy consumption. For each performance characteristic, we categorize optimization approaches based on the method used in the corresponding publications. Furthermore, we identify research gaps in the literature for future work

Providing efficient services for smartphone applications

Mobile applications are becoming an indispensable part of people\u27s lives, as they allow access to a broad range of services when users are on the go. We present our efforts towards enabling efficient mobile applications in smartphones. Our goal is to improve efficiency of the underlying services, which provide essential functionality to smartphone applications. In particular, we are interested in three fundamental services in smartphones: wireless communication service, power management service, and location reporting service.;For the wireless communication service, we focus on improving spectrum utilization efficiency for cognitive radio communications. We propose ETCH, a set of channel hopping based MAC layer protocols for communication rendezvous in cognitive radio communications. ETCH can fully utilize spectrum diversity in communication rendezvous by allowing all the rendezvous channels to be utilized at the same time.;For the power management service, we improve its efficiency from three different angles. The first angle is to reduce energy consumption of WiFi communications. We propose HoWiES, a system-for WiFi energy saving by utilizing low-power ZigBee radio. The second angle is to reduce energy consumption of web based smartphone applications. We propose CacheKeeper, which is a system-wide web caching service to eliminate unnecessary energy consumption caused by imperfect web caching in many smartphone applications. The third angle is from the perspective of smartphone CPUs. We found that existing CPU power models are ill-suited for modern multicore smartphone CPUs. We present a new approach of CPU power modeling for smartphones. This approach takes CPU idle power states into consideration, and can significantly improve power estimation accuracy and stability for multicore smartphones.;For the location reporting service, we aim to design an efficient location proof solution for mobile location based applications. We propose VProof, a lightweight and privacy-preserving location proof scheme that allows users to construct location proofs by simply extracting unforgeable information from the received packets