Location information is one of the key enablers to context-aware systems and applications for mobile devices. However, most existing location sensing techniques do not work or will be significantly slowed down without infrastructure support, which limits their applicability in several cases. In this paper, we propose a localization system that works for both indoor and outdoor environments in a completely offline manner. Our system leverages human users' perception of nearby textual signs, without using GPS, Wi-Fi, cellular, and Internet. It enables several important use cases, such as offline localization on wearable devices. Based on real data collected from Google Street View and OpenStreetMap, we examine the feasibility of our approach. The preliminary result was encouraging. Our system was able to achieve higher than 90% accuracy with only 4 iterations even when the speech recognition accuracy is 70%, requiring very small storage space, and consuming 44% less instantaneous power compared to GPS.
{"title":"Human Assisted Positioning Using Textual Signs","authors":"B. Han, Feng Qian, Moo-Ryong Ra","doi":"10.1145/2699343.2699347","DOIUrl":"https://doi.org/10.1145/2699343.2699347","url":null,"abstract":"Location information is one of the key enablers to context-aware systems and applications for mobile devices. However, most existing location sensing techniques do not work or will be significantly slowed down without infrastructure support, which limits their applicability in several cases. In this paper, we propose a localization system that works for both indoor and outdoor environments in a completely offline manner. Our system leverages human users' perception of nearby textual signs, without using GPS, Wi-Fi, cellular, and Internet. It enables several important use cases, such as offline localization on wearable devices. Based on real data collected from Google Street View and OpenStreetMap, we examine the feasibility of our approach. The preliminary result was encouraging. Our system was able to achieve higher than 90% accuracy with only 4 iterations even when the speech recognition accuracy is 70%, requiring very small storage space, and consuming 44% less instantaneous power compared to GPS.","PeriodicalId":252231,"journal":{"name":"Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123511521","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}
Thomas Zachariah, Noah Klugman, Bradford Campbell, Joshua Adkins, Neal Jackson, P. Dutta
The vision of an Internet of Things (IoT) has captured the imagination of the world and raised billions of dollars, all before we stopped to deeply consider how all these Things should connect to the Internet. The current state-of-the-art requires application-layer gateways both in software and hardware that provide application-specific connectivity to IoT devices. In much the same way that it would be difficult to imagine requiring a new web browser for each website, it is hard to imagine our current approach to IoT connectivity scaling to support the IoT vision. The IoT gateway problem exists in part because today's gateways conflate network connectivity, in-network processing, and user interface functions. We believe that disentangling these functions would improve the connectivity potential for IoT devices. To realize the broader vision, we propose an architecture that leverages the increasingly ubiquitous presence of Bluetooth Low Energy radios to connect IoT peripherals to the Internet. In much the same way that WiFi access points revolutionized laptop utility, we envision that a worldwide deployment of IoT gateways could revolutionize application-agnostic connectivity, thus breaking free from the stove-piped architectures now taking hold. In this paper, we present our proposed architecture, show example applications enabled by it, and explore research challenges in its implementation and deployment.
{"title":"The Internet of Things Has a Gateway Problem","authors":"Thomas Zachariah, Noah Klugman, Bradford Campbell, Joshua Adkins, Neal Jackson, P. Dutta","doi":"10.1145/2699343.2699344","DOIUrl":"https://doi.org/10.1145/2699343.2699344","url":null,"abstract":"The vision of an Internet of Things (IoT) has captured the imagination of the world and raised billions of dollars, all before we stopped to deeply consider how all these Things should connect to the Internet. The current state-of-the-art requires application-layer gateways both in software and hardware that provide application-specific connectivity to IoT devices. In much the same way that it would be difficult to imagine requiring a new web browser for each website, it is hard to imagine our current approach to IoT connectivity scaling to support the IoT vision. The IoT gateway problem exists in part because today's gateways conflate network connectivity, in-network processing, and user interface functions. We believe that disentangling these functions would improve the connectivity potential for IoT devices. To realize the broader vision, we propose an architecture that leverages the increasingly ubiquitous presence of Bluetooth Low Energy radios to connect IoT peripherals to the Internet. In much the same way that WiFi access points revolutionized laptop utility, we envision that a worldwide deployment of IoT gateways could revolutionize application-agnostic connectivity, thus breaking free from the stove-piped architectures now taking hold. In this paper, we present our proposed architecture, show example applications enabled by it, and explore research challenges in its implementation and deployment.","PeriodicalId":252231,"journal":{"name":"Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121218820","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}
Tan Zhang, Ashish Patro, Ning Leng, Suman Banerjee
We propose Snoopy, a system that can translate one's mobile phone or tablet into a low-cost, yet effective RF spectrum analyzer. Since typical spectrum analyzers are specialized hardware that is both expensive to acquire and cumbersome to carry around, they are rarely available for quick-and-easy spectrum sensing while on the go. To address this challenge, Snoopy augments popular mobile devices with a small attachable hardware unit (RF frequency translator) that can provide a reasonable view of the wireless spectrum across different frequency bands. It achieves this by leveraging the spectral scan functionality available in certain 802.11 NICs (e.g., the Atheros 9280 family of chipsets), which provides an unique lens towards the WiFi spectrum (2.4 GHz). Through the use of suitable frequency translators, such a view can be flexibly shifted to other spectrum bands. Although such a construction might not match the precision of the most sophisticated but expensive spectrum analyzers, we show that by leveraging some carefully designed spectral features, Snoopy can achieve decent accuracy in determining TV whitespaces (512 -- 698 MHz) -- it can detect primary signals at up to - 90dBm with an error rate of <15%, while achieving a median error of < 4dB in estimating the power of these signals. These promising results suggest that Snoopy is an intriguing option in bringing the ability of spectrum sensing to the masses, thereby truly enabling crowdsourcing options in this domain.
{"title":"A Wireless Spectrum Analyzer in Your Pocket","authors":"Tan Zhang, Ashish Patro, Ning Leng, Suman Banerjee","doi":"10.1145/2699343.2699353","DOIUrl":"https://doi.org/10.1145/2699343.2699353","url":null,"abstract":"We propose Snoopy, a system that can translate one's mobile phone or tablet into a low-cost, yet effective RF spectrum analyzer. Since typical spectrum analyzers are specialized hardware that is both expensive to acquire and cumbersome to carry around, they are rarely available for quick-and-easy spectrum sensing while on the go. To address this challenge, Snoopy augments popular mobile devices with a small attachable hardware unit (RF frequency translator) that can provide a reasonable view of the wireless spectrum across different frequency bands. It achieves this by leveraging the spectral scan functionality available in certain 802.11 NICs (e.g., the Atheros 9280 family of chipsets), which provides an unique lens towards the WiFi spectrum (2.4 GHz). Through the use of suitable frequency translators, such a view can be flexibly shifted to other spectrum bands. Although such a construction might not match the precision of the most sophisticated but expensive spectrum analyzers, we show that by leveraging some carefully designed spectral features, Snoopy can achieve decent accuracy in determining TV whitespaces (512 -- 698 MHz) -- it can detect primary signals at up to - 90dBm with an error rate of <15%, while achieving a median error of < 4dB in estimating the power of these signals. These promising results suggest that Snoopy is an intriguing option in bringing the ability of spectrum sensing to the masses, thereby truly enabling crowdsourcing options in this domain.","PeriodicalId":252231,"journal":{"name":"Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114756729","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}
Animesh Srivastava, Jeremy Gummeson, Mary G. Baker, Kyu-Han Kim
Many people now carry multiple mobile devices on a daily basis. Wearables, smartphones, tablets, and laptops all have their different advantages, but collectively they can increase a user's device management burden. Management problems include leaving a device behind accidentally, receiving notifications on the wrong device, and failing to secure all of the devices as needed. Reducing this burden requires detecting which of a user's devices are "personally collocated" -- those devices he currently wears, carries, or has under his immediate physical control. We present a lightweight method to detect personal collocation by comparing accelerometer-based footstep signatures across the devices over time. Through several experiments, we demonstrate that the technique is lower latency and lower power than state-of-the-art RSSI-based collocation techniques. We describe other advantages and limitations of our method and also provide several examples of higher-layer applications and services that can make use of personal collocation information.
{"title":"Step-by-step Detection of Personally Collocated Mobile Devices","authors":"Animesh Srivastava, Jeremy Gummeson, Mary G. Baker, Kyu-Han Kim","doi":"10.1145/2699343.2699367","DOIUrl":"https://doi.org/10.1145/2699343.2699367","url":null,"abstract":"Many people now carry multiple mobile devices on a daily basis. Wearables, smartphones, tablets, and laptops all have their different advantages, but collectively they can increase a user's device management burden. Management problems include leaving a device behind accidentally, receiving notifications on the wrong device, and failing to secure all of the devices as needed. Reducing this burden requires detecting which of a user's devices are \"personally collocated\" -- those devices he currently wears, carries, or has under his immediate physical control. We present a lightweight method to detect personal collocation by comparing accelerometer-based footstep signatures across the devices over time. Through several experiments, we demonstrate that the technique is lower latency and lower power than state-of-the-art RSSI-based collocation techniques. We describe other advantages and limitations of our method and also provide several examples of higher-layer applications and services that can make use of personal collocation information.","PeriodicalId":252231,"journal":{"name":"Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132644423","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}
Smartwatch is becoming one of the most popular wearable device with many major smartphone manufacturers such as Samsung and Apple releasing their smartwatches recently. Apart from the fitness applications, the smartwatch provides a rich user interface that has enabled many applications like instant messaging and email. Since the smartwatch is worn on the wrist, it introduces a unique opportunity to understand user's arm, hand and possibly finger movements using its accelerometer and gyroscope sensors. Although user's arm and hand gestures are likely to be identified with ease using the smartwatch sensors, it is not clear how much of user's finger gestures can be recognized. In this paper, we show that motion energy measured at the smartwatch is sufficient to uniquely identify user's hand and finger gestures. We identify essential features of accelerometer and gyroscope data that reflect the movements of tendons (passing through the wrist) when performing a finger or a hand gesture. With these features, we build a classifier that can uniquely identify 37 (13 finger, 14 hand and 10 arm) gestures with an accuracy of 98%. We further extend our gesture recognition to identify the characters written by the user with her index finger on a surface, and show that such finger-writing can also be accurately recognized with nearly 95% accuracy. Our presented results will enable many novel applications like remote control and finger-writing-based input to devices using smartwatch.
{"title":"Finger-writing with Smartwatch: A Case for Finger and Hand Gesture Recognition using Smartwatch","authors":"Chao Xu, P. Pathak, P. Mohapatra","doi":"10.1145/2699343.2699350","DOIUrl":"https://doi.org/10.1145/2699343.2699350","url":null,"abstract":"Smartwatch is becoming one of the most popular wearable device with many major smartphone manufacturers such as Samsung and Apple releasing their smartwatches recently. Apart from the fitness applications, the smartwatch provides a rich user interface that has enabled many applications like instant messaging and email. Since the smartwatch is worn on the wrist, it introduces a unique opportunity to understand user's arm, hand and possibly finger movements using its accelerometer and gyroscope sensors. Although user's arm and hand gestures are likely to be identified with ease using the smartwatch sensors, it is not clear how much of user's finger gestures can be recognized. In this paper, we show that motion energy measured at the smartwatch is sufficient to uniquely identify user's hand and finger gestures. We identify essential features of accelerometer and gyroscope data that reflect the movements of tendons (passing through the wrist) when performing a finger or a hand gesture. With these features, we build a classifier that can uniquely identify 37 (13 finger, 14 hand and 10 arm) gestures with an accuracy of 98%. We further extend our gesture recognition to identify the characters written by the user with her index finger on a surface, and show that such finger-writing can also be accurately recognized with nearly 95% accuracy. Our presented results will enable many novel applications like remote control and finger-writing-based input to devices using smartwatch.","PeriodicalId":252231,"journal":{"name":"Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132072258","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}
Geoffrey Challen, J. Ajay, Nick DiRienzo, Oliver Kennedy, Anudipa Maiti, Anandatirtha Nandugudi, S. Shantharam, Jinghao Shi, Guru Prasad Srinivasa, Lukasz Ziarek
One of the reasons programming mobile systems is so hard is the wide variety of environments a typical app encounters at runtime. As a result, in many cases only post-deployment user testing can determine the right algorithm to use, the rate at which something should happen, or when an app should attempt to conserve energy. Programmers should not be forced to make these choices at development time. Unfortunately, languages leave no way for programmers to express and structure uncertainty about runtime conditions, forcing them to adopt ineffective or fragile ad-hoc solutions. We introduce a new approach based on structured uncertainty through a new language construct: the maybe statement. maybe statements allow programmers to defer choices about app behavior that cannot be made at development time, while providing enough structure to allow a system to later adaptively choose from multiple alternatives. Eliminating the uncertainty introduced by maybe statements can be done in a large variety of ways: through simulation, split testing, user configuration, temporal adaptation, or machine learning techniques, depending on the type of adaptation appropriate for each situation. Our paper motivates the maybe statement, presents its syntax, and describes a complete system for testing and choosing from maybe alternatives.
{"title":"maybe We Should Enable More Uncertain Mobile App Programming","authors":"Geoffrey Challen, J. Ajay, Nick DiRienzo, Oliver Kennedy, Anudipa Maiti, Anandatirtha Nandugudi, S. Shantharam, Jinghao Shi, Guru Prasad Srinivasa, Lukasz Ziarek","doi":"10.1145/2699343.2699361","DOIUrl":"https://doi.org/10.1145/2699343.2699361","url":null,"abstract":"One of the reasons programming mobile systems is so hard is the wide variety of environments a typical app encounters at runtime. As a result, in many cases only post-deployment user testing can determine the right algorithm to use, the rate at which something should happen, or when an app should attempt to conserve energy. Programmers should not be forced to make these choices at development time. Unfortunately, languages leave no way for programmers to express and structure uncertainty about runtime conditions, forcing them to adopt ineffective or fragile ad-hoc solutions. We introduce a new approach based on structured uncertainty through a new language construct: the maybe statement. maybe statements allow programmers to defer choices about app behavior that cannot be made at development time, while providing enough structure to allow a system to later adaptively choose from multiple alternatives. Eliminating the uncertainty introduced by maybe statements can be done in a large variety of ways: through simulation, split testing, user configuration, temporal adaptation, or machine learning techniques, depending on the type of adaptation appropriate for each situation. Our paper motivates the maybe statement, presents its syntax, and describes a complete system for testing and choosing from maybe alternatives.","PeriodicalId":252231,"journal":{"name":"Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127037067","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}
Should more academics be making the leap to startups? I have been lucky enough to have that experience: going from a tenured professor position in mobile systems at UMass Amherst to a CTO job at a $100M+ startup in the mobile advertising space, Fiksu Inc. This talk examines some of the tradeoffs between academia and the startup world, the challenges in starting companies, and the calculus for joining them. Startups abound in the world of mobile advertising technology, which provides the economic foundation of the free-to-play internet and the continuing growth of e-commerce. We will delve into the murky world of advertising technology and discuss the unique opportunities that mobile presents
{"title":"Academia, Startups and Mobile Advertising","authors":"M. Corner","doi":"10.1145/2699343.2699368","DOIUrl":"https://doi.org/10.1145/2699343.2699368","url":null,"abstract":"Should more academics be making the leap to startups? I have been lucky enough to have that experience: going from a tenured professor position in mobile systems at UMass Amherst to a CTO job at a $100M+ startup in the mobile advertising space, Fiksu Inc. This talk examines some of the tradeoffs between academia and the startup world, the challenges in starting companies, and the calculus for joining them. Startups abound in the world of mobile advertising technology, which provides the economic foundation of the free-to-play internet and the continuing growth of e-commerce. We will delve into the murky world of advertising technology and discuss the unique opportunities that mobile presents","PeriodicalId":252231,"journal":{"name":"Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications","volume":"397 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131723676","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}
While mobile advertisement is the dominant source of revenue for mobile apps, the usage patterns of mobile users, and thus their engagement and exposure times, may be in conflict with the effectiveness of current ads. Users engagement with apps can range from a few seconds to several minutes, depending on a number of factors such as users' locations, concurrent activities and goals. Despite the wide-range of engagement times, the current format of ad auctions dictates that ads are priced, sold and configured prior to actual viewing, that is regardless of the actual ad exposure time. We argue that the wealth of easy-to-gather contextual information on mobile devices is sufficient to allow advertisers to make better choices by effectively predicting exposure time. We analyze mobile device usage patters with a detailed two-week long user study of 37 users in the US and South Korea. After characterizing application session times, we use factor analysis to derive a simple predictive model and show that is able to offer improved accuracy compared to mean session time over 90% of the time. We make the case for including predicted ad exposure duration in the price of mobile advertisements and posit that such information could significantly impact the effectiveness of mobile ads by giving publishers the ability to tune campaigns for engagement length, and enable a more efficient market for ad impressions while lowering network utilization and device power consumption.
{"title":"Mobile AD(D): Estimating Mobile App Session Times for Better Ads","authors":"John P. Rula, Byungjin Jun, F. Bustamante","doi":"10.1145/2699343.2699365","DOIUrl":"https://doi.org/10.1145/2699343.2699365","url":null,"abstract":"While mobile advertisement is the dominant source of revenue for mobile apps, the usage patterns of mobile users, and thus their engagement and exposure times, may be in conflict with the effectiveness of current ads. Users engagement with apps can range from a few seconds to several minutes, depending on a number of factors such as users' locations, concurrent activities and goals. Despite the wide-range of engagement times, the current format of ad auctions dictates that ads are priced, sold and configured prior to actual viewing, that is regardless of the actual ad exposure time. We argue that the wealth of easy-to-gather contextual information on mobile devices is sufficient to allow advertisers to make better choices by effectively predicting exposure time. We analyze mobile device usage patters with a detailed two-week long user study of 37 users in the US and South Korea. After characterizing application session times, we use factor analysis to derive a simple predictive model and show that is able to offer improved accuracy compared to mean session time over 90% of the time. We make the case for including predicted ad exposure duration in the price of mobile advertisements and posit that such information could significantly impact the effectiveness of mobile ads by giving publishers the ability to tune campaigns for engagement length, and enable a more efficient market for ad impressions while lowering network utilization and device power consumption.","PeriodicalId":252231,"journal":{"name":"Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114722323","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}
Despite decades of work on privacy-protecting systems, mobile user privacy remains at the mercy of cloud service providers. This paper proposes a different approach -- let users attach Terms of Service (ToS) to their data before uploading it to the cloud. We propose an abstraction, called policy-carrying data (PCD), that lets users specify and attach ToS to their data. PCD guarantees that cloud providers claim they are compliant with the ToS policy before they are able to access the data. To offer this guarantee, PCD relies on attribute-based encryption. We present PCD's semantics, its properties, and describe how PCD can be added to JSON or REST. Our hope is that PCD opens a different research path -- designing privacy abstractions that provide legal ammunition for mobile users against misuse of their data.
{"title":"Policy-Carrying Data: A Privacy Abstraction for Attaching Terms of Service to Mobile Data","authors":"S. Saroiu, A. Wolman, S. Agarwal","doi":"10.1145/2699343.2699357","DOIUrl":"https://doi.org/10.1145/2699343.2699357","url":null,"abstract":"Despite decades of work on privacy-protecting systems, mobile user privacy remains at the mercy of cloud service providers. This paper proposes a different approach -- let users attach Terms of Service (ToS) to their data before uploading it to the cloud. We propose an abstraction, called policy-carrying data (PCD), that lets users specify and attach ToS to their data. PCD guarantees that cloud providers claim they are compliant with the ToS policy before they are able to access the data. To offer this guarantee, PCD relies on attribute-based encryption. We present PCD's semantics, its properties, and describe how PCD can be added to JSON or REST. Our hope is that PCD opens a different research path -- designing privacy abstractions that provide legal ammunition for mobile users against misuse of their data.","PeriodicalId":252231,"journal":{"name":"Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126838415","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}
Alarms are often used to set smartphones to perform tasks at scheduled times. Many applications use alarm functionality, and devices consequently experience frequent wake-ups and waste energy. In this paper, we analyze alarm-induced wake-ups in the Android platforms in terms of energy consumption. We propose a "Time Critical Alarm", in which alarms necessarily accompany wake-ups. We then propose, AlarmScope, a scheme to reduce non-critical alarms and thus minimize energy waste. Our evaluation of widely-used applications on Android smartphones shows that the proposed scheme would save between 2.6% and 12.5% of energy use.
{"title":"Reducing Energy Consumption of Alarm-induced Wake-ups on Android Smartphones","authors":"Sewook Park, Dongwon Kim, H. Cha","doi":"10.1145/2699343.2699346","DOIUrl":"https://doi.org/10.1145/2699343.2699346","url":null,"abstract":"Alarms are often used to set smartphones to perform tasks at scheduled times. Many applications use alarm functionality, and devices consequently experience frequent wake-ups and waste energy. In this paper, we analyze alarm-induced wake-ups in the Android platforms in terms of energy consumption. We propose a \"Time Critical Alarm\", in which alarms necessarily accompany wake-ups. We then propose, AlarmScope, a scheme to reduce non-critical alarms and thus minimize energy waste. Our evaluation of widely-used applications on Android smartphones shows that the proposed scheme would save between 2.6% and 12.5% of energy use.","PeriodicalId":252231,"journal":{"name":"Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122315888","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}
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