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Making JavaScript Better By Making It Even Slower
"... Abstract—On mobile devices, such as smartphones and tablets, client-side JavaScript is a significant contributor to power consumption, and thus battery lifetime. We claim that this is partially due to JavaScript interpretation running faster than is necessary to maintain a satisfactory user experien ..."
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Abstract—On mobile devices, such as smartphones and tablets, client-side JavaScript is a significant contributor to power consumption, and thus battery lifetime. We claim that this is partially due to JavaScript interpretation running faster than is necessary to maintain a satisfactory user experience, and we propose that JavaScript implementations include a user-configurable throttle. To evaluate our claim we developed a web proxy system, named JSSlow, that reduces power consumption by transcoding client-side JavaScript and injecting “sleep ” invocations. This can be done safely, even given JavaScript’s single-threaded nature, through the use of continuation passing, and the proxy model requires neither server nor client-side changes. Using JSSlow we studied the 120 most popular sites and found that the technique could reduce power consumption by an average of 5 % on Android phones. We also considered buggy code (52 % reduction) and advertising (10 % reduction). To evaluate the system’s impact on the user experience, we conducted a user study consisting of interactive tasks the user carried out on. The perceived performance impact varies by user and site, with the variation being highest on the most interactive sites, such as games. This argues for making the throttle user-configurable in some cases.
Measurement and Analysis of Mobile Web Cache Performance
"... The Web browser is a killer app on mobile devices such as smartphones. However, the user experience of mobile Web browsing is undesirable because of the slow resource loading. To improve the performance of Web resource loading, caching has been adopted as a key mechanism. However, the existing passi ..."
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The Web browser is a killer app on mobile devices such as smartphones. However, the user experience of mobile Web browsing is undesirable because of the slow resource loading. To improve the performance of Web resource loading, caching has been adopted as a key mechanism. However, the existing passive measurement studies cannot comprehensively characterize the performance of mobile Web caching. For example, most of these studies mainly focus on client-side implementations but not server-side configurations, suffer from biased user behaviors, and fail to study “miscached ” resources. To address these issues, in this paper, we present a proactive approach for a comprehensive measurement study on mobile Web cache performance. The key idea of our approach is to proactively crawl resources from hundreds of websites periodically with a fine-grained time interval. Thus, we are able to uncover the resource update history and cache configurations at the server side, and analyze the cache performance in various time granularities. Based on our collected data, we build a new cache analysis model and study the upper bound of how high percentage of resources could potentially be cached and how effective the caching works in practice. We report detailed analysis results of different websites and various types of Web resources, and identify the problems caused by unsatisfactory cache performance. In particular, we identify two major problems – Redundant Transfer and Miscached Resource, which lead to unsatisfactory cache performance. We investigate three main root causes: Same Content, Heuristic Expiration, and Conservative Expiration Time, and discuss what mobile Web developers can do to mitigate those problems.
Co-operative Content Adaptation Framework Satisfying Consumer and Content Creator in Resource Constrained Browsing
"... Mobile Web is characterized by two salient features, (i) ubiquitous access to content and (ii) limited resources, like bandwidth and battery. Since most web pages are designed for the wired Internet, it is challenging to adapt the pages seamlessly to ensure a satisfactory mobile web experience. Cont ..."
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Mobile Web is characterized by two salient features, (i) ubiquitous access to content and (ii) limited resources, like bandwidth and battery. Since most web pages are designed for the wired Internet, it is challenging to adapt the pages seamlessly to ensure a satisfactory mobile web experience. Content heavy web pages lead to longer load time on mobile browsers. Pre-defined load order of items in a page does not adapt to mobile browsing habits, where user looks for different snippets of a page to load under different contexts. Web content adaptation for mobile web has mainly focused on the user to define her preferences for content. We propose a framework where content creator is additionally included in guiding the adaptation. Allowing content creator to specify importance of items in a page also helps in factoring her incentives by pushing revenue generating content. We present mechanisms to enable cooperative content adaptation. Preliminary results show the efficacy of cooperative content adaptation in resource constrained mobile browsing scenario.
What is Wrecking Your Data Plan? A Measurement Study of Mobile Web Overhead
"... Abstract—The growing popularity of smartphones and contin-uous user demand for a rich web experience has resulted in an exponential surge in cellular bandwidth requirements. Cellular providers have struggled to keep pace with the new requirements while users often face a monetary cost associated wit ..."
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Abstract—The growing popularity of smartphones and contin-uous user demand for a rich web experience has resulted in an exponential surge in cellular bandwidth requirements. Cellular providers have struggled to keep pace with the new requirements while users often face a monetary cost associated with the data downloaded to their device. While many modern websites have adapted to the new mobile habitat, they often take shortcuts to transition from their desktop to mobile versions, many times car-rying redundant content that is never utilized. Moreover, mobile users are effectively paying for certain undesirable content, such as advertisements, in the form of their bandwidth costs. In this paper, we study the composition and complexity of modern websites, from both a mobile and desktop perspective, to identify sources of wasted bandwidth. We developed a custom crawler-based framework to perform an in-depth analysis of the top 100,000 popular sites ranked by Alexa. Our results show that 23 % or more of the content size on an average website is unnecessary, unused or redundant. Our results serve as a motivation for developing optimized websites and enhancing the web infrastructure to better suit the mobile environment with emphasis on reducing bandwidth costs, while also improving performance and efficiency. I.
Energy-Efficient On-Demand Streaming in Mobile Cellular Networks
"... With the rapid development of wireless access technologies and mobile terminals (e.g. tablet, smartphone), end users are able to enjoy abundant applications with heavy workload on mobile platforms ..."
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With the rapid development of wireless access technologies and mobile terminals (e.g. tablet, smartphone), end users are able to enjoy abundant applications with heavy workload on mobile platforms
Powerslave: Analyzing the Energy Consumption of Mobile Antivirus Software
"... Abstract. Battery technology seems unable to keep up with the rapid evolution of smartphones and their applications, which continuously demand more and more energy. Modern smartphones, with their plethora of application scenarios and usage habits, are setting new challenges and constraints for malwa ..."
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Abstract. Battery technology seems unable to keep up with the rapid evolution of smartphones and their applications, which continuously demand more and more energy. Modern smartphones, with their plethora of application scenarios and usage habits, are setting new challenges and constraints for malware detection software. Among these challenges, preserving the battery life as much as possible is one of the most pressing. From the end users ’ perspective, a security solution, such as an antivirus (AV), that significantly impacts the battery’s life is unacceptable. Thus, the quality and degree of adoption of malware-detection products is also influenced by their energy demands. Motivated by the above rationale, we perform the first fine-grained mea-surement that analyzes, at a low level, the energy efficiency of modern, commercial, popular AVs. We explore the relations between various as-pects of popular AVs, when handling malicious and benign applications, and the resulting energy consumption. Even though we focus on energy consumption, we also explore other dimensions such as the discrepancies between scanning modes, the impact of file size and scan duration. We then translate our findings into a set of design guidelines for reducing the energy footprint of modern AVs for mobile devices. 1
Demystifying the Imperfect Client-Side Cache Performance of Mobile Web Browsing
"... Abstract—The Web browser is one of the most significant applications on mobile devices such as smartphones. However, the user experience of mobile Web browsing is undesirable because of the slow resource loading. To improve the performance of Web resource loading, client-side cache has been adopted ..."
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Abstract—The Web browser is one of the most significant applications on mobile devices such as smartphones. However, the user experience of mobile Web browsing is undesirable because of the slow resource loading. To improve the performance of Web resource loading, client-side cache has been adopted as a key mechanism. However, the existing passive measurement studies cannot comprehensively characterize the “client-side ” cache performance of mobile Web browsing. For example, most of these studies mainly focus on client-side implementations but not server-side configurations, suffer from biased user behaviors, and fail to study “miscached” resources. To address these issues, in this article, we present a proactive approach to making a comprehensive measurement study on client-side cache performance. The key idea of our approach is to proactively crawl resources from hundreds of websites periodically with a fine-grained time interval. Thus, we are able to uncover the resource update history and cache configurations at the server side, and analyze the cache performance in various time granularities. Based on our collected data, we build a new cache analysis model and study the upper bound of how high percentage of resources could potentially be cached and how effectively the caching works in practice. We report detailed analysis results of different websites and various types of Web resources, and identify the problems caused by unsatisfactory cache performance. In particular, we identify two major problems- Redundant Transfer and Miscached Resource, which lead to unsatisfactory cache performance. We investigate three main root causes: Same Content, Heuristic Expiration, and Conservative Expiration Time, and discuss what mobile Web developers can do to mitigate those problems.
Just-in-time Acceleration of JavaScript
"... JavaScript has seen tremendous growth in popularity driven by increasingly interactive web sites and sophisticated web interfaces. However, the performance of JavaScript continues to be a hurdle in using it for tasks that are computationally intensive, such as gaming, simulations, and visualization. ..."
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JavaScript has seen tremendous growth in popularity driven by increasingly interactive web sites and sophisticated web interfaces. However, the performance of JavaScript continues to be a hurdle in using it for tasks that are computationally intensive, such as gaming, simulations, and visualization. JavaScript has also been slow to exploit the available parallelism on modern computers. Specifically, it is not currently easy to exploit GPG-PUs within JavaScript. A part of the reason is that the low-level interface demanded for GPGPU programming is often not approachable by JavaScript programmers. In this paper, we present a novel approach that provides a mechanism to accelerate portions of JavaScript programs without requiring the programmers to learn new syntax or low-level APIs. We achieve that through an embedded DSL used to specify GPGPU computations. We have designed a JavaScript library, and an accompanying Firefox extension, that work together to compile the embedded DSL just-in-time using the LLVM backend for generating PTX. The compiled code is cached to minimize the compilation overhead. Our evaluation of the system using a micro-benchmark, two applications kernels, and an application benchmark demonstrates that our approach imposes minimal performance overhead, while providing an easy GPGPU programming interface to JavaScript programmers. 1
empathic systemsMaking JavaScript Better By Making It Even Slower
, 2013
"... On mobile devices, such as smartphones and tablets, client-side JavaScript is a significant contributor to power consumption, and thus battery lifetime. We claim that this is partially due to JavaScript interpretation running faster than is necessary to maintain a satisfactory user experience, and w ..."
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On mobile devices, such as smartphones and tablets, client-side JavaScript is a significant contributor to power consumption, and thus battery lifetime. We claim that this is partially due to JavaScript interpretation running faster than is necessary to maintain a satisfactory user experience, and we propose that JavaScript implementations include a user-configurable throttle. To evaluate our claim we developed a web proxy system, named JSSlow, that reduces power consumption by transcoding client-side JavaScript and injecting “sleep ” invocations. This can be done safely, even given JavaScript’s single threaded nature, through the use of continuation passing, and the proxy model requires neither server nor client-side changes. Using JSSlow we studied the 120 most popular sites and found that the technique could reduce power consumption by an average of 6 % on Android phones. We also considered buggy code (52 % reduction) and advertising (10 % reduction). To evaluate the system’s impact on the user experience, we conducted a user study consisting of interactive tasks the user carried out on. The perceived performance impact varies by user and site, with the variation being highest on the most interactive sites, such as games. This argues for making the throttle user-configurable in some cases.
IEEE TRANSACTIONS ON MOBILE COMPUTING 1 Utilize Signal Traces from Others? A Crowdsourcing Perspective of Energy Saving in Cellular Data Communication
"... Abstract—With the tremendous growth in wireless network deployment and increasing use of mobile devices, e.g., smartphones and tablets, improving energy efficiency in such devices, especially with communication driven workloads, is critical to providing a satisfactory user experience. Studies show t ..."
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Abstract—With the tremendous growth in wireless network deployment and increasing use of mobile devices, e.g., smartphones and tablets, improving energy efficiency in such devices, especially with communication driven workloads, is critical to providing a satisfactory user experience. Studies show that signal strength plays an important role on energy consumption of cellular data communications. While energy consumption can be minimized by accurately predicting signal strengths and reacting to it in real-time, the dynamic nature of wireless environments makes signal strengths highly unpredictable. In this paper, after analyzing in detail the signal strength variation and its impact on energy consumption, we propose to use crowdsourcing approach to optimize mobile devices ’ energy efficiency by utilizing signal strength traces reported/shared by other users/devices in cellular networks. Via a comprehensive measurement study, we observe that signal strength traces collected from different devices are pseudo-identical, and they even exhibit similar threshold-based behaviors in the relationship between signal strength and device power consumption. Based on our observations, we propose a predictive scheduling algorithm that: (i) selects the right set of signal strength traces based on its location, (ii) applies a filter to smooth out signal strengths and hide abrupt changes, (iii) digitizes the signal strength to “good " and “bad " areas, and (iv) schedules transmissions based on power-throughput characteristics to optimize the transmission energy efficiency. To demonstrate the efficacy of the proposed algorithms, we prototype the crowdsourcing-based predicative scheduling algorithm on Android-based smartphones. Our experiment results from real-life driving tests demonstrate that, by leveraging others ’ signal traces, mobile devices can save energy up to 35 % compared to the
