DOCSLIB.ORG

Building Blocks for Tomorrow's Mobile App Store

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Building Blocks for Tomorrow's Mobile App Store Building Blocks for Tomorrow’s Mobile App Store by Justin G. Manweiler Department of Computer Science Duke University Date: Approved: Romit Roy Choudhury, Supervisor Jeffrey S. Chase Landon P. Cox Victor Bahl Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science in the Graduate School of Duke University 2012 Abstract (0984) Building Blocks for Tomorrow’s Mobile App Store by Justin G. Manweiler Department of Computer Science Duke University Date: Approved: Romit Roy Choudhury, Supervisor Jeffrey S. Chase Landon P. Cox Victor Bahl An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science in the Graduate School of Duke University 2012 Copyright c 2012 by Justin G. Manweiler All rights reserved Abstract In our homes and in the enterprise, in our leisure and in our professions, mobile computing is no longer merely “exciting;” it is becoming an essential, ubiquitous tool of the modern world. New and innovative mobile applications continue to inform, entertain, and surprise users. But, to make the daily use of mobile technologies more gratifying and worthwhile, we must move forward with new levels of sophistication. The Mobile App Stores of the future must be built on stronger foundations. This dissertation considers a broad view of the challenges and intuitions behind a diverse selection of such new primitives. Some of these primitives will mitigate exist- ing and fundamental challenges of mobile computing, especially relating to wireless communication. Others will take an application-driven approach, being designed to serve a novel purpose, and be adapted to the unique and varied challenges from their disparate domains. However, all are related through a unifying goal, to provide a seamless, enjoyable, and productive mobile experience. This dissertation takes view that by bringing together nontrivial enhancements across a selection of disparate-but- interrelated domains, the impact is synergistically stronger than the sum of each in isolation. Through their collective impact, these new “building blocks” can help lay a foundation to upgrade mobile technology beyond the expectations of early-adopters, and into seamless integration with all of our lives. iv For Jane. v Contents Abstract iv List of Tables xv List of Figures xvi List of Abbreviations and Symbols xxviii Acknowledgements xxxi 1 Introduction 1 2 TransmissionReorderinginWirelessNetworks 14 2.1 Introduction................................ 14 2.2 VerifyingMIM .............................. 18 2.3 MIM:OptimalityAnalysis . 20 2.3.1 OptimalSchedulewithIntegerProgram . 20 2.3.2 Results............................... 24 2.4 Shuffle:SystemDesign .......................... 24 2.4.1 ProtocolDesign.......................... 25 2.4.2 DesignDetails........................... 33 2.4.3 RateControl ........................... 33 2.4.4 UploadTraffic........................... 34 2.4.5 ControllerPlacement . 35 2.5 Shuffle:Implementation . 35 vi 2.5.1 TestbedPlatform . 35 2.5.2 TimeSynchronizationandStagger . 36 2.5.3 CoordinationandDispatching . 37 2.6 Evaluation................................. 39 2.6.1 Throughputwith2AccessPoints . 40 2.6.2 Throughputwith3AccessPoints . 41 2.6.3 Fairness .............................. 41 2.6.4 PerformanceonLargerTopologies. 42 2.6.5 CompleteShufflewithRateControl. 42 2.6.6 SimulationResults . 46 2.6.7 ImpactofAPdensity. 46 2.6.8 ImpactofFading ......................... 47 2.7 LimitationsandDiscussion. 48 2.7.1 ExternalNetworkInterference . 48 2.7.2 Latency .............................. 48 2.7.3 ClientMobility .......................... 49 2.7.4 TransportLayerInteractions. 49 2.7.5 Compatibility ........................... 49 2.7.6 Small-scaleTestbed. 49 2.8 RelatedWork ............................... 50 2.8.1 CaptureandMIM ........................ 50 2.8.2 SpatialReuse ........................... 50 2.8.3 EnterpriseWirelessLANsandScheduling . 50 2.8.4 Characterizing and Measuring Interference . ... 51 2.9 Conclusion................................. 52 vii 3 MonitoringtheHealthofHomeWirelessNetworks 53 3.1 Introduction................................ 54 3.2 RxIPArchitecture ............................ 60 3.3 HiddenTerminalDiagnosis. 62 3.3.1 EnsuringHiddenTerminalsaretheCause . 62 3.3.2 IsolatingtheHiddenTerminal . 63 3.4 RecoverybyCoordination . 66 3.4.1 CopingwithInternetLatencies . 66 3.4.2 MultiplePartnerships. 67 3.4.3 ProvablePropertiesofCoordination. 68 3.5 AdditionalConsiderations . 70 3.5.1 CopingwithTokenLoss . 70 3.5.2 AddressTranslation . 71 3.5.3 UploadTraffic........................... 71 3.5.4 IncrementalDeployability . 71 3.6 Evaluation................................. 72 3.6.1 TestbedPlatform . 72 3.6.2 Methodology ........................... 73 3.6.3 HiddenTerminalDiagnosisandRecovery . 73 3.6.4 Microbenchmarks . 77 3.6.5 Scalability of Partnership-based TDMA. 79 3.7 RelatedWork ............................... 82 3.7.1 EnterpriseNetworkManagement . 82 3.7.2 HiddenTerminalMitigation . 82 3.7.3 NetworkMeasurement . 82 viii 3.7.4 RelatedTechniques . 83 3.8 Conclusion................................. 83 4 WiFiEnergyManagementviaTrafficIsolation 84 4.1 Introduction................................ 85 4.2 BackgroundandMeasurements . 89 4.2.1 ChoiceofDevice ......................... 89 4.2.2 MeasurementSet-up . 89 4.2.3 Terminology............................ 90 4.2.4 PSMEnergyProfiling . 91 4.2.5 ImpactofNetworkContentiononEnergy. 93 4.3 SleepWellDesign ............................. 96 4.3.1 BasicSleepWell .......................... 96 4.3.2 CopingwithTrafficDynamics . 101 4.3.3 SeamlessBeaconRe-adjustment . 103 4.3.4 MultipleClientsperAP . 104 4.3.5 Compatibility with Adaptive-PSM Clients . 105 4.4 Evaluation................................. 105 4.4.1 Implementation . 105 4.4.2 Methodology ........................... 106 4.4.3 PerformanceResults . 106 4.5 LimitationsandDiscussion. 117 4.5.1 ImpactofHiddenTerminals . 117 4.5.2 IncrementalDeployability . 119 4.5.3 InteractiveTraffic. 120 4.5.4 TSFAdjustment ......................... 120 ix 4.6 RelatedWork ............................... 120 4.6.1 WiFiPSMsleepoptimization . 120 4.6.2 WiFiDutyCycling ........................ 121 4.6.3 SensornetworkTDMA . 121 4.7 Conclusion................................. 122 5 A Matchmaking System for Multiplayer Mobile Games 123 5.1 Introduction................................ 124 5.2 MotivationandPriorWork . 126 5.2.1 LatencyinMultiplayerGames . 126 5.2.2 MatchmakinginOnlineGames . 127 5.2.3 P2PGamesOverCellularNetworks. 129 5.2.4 CellularNetworkPerformance . 130 5.2.5 Grouping ............................. 131 5.3 EstimatingCellularLatency . 132 5.3.1 Predicting Future Latency Based on Current Latency . 134 5.3.2 Using One Phone to Predict the Future Latency of a Different Phone ............................... 139 5.3.3 PredictingtheLatencyBetweenPhones . 145 5.4 Switchboard................................ 147 5.4.1 ArchitectureofSwitchboard . 147 5.4.2 ClientAPIforLobbyBrowser . 148 5.4.3 LatencyEstimator . 150 5.4.4 GroupingAgent.......................... 152 5.4.5 GroupingAlgorithm . 153 5.5 Evaluation................................. 155 5.5.1 Implementation . 155 x 5.5.2 EvaluationofGrouping. 156 5.5.3 End-to-endEvaluation . 161 5.5.4 SummaryofEvaluationResults . 165 5.6 Conclusion................................. 166 6 An Object Positioning System using Smartphones 168 6.1 Introduction................................ 169 6.2 MotivationandOverview. 172 6.2.1 ApplicationsbeyondTagging . 172 6.2.2 SystemOverview . 173 6.3 PrimitivesforObjectLocalization . 175 6.4 OPS:SystemDesign ........................... 181 6.4.1 ExtractingaVisualModel . 181 6.4.2 Questions ............................. 185 6.4.3 Point Cloud toLocation: Failed Attempts . 186 6.4.4 TheConvergedDesignofOPS. 188 6.5 Discussion ................................. 192 6.5.1 ExtendingtheLocationModelto3D . 192 6.5.2 AlternativesforCapturingUserIntent . 193 6.6 Evaluation................................. 194 6.6.1 Implementation . 194 6.6.2 AccuracyofObjectLocalization. 196 6.7 RoomforImprovement. 200 6.7.1 Live Feedback to Improve Photograph Quality . 201 6.7.2 Improving GPS Precision with Dead Reckoning . 201 6.7.3 Continual Estimation of Relative Positions with Video . 201 xi 6.8 RelatedWork ............................... 202 6.8.1 Localization through Large-Scale Visual Clustering . ..... 202 6.8.2 Aligning Structure from Motion to the Real World . 202 6.8.3 BuildingObjectInventories . 203 6.8.4 ApplyingComputerVisiontoInferContext . 203 6.9 Conclusion................................. 203 6.10 ReferenceEquations . 204 6.10.1 EquationofVisualTrilateration . 204 6.10.2 EquationofVisualTriangulation . 205 7 PredictingClientDwellTimeinWiFiHotspots 209 7.1 Introduction................................ 209 7.2 NaturalQuestions............................. 212 7.3 ToGoPredictionEngine . 214 7.3.1 DesignOverview . 214 7.3.2 Components............................ 215 7.4 BytesToGo: AnApplicationofToGo . 218 7.4.1 Motivation............................. 218 7.4.2 NaturalQuestions . 219 7.4.3 ExtendingfromToGo . 221 7.5 ImplementationandEvaluation . 223 7.5.1 PrototypeImplementation . 223 7.5.2 ToGo Performance: Dwell Prediction Accuracy . 224 7.5.3 BytesToGo Performance: Offloading 3G to WiFi . 230 7.6 Discussion ................................. 233 7.6.1 ConsiderationsforallToGoSystems . 234 xii 7.6.2 Considerations particular
Load more

Recommended publications
  • Toward Building a Safe, Secure, and Easy-To-Use Internet of Things
    IOT CONNECTION Toward Building a Safe, Secure, and Easy-to-Use Sal glances at the display near her office door and sees that her next meeting is in 10 Internet of Things minutes. One participant is out of town and the other two people are running late, but the meeting room is still occupied Infrastructure by several people. The display also suggests it might be a Yuvraj Agarwal and Anind K. Dey, Carnegie Mellon University good time to get coffee because the lines are short at the cafe downstairs. Her good friend Joe Carnegie Mellon University is leading a happens to be at the cafe, too. multi-institutional effort to build an open Sal checks an app she recently built and sees that the coffee is infrastructure to support the Internet of Things. freshly brewed. “That simplifies things,” she thinks to herself as she heads toward the cafe. safe and secure world enabled by the Inter- This is the unique promise of a successful IoT, and is net of Things (IoT) promises to lead to truly what we are aiming for with GIoTTO, the IoT program connected environments, where people and at Carnegie Mellon University (CMU) named after the things collaborate to improve the overall famous Renaissance painter. qualityA of life. The IoT will give us actionable informa- tion at our fingertips, without us having to ask for it or NEED FOR AN OPEN INFRASTRUCTURE even recognizing that it might be needed. Consider this Although numerous commercial and academic programs example that combines many simple uses of the IoT to cu- focus on building IoT systems, it’s clear that for any IoT mulatively form an omnipotent assistant: stack to be widely adopted, it must be open—without a 40 COMPUTER PUBLISHED BY THE IEEE COMPUTER SOCIETY 0018-9162/16/$33.00 © 2016 IEEE EDITOR ROY WANT Google; [email protected] singular organization claiming own- ership.
    [Show full text]
  • Passing the Torch
    From the Editor in Chief Editor in Chief: M. Satyanarayanan ■ Carnegie Mellon University ■ [email protected] Passing the Torch M. Satyanarayanan his issue marks the end of my sec- a highly portable information appliance LOOKING BACK, T ond two-year term as editor in that transforms nearby displays and LOOKING FORWARD chief. I am delighted to introduce my input devices into a transient personal- In August 2001, 10 years after the successor, Roy Want of Intel Research, computing environment. Roy has pub- publication of Mark Weiser’s seminal who will begin his term on 1 January lished extensively over his research career paper introducing the concept of ubiq- 2006. I will continue to serve as active and has over 50 patents to his credit. uitous computing,1 I summarized the editor in chief until that time and will It is hard to imagine a person more field’s progress and reflected on the work closely with Roy to ensure a qualified than Roy to be the next editor challenges ahead in a paper entitled smooth and efficient transition. My in chief of IEEE Pervasive Computing. “Pervasive Computing: Vision and involvement with this publication will In 2001, he was part of the founding edi- Challenges.”2 Looking back, it is grat- continue even after I step down, as I will torial board that created this publication ifying to see how much progress has remain on the editorial board. occurred in just four short years. Many forces have converged to make IN GOOD HANDS It is hard to this progress possible, one of which was Roy received his PhD from Cambridge imagine a substantial industry investment in prod- University in 1988, under the supervision person more uct development relevant to mobile and of Roger Needham.
    [Show full text]
  • Curriculum Vitae: Roy Want
    Curriculum Vitae: Roy Want E-mail: roywant AT google.com ; roywant AT acm.org Google Inc, Mail-Stop: US-MTV-B43 1600 Amphitheatre Parkway Mountain View, CA 94043, USA Office/Cell: (650) 691 3600 Date: January, 2019 Up-to-date CV: http://www.roywant.com/cv/vita.htm Research Interests Mobile & ubiquitous computing, location & context-aware systems, electronic tagging(RFID/NFC/BLE), hardware design, electronic commerce, smart cards, distributed systems, multimedia systems, cellular automata, novel UI, and MEMS. Professional ACM Fellow: 2005, and ACM (Association of Computer Machinery) member since 1996. IEEE Fellow: 2005 and IEEE (Institute for Electrical and Electronic Engineers) member since 1991. Lillian Gilbreth lectureship, National Academy of Engineering (NAE), Washington DC, Oct 12th, 2003 Education Ph.D. Cambridge University UK, Churchill College, Computer Science, Advisor: Roger Needham, 1983-88 o Thesis title: "Reliable Management of Voice in a Distributed System" BA hons. Cambridge University UK, Churchill College, Nat. Science/Computer Science, Tutor: Frank King, 1980-83 o Dissertation title: “A Local Area Network (LAN) Based on the Domestic Mains Supply” High School: William Ellis Grammar School, London UK, 1972-79 Experience Google Inc. (2011-present) o Senior Research Scientist: Google Research and Android Location & Context Team Intel Corporation (2001-2011) o Senior Principal Engineer (SPE) 2008-2011 -Assoc. Director: ILSC (2009-10) & Director (NPL) 2010-11 o Principal Engineer (PE) 2000-2007 Xerox - Palo Alto Research Center (PARC). Computer Science Laboratory (CSL). 1991 - 2001 (reporting to Mark Weiser, Laboratory Manager for CSL; CTO) o Principal Scientist 2000-2001 o Area Manager for Embedded Systems Area 1992-1999 o Member of Research Staff II 1991-1992.
    [Show full text]
  • Annual Report
    ANNUAL REPORT 2019FISCAL YEAR ACM, the Association for Computing Machinery, is an international scientific and educational organization dedicated to advancing the arts, sciences, and applications of information technology. Letter from the President It’s been quite an eventful year and challenges posed by evolving technology. for ACM. While this annual Education has always been at the foundation of exercise allows us a moment ACM, as reflected in two recent curriculum efforts. First, “ACM’s mission to celebrate some of the many the ACM Task Force on Data Science issued “Comput- hinges on successes and achievements ing Competencies for Undergraduate Data Science Cur- creating a the Association has realized ricula.” The guidelines lay out the computing-specific over the past year, it is also an competencies that should be included when other community that opportunity to focus on new academic departments offer programs in data science encompasses and innovative ways to ensure at the undergraduate level. Second, building on the all who work in ACM remains a vibrant global success of our recent guidelines for 4-year cybersecu- the computing resource for the computing community. rity curricula, the ACM Committee for Computing Edu- ACM’s mission hinges on creating a community cation in Community Colleges created a related cur- and technology that encompasses all who work in the computing and riculum targeted at two-year programs, “Cybersecurity arena” technology arena. This year, ACM established a new Di- Curricular Guidance for Associate-Degree Programs.” versity and Inclusion Council to identify ways to create The following pages offer a sampling of the many environments that are welcoming to new perspectives ACM events and accomplishments that occurred over and will attract an even broader membership from the past fiscal year, none of which would have been around the world.
    [Show full text]
  • SOUL: an Edge-Cloud System for Mobile Applications in a Sensor-Rich World
    2016 IEEE/ACM Symposium on Edge Computing SOUL: An Edge-cloud System for Mobile Applications in a Sensor-rich World Minsung Jang∗, HyunJong Lee†, Karsten Schwan‡, Ketan Bhardwaj‡ ∗AT&T Labs - Research, [email protected] †University of Michigan, [email protected] ‡Georgia Institute of Technology, {karsten, ketanbj}@gatech.edu Abstract—With the Internet of Things, sensors are becoming In order for such apps to efficiently interact with and ever more ubiquitous, but interacting with them continues manage the dynamic sets of currently accessible sensors with to present numerous challenges, particularly for applications the associated actuators and software services, SOUL (Sensors running on resource-constrained devices like smartphones. The Of Ubiquitous Life) SOUL abstractions in this paper address two issues faced • by such applications: (1) access to sensors with the levels of externalizes sensor & actuator interactions and process- convenience needed for their ubiquitous, dynamic use, and only ing from the resource-constrained device to edge- and by parties authorized to do so, and (2) scalability in sensor remote-cloud resources, to leverage their computational and access, given today’s multitude of sensors. Toward this end, storage abilities for running the complex sensor processing SOUL, first, introduces a new abstraction for the applications to functionality; transparently and uniformly access both on-device and ambient • sensors with associated actuators. Second, potentially expensive automates reconfiguration of these interactions when sensor-related processing needs not just occur on smartphones, better-matched sensors and actuators become physically but can also leverage edge- and remote-cloud resources. Finally, available; SOUL provides access control methods that permit users to easily • supports existing sensor-based applications allowing define access permissions for sensors, which leverages users’ social ties and captures the context in which access requests them to use SOUL’s capabilities without requiring modi- are made.
    [Show full text]
  • Getmobile MOBILE COMPUTING & COMMUNICATIONS REVIEW
    GetMobile MOBILE COMPUTING & COMMUNICATIONS REVIEW Volume 21, Issue 2 • June 2017 CONTENTS 3 Message from the Editor-in-Chief 16 22 (ALMOST) UNPUBLISHABLE HIGHLIGHTS 5 RESULTS 22 EmotionCheck: A Wearable Device 16 Experiences Deploying an to Regulate Anxiety through False EXPERIMENTAL METHODS Always-On Farm Network Heart Rate Feedback 5 How Do You Know If 85% Accuracy Is Good Enough for Your Application? 26 9 31 26 HemaApp: Noninvasive Blood Screening of Hemoglobin Using Smartphone Cameras MOBILE PLATFORMS 9 Beyond Reality: Head-Mounted 31 Who Are the Smartphone Users? Displays for Mobile Systems Identifying User Groups with Researchers Apps Usage Behaviors 35 Interpretable Machine Learning for Mobile Notification Management: An Overview of PrefMiner 35 2 GetMobile June 2017 | Volume 21, Issue 2 MESSAGE FROM THE EDITOR-IN-CHIEF CONTRIBUTORS EDITOR-IN-CHIEF IN THIS ISSUE, we highlight four papers Eyal de Lara, University of Toronto from ACM UbiComp 2016. MANAGING EDITOR Donna Paris “EmotionCheck: A Wearable Device DESIGNER JoAnn McHardy to Regulate Anxiety through False Heart SENIOR ADVISORS (Past Editors-in-Chief) Rate Feedback,” by Jean Costa, Alexander Paramvir Bahl, Microsoft Research T. Adams, Malte F. Jung, François Suman Banerjee, University of Wisconsin, Madison Guimbretière, and Tanzeem Choudhury, Srikanth Krishnamurthy, University of California, Riverside describes a device that generates subtle Jason Redi, BBN Technologies vibrations on the wrist to resemble a pulse, Mani Srivastava, University of California, Los Angeles which helps users regulate their anxiety Eyal de Lara Nitin Vaidya, University of Illinois, Urbana-Champaign through false feedback of a slow heart rate. SECTION EDITORS In “HemaApp: Noninvasive Blood Screening of Hemoglobin Ardalan Amiri Sami, University of California, Irvine Using Smartphone Cameras,” Edward Jay Wang, William Li, Doug Aruna Balasubramanian, Stony Brook University Nilanjan Banerjee, University of Maryland, Hawkins, Terry Gernsheimer, Colette Norby-Slycord, and Shwetak N.
    [Show full text]
  • Activating the Internet of Things
    COVER FEATURE ACTIVATING THE INTERNET OF THINGS Activating the Internet of Things Roy Want, Google Schahram Dustdar, TU Wien 16 COMPUTER PUBLISHED BY THE IEEE COMPUTER SOCIETY 0018-9162/15/$31.00 © 2015 IEEE Now is the time to tune in, turn on, and plug in— the Internet of Things ushers in a whole new paradigm in our relationship with technology. he Internet of Things (IoT) turn uses an LTE cellular service is a term now widely used to connect to the Internet and ulti- in scholarly technical pub- mately to a cloud service. How- lications and mainstream ever, the common factor for all IoT Tmedia. CEOs of major tech compa- devices—from low-end sensors to nies center their keynote addresses high-end appliances—is that they around this term at top industry will have some form of Internet shows—as illustrated by Samsung connectivity and embedded pro- Activating CEO BK Yoon’s address at this year’s cessing to make use of it. Consumer Electronics Show. Analysts have predicted the What is so exciting about the IoT to be the “next big thing” for IoT? What does it really mean and several years. Gartner recently why should we care? The IoT vision, estimated that there would be the Internet simply put, is that almost any elec- about 5 billion devices connected tronic device can be augmented by a to the Internet in 2015, rising to connection to the Internet, enabling 25 billion by 2020.3 Others see the an ordinary standalone device to IoT as just another overhyped tech of Things become a smart networked device.1 story feeding headlines and giving For example, a garden sprinkler consumers inflated expectations.
    [Show full text]
  • Victor Bahl Microsoft Corporation
    Victor Bahl Microsoft Corporation SIGCOMM MobiArch 2007, August 2007 Source: Victoria Poncini, MS IT ~7, 000 Access Points ~65,000 XP & Vista Clients December 2006 ~40,000 connections/day ~35,000 handheld devices 100% 80% 39,6% 37,3% 42,2% 45,8% 47,1% 60% 40% 39,8% 39,7% 34,2% 44,2% 35,3% 20% 18,1% 20,1% 16,2% 17,6% 22,9% 0% Worldwide Americas w/o PS Puget Sound EMEA APJ Very SfSatisfied SSfSomewhat Satisfied SfSomewhat Dissatisfied or Very Dissati fied 2 Victor Bahl Microsoft’s IT Dept. logs several hundred complaints / month 70% calls are about client connectivity issues (e. g. ping-ponging between APs) 30% (and growing) are about performance problems due to interference End-users complain about Lack of RF coverage, performance & reliability Connectivity & authentication problems Network administrators worry about Providing adequate coverage, performance Security and unauthorized access Corporations spend lots of $$ on WLAN infrastructure WLAN hardware business to reach $2.6 billion in 2007. (Forester 2006) Heavy VC funding in this area (e.g. AirTight $36M in the last 16 months) 3 Victor Bahl 4 Victor Bahl FY05 Cost Element View Functional View Breakdown People 72% Applications 60% Data & Voice 16% App Development (29%) App Support (31%) Hardware 5% Facilities 5% Infrastructure 40% Software* 2% Network (14%) * 5% If MS software were included Data Center (7%) Employee Services (5%) Voice (5%) 30% Helpdesk (5%) New Increases Security (3%) Capability value 45% New 70% Capability Sustaining & Running Decreases Existing maintenance 55% Capability delivery Existing Capability 5 Victor Bahl Timeline HotNets’05 , MobiSys’ 06, NSDI ‘07 ACM CCR ’ 06 MobiCom’ 04 MobiSys’ 06 6 Victor Bahl Heterogeneous world Multiple technologies: 802.
    [Show full text]
  • (Cloudlets/Edges) for Mobile Computing
    emergence of micro datacenter (cloudlets/edges) for mobile computing Victor Bahl Wednesday, May 13, 2015 what if our computers could see? Microsoft’s’s HoloLens who? where? what? Video credits: Matthai Philipose Microsoft Research seeing is for real MSR’s Glimpse project vision is demanding recognition using deep neural networks face1 [1] scene [2] object2[3] memory (floats) 103M 76M 138M compute 1.00 GFLOPs 2.54 GFLOPs 30.9 GFLOPs accuracy 97% 51% 94% (top 5) 1: 4000 people; 2: 1000 objects from ImageNet, top 5: one of your top 5 matches human-level accuracy, heavy resource demands … offloading computation is highly desirable [1] Y. Taigman et al. DeepFace: Closing the Gap to Human-Level Performance in Face Verification. In CVPR 2014. (Facebook) [2] B. Zhou et al. Learning deep features for scene recognition using places database. In NIPS, 2014. [MIT, Princeton, ..] [3] K. Simonyan & A. Zisserman. Very deep convolutional networks for large-scale image recognition. 2014 [Google, Oxford] under review recognition: server versus mobile road sign recognition1 stage Mobile server Spedup (Samsung Galaxy Nexus) (i7, 3.6GHz, 4-core) (server:mobile) detection 2353 +/- 242.4 ms 110 +/- 32.1 ms ~15-16X feature extraction 1327.7 +/- 102.4 ms 69 +/- 15.2 ms ~18X recognition2 162.1 +/- 73.2 ms 11 +/- 1.6 ms ~14X Energy used 11.32 Joules 0.54 Joules ~21X 1convolution neural networks 2classifying 1000 objects with 4096 features using a linear SVM how long does it take to reach the cloud? 3g networks 4g-lte networks T-Mobile 450ms AT&T 350ms MobiSys 2010
    [Show full text]
  • Internet of Things a Survey About Thoughts and Knowledge
    Thesis no: URI: urn:nbn:se:bth-16304 Internet of Things A survey about thoughts and knowledge Eric Nilsson and David Andersson Faculty of Computing Blekinge Institute of Technology SE-371 79 Karlskrona Sweden This thesis is submitted to the Faculty of Computing at Blekinge Institute of Technology in partial fulfillment of the requirements for the bachelor degree in Software Engineering. The thesis is equivalent to 10 weeks of full time studies. Contact Information: Author(s): David Andersson E-mail: [email protected] Eric Nilsson E-mail: [email protected] University advisor: Huseyin Kusetogullari Department of Computer Science and Engineering Faculty of Computing Internet : www.bth.se Blekinge Institute of Technology Phone : +46 455 38 50 00 SE-371 79 Karlskrona, Sweden Fax : +46 455 38 50 57 ii ABSTRACT In this paper we introduce our readers to Internet of Things, what it is, how it works and providing statistics on society knowledge and thoughts about this subject. Data gathered for our statistics will be collected through a survey. From the literature review of this thesis we provide information about how IoT works and how a general architecture behind an IoT product looks like. since IoT comes in all different shapes we want to find out the high-level architecture behind it. With our survey we will first focus on getting the raw knowledge of the society on IoT and these answers will be compared between IT-persons and non-IT persons, then we will get everyone's answers regarding their thoughts on IoT after we have provided information on IoT to get everyone on the same page.
    [Show full text]
  • Building Aggressively Duty-Cycled Platforms to Achieve Energy Efficiency
    UNIVERSITY OF CALIFORNIA, SAN DIEGO Building Aggressively Duty-Cycled Platforms to Achieve Energy Efficiency A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Computer Science (Computer Engineering) by Yuvraj Agarwal Committee in charge: Rajesh Gupta, Chair Paramvir Bahl William Hodgkiss Stefan Savage Alex Snoeren Geoff Voelker 2009 Copyright Yuvraj Agarwal, 2009 All rights reserved. The dissertation of Yuvraj Agarwal is approved, and it is acceptable in quality and form for publication on mi- crofilm and electronically: Chair University of California, San Diego 2009 iii DEDICATION To Dadi, Shyam Babaji, Papa and Ma. iv TABLE OF CONTENTS Signature Page .................................. iii Dedication ..................................... iv Table of Contents ................................. v List of Figures .................................. ix List of Tables ................................... xi Acknowledgements ................................ xii Vita and Publications .............................. xv Abstract of the Dissertation ........................... xvi Chapter 1 Introduction ............................ 1 1.1 Reducing the Energy Consumption of Computing Devices 3 1.2 Using Collaboration to Aggressively Duty-Cycle Platforms 5 1.3 Contributions ........................ 7 1.4 Organization ......................... 8 Chapter 2 Background and Related Work .................. 9 2.1 Mobile Platforms ...................... 9 2.2 Power and Energy ...................... 12 2.2.1 Measuring Power and Energy Consumption .... 13 2.3 Related Work ........................ 14 2.3.1 Power Management in Mobile Devices ....... 14 2.3.2 Power Management in Laptops and Desktop PCs 17 Chapter 3 Radio Collaboration - Cellular and LAN Data Radios ..... 20 3.1 Overview of a VoIP Deployment .............. 23 3.2 Alternatives to VoIP over Wi-Fi Radios .......... 24 3.2.1 Cellular Data vs. Wi-Fi .............. 25 3.2.2 Smartphone Power Measurements ......... 28 3.3 Cell2Notify Architecture .................
    [Show full text]
  • RFID: a Key to Automating Everything
    EBSCOhost 2/21/04 10:50 PM 10 page(s) will be printed. Back Record: 1 Title: RFID: A Key to Automating Everything. Author(s): Want, Roy Source: Scientific American; Jan2004, Vol. 290 Issue 1, p56, 10p, 3 diagrams, 3c Document Type: Article Subject(s): AUTOMATION TECHNOLOGICAL innovations ELECTRONICS INTEGRATED circuits AUTOMOBILE industry & trade MOBILE communication systems WEISER, Mark ELECTRONIC digital computers EMBEDDED computer systems RADIO frequency identification systems Abstract: Already common in security systems and tollbooths, radio-frequency identification tags and readers stand poised to take over many processes now accomplished by human toil. Thirteen years ago, in an article for Scientific American, the late Mark Weiser, then my colleague at Xerox PARC, outlined his bold vision of" ubiquitous computing": small computers would be embedded in everyday objects all around us and, using wireless connections, would respond to our presence, desires and needs without being actively manipulated. Weiser called such systems "calm technology," because they would make it easier for us to focus on our work and other activities, instead of demanding that we interact with and control them, as the typical PC does today. Today systems based on radio-frequency identification (RFID) technology are helping to move Weiser's vision closer to reality. The responsive RFID home--and conference room, office building and car--are still far away, but RFID technology is already in limited use. But the RFID revolution is not without a downside: the technology's growth raises important social issues, and as RFID systems proliferate, we will be forced to address new problems related to privacy, law and ethics.
    [Show full text]