Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services最新文献_第2页

I-Pic: A Platform for Privacy-Compliant Image Capture I-Pic:一个符合隐私的图像捕获平台

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/2906388.2906412

Paarijaat Aditya, Rijurekha Sen, P. Druschel, Seong Joon Oh, Rodrigo Benenson, Mario Fritz, B. Schiele, Bobby Bhattacharjee, Tongyu Wu

{"title":"I-Pic: A Platform for Privacy-Compliant Image Capture","authors":"Paarijaat Aditya, Rijurekha Sen, P. Druschel, Seong Joon Oh, Rodrigo Benenson, Mario Fritz, B. Schiele, Bobby Bhattacharjee, Tongyu Wu","doi":"10.1145/2906388.2906412","DOIUrl":"https://doi.org/10.1145/2906388.2906412","url":null,"abstract":"The ubiquity of portable mobile devices equipped with built-in cameras have led to a transformation in how and when digital images are captured, shared, and archived. Photographs and videos from social gatherings, public events, and even crime scenes are commonplace online. While the spontaneity afforded by these devices have led to new personal and creative outlets, privacy concerns of bystanders (and indeed, in some cases, unwilling subjects) have remained largely unaddressed. We present I-Pic, a trusted software platform that integrates digital capture with user-defined privacy. In I-Pic, users choose alevel of privacy (e.g., image capture allowed or not) based upon social context (e.g., out in public vs. with friends vs. at workplace). Privacy choices of nearby users are advertised via short-range radio, and I-Pic-compliant capture platforms generate edited media to conform to privacy choices of image subjects. I-Pic uses secure multiparty computation to ensure that users' visual features and privacy choices are not revealed publicly, regardless of whether they are the subjects of an image capture. Just as importantly, I-Pic preserves the ease-of-use and spontaneous nature of capture and sharing between trusted users. Our evaluation of I-Pic shows that a practical, energy-efficient system that conforms to the privacy choices of many users within a scene can be built and deployed using current hardware.","PeriodicalId":413230,"journal":{"name":"Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130879595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 106

Privacy Capsules: Preventing Information Leaks by Mobile Apps 隐私胶囊:防止移动应用程序泄露信息

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/2906388.2906409

Raul Herbster, Scott DellaTorre, P. Druschel, Bobby Bhattacharjee

引用次数: 20

TaskFolder: Dynamic and Fine-Grained Workload Consolidation for Mobile Devices TaskFolder:移动设备的动态和细粒度工作负载整合

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/2906388.2906397

Yuyang Du, Sebastien Haezebrouck, Jin Cui, R. Muralidhar, Harinarayanan Seshadri, Vishwesh Rudramuni, Nicole Chalhoub, Y. Chua, Richard Quinzio

{"title":"TaskFolder: Dynamic and Fine-Grained Workload Consolidation for Mobile Devices","authors":"Yuyang Du, Sebastien Haezebrouck, Jin Cui, R. Muralidhar, Harinarayanan Seshadri, Vishwesh Rudramuni, Nicole Chalhoub, Y. Chua, Richard Quinzio","doi":"10.1145/2906388.2906397","DOIUrl":"https://doi.org/10.1145/2906388.2906397","url":null,"abstract":"Despite the resource-constrained environment associated with mobile devices, the Android task scheduler tries to spread the workload equally among all CPU cores. While this is a sensible use of resources in desktop or server environments, it is inefficient for mobile devices, because they usually have lower computing demand and require single-user-perceptible performance guaran-tees. As a result, spreading tasks to all cores does not improve per-formance, increases energy consumption, and can cause perfor-mance issues when multiple mobile virtual machines attempt to engage as many cores as possible. To address this problem, we propose TaskFolder, a multi-core management scheme implemented on top of the task scheduler. TaskFolder attempts to compute the minimum number of cores required to perform the current workload without sacrificing per-formance, and schedules tasks to only that minimal number of cores. This number is called the Core Concurrency and is calculated based on past task dynamics. Experimental results of a case study show that TaskFolder saves an average of 19% and up to 48% of CPU power over a set of mobile applications on the latest Intel mobile platform.","PeriodicalId":413230,"journal":{"name":"Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125518135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Mobility Modeling and Prediction in Bike-Sharing Systems 共享单车系统的移动性建模与预测

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/2906388.2906408

Zidong Yang, Ji Hu, Yuanchao Shu, Peng Cheng, Jiming Chen, T. Moscibroda

{"title":"Mobility Modeling and Prediction in Bike-Sharing Systems","authors":"Zidong Yang, Ji Hu, Yuanchao Shu, Peng Cheng, Jiming Chen, T. Moscibroda","doi":"10.1145/2906388.2906408","DOIUrl":"https://doi.org/10.1145/2906388.2906408","url":null,"abstract":"As an innovative mobility strategy, public bike-sharing has grown dramatically worldwide. Though providing convenient, low-cost and environmental-friendly transportation, the unique features of bike-sharing systems give rise to problems to both users and operators. The primary issue among these problems is the uneven distribution of bicycles caused by the ever-changing usage and (available) supply. This bicycle imbalance issue necessitates efficient bike re-balancing strategies, which depends highly on bicycle mobility modeling and prediction. In this paper, for the first time, we propose a spatio-temporal bicycle mobility model based on historical bike-sharing data, and devise a traffic prediction mechanism on a per-station basis with sub-hour granularity. We extensively evaluated the performance of our design through a one-year dataset from the world's largest public bike-sharing system (BSS) with more than 2800 stations and over 103 million check in/out records. Evaluation results show an 85 percentile relative error of 0.6 for both check in and check out prediction. We believe this new mobility modeling and prediction approach can advance the bike re-balancing algorithm design and pave the way for the rapid deployment and adoption of bike-sharing systems across the globe.","PeriodicalId":413230,"journal":{"name":"Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130361267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 175

Beetle: Flexible Communication for Bluetooth Low Energy 甲虫:低功耗蓝牙灵活通信

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/2906388.2906414

A. Levy, James Hong, Laurynas Riliskis, P. Levis, Keith Winstein

引用次数: 33

Session details: Session I: Smart Environments 会议详情:会议一:智能环境

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/3257196

Eduardo Cuervo

引用次数: 0

LiveLabs: Building In-Situ Mobile Sensing & Behavioural Experimentation TestBeds LiveLabs:建立原位移动传感和行为实验试验台

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/2906388.2906400

Kasthuri Jayarajah, R. Balan, Meera Radhakrishnan, Archan Misra, Youngki Lee

引用次数: 24

DefDroid: Towards a More Defensive Mobile OS Against Disruptive App Behavior DefDroid:面向更具防御性的手机操作系统，对抗破坏性应用行为

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/2906388.2906419

Peng Huang, Tianyin Xu, Xinxin Jin, Yuanyuan Zhou

{"title":"DefDroid: Towards a More Defensive Mobile OS Against Disruptive App Behavior","authors":"Peng Huang, Tianyin Xu, Xinxin Jin, Yuanyuan Zhou","doi":"10.1145/2906388.2906419","DOIUrl":"https://doi.org/10.1145/2906388.2906419","url":null,"abstract":"The mobile app market is enjoying an explosive growth. Many people, including teenagers, set about developing mobile apps. Unfortunately, due to developers' inexperience and the unique mobile programming paradigms, a growing number of immature apps are released to users. Despite having useful functionalities, these apps exhibit disruptive behaviors that are inconsiderate to the mobile system as a whole, e.g.,, retrying network connections too aggressively, waking up the device too frequently, or holding resources for unnecessarily long. These behaviors adversely affect other apps running on the same device and frustrate users with battery drain, excessive cellular data consumption, storage overuse, etc. In this paper, we investigate Disruptive App Behavior (DAB) with a study on 287 real-world DAB issues. Guided by the study, we present DefDroid, a mobile OS designed to protect users from the negative impact of DAB at runtime. DefDroid monitors important app activities and tries to adjust app behaviors using fine-grained actions (e.g., enforce back-off to continuous retries, decrease aggressive timer frequency) without breaking app main functionality. Our experiments show that DefDroid effectively curbs 125 real-world DAB cases with small overhead and marginal impact to the usability of both the misbehaving apps and normal apps. During a small-scale user trial, DefDroid also found 6 new DAB issues. We further deployed DefDroid to 185 real users through the PhoneLab testbed for 43 days and found DAB issues from at least 57 apps.","PeriodicalId":413230,"journal":{"name":"Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121650353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 21

uLink: Enabling User-Defined Deep Linking to App Content uLink:启用自定义深度链接到应用程序内容

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/2906388.2906416

Tanzirul Azim, Oriana Riva, Suman Nath

{"title":"uLink: Enabling User-Defined Deep Linking to App Content","authors":"Tanzirul Azim, Oriana Riva, Suman Nath","doi":"10.1145/2906388.2906416","DOIUrl":"https://doi.org/10.1145/2906388.2906416","url":null,"abstract":"Web deep links are instrumental to many fundamental user experiences such as navigating to one web page from another, bookmarking a page, or sharing it with others. Such experiences are not possible with individual pages inside mobile apps, since historically mobile apps did not have links equivalent to web deep links. Mobile deep links, introduced in recent years, still lack many important properties of web deep links. Unlike web links, mobile deep links need significant developer effort, cover a small number of predefined pages, and are defined statically to navigate to a page for a given link, but not to dynamically generate a link for a given page. We propose uLink, a novel deep linking mechanism that addresses these problems. uLink is implemented as an application library, which transparently tracks data- and UI-event-dependencies of app pages, and encodes the information in links to the pages; when a link is invoked, the information is utilized to recreate the target page quickly and accurately. uLink also employs techniques, based on static and dynamic analysis of the app, that can provide feedback to users about whether a link may break in the future due to, e.g., modifications of external resources such as a file the link depends on. We have implemented uLink on Android. Our evaluation with 34 (of 1000 most downloaded) Android apps shows that compared to existing mobile deep links, uLink requires minimal developer effort, achieves significantly higher coverage, and can provide accurate user feedback on a broken link.","PeriodicalId":413230,"journal":{"name":"Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114678721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 31

MCDNN: An Approximation-Based Execution Framework for Deep Stream Processing Under Resource Constraints MCDNN:资源约束下基于近似的深度流处理执行框架

Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Pub Date : 2016-06-20 DOI: 10.1145/2906388.2906396

Seungyeop Han, Haichen Shen, Matthai Philipose, S. Agarwal, A. Wolman, A. Krishnamurthy

{"title":"MCDNN: An Approximation-Based Execution Framework for Deep Stream Processing Under Resource Constraints","authors":"Seungyeop Han, Haichen Shen, Matthai Philipose, S. Agarwal, A. Wolman, A. Krishnamurthy","doi":"10.1145/2906388.2906396","DOIUrl":"https://doi.org/10.1145/2906388.2906396","url":null,"abstract":"We consider applying computer vision to video on cloud-backed mobile devices using Deep Neural Networks (DNNs). The computational demands of DNNs are high enough that, without careful resource management, such applications strain device battery, wireless data, and cloud cost budgets. We pose the corresponding resource management problem, which we call Approximate Model Scheduling, as one of serving a stream of heterogeneous (i.e., solving multiple classification problems) requests under resource constraints. We present the design and implementation of an optimizing compiler and runtime scheduler to address this problem. Going beyond traditional resource allocators, we allow each request to be served approximately, by systematically trading off DNN classification accuracy for resource use, and remotely, by reasoning about on-device/cloud execution trade-offs. To inform the resource allocator, we characterize how several common DNNs, when subjected to state-of-the art optimizations, trade off accuracy for resource use such as memory, computation, and energy. The heterogeneous streaming setting is a novel one for DNN execution, and we introduce two new and powerful DNN optimizations that exploit it. Using the challenging continuous mobile vision domain as a case study, we show that our techniques yield significant reductions in resource usage and perform effectively over a broad range of operating conditions.","PeriodicalId":413230,"journal":{"name":"Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123293233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 366