Yin Yan, Shaun Cosgrove, Varun Anand, Amit Kulkarni, Sree Harsha Konduri, Steven Y. Ko, Lukasz Ziarek
This paper presents RTDroid, a variant of Android that provides predictability to Android applications. Although there has been much interest in adopting Android in real-time contexts, surprisingly little work has been done to examine the suitability of Android for real-time systems. Existing work only provides solutions to traditional problems, including real-time garbage collection at the virtual machine layer and kernel-level real-time scheduling and resource management. While it is critical to address these issues, it is by no means sufficient. After all, Android is a vast system that is more than a Java virtual machine and a kernel. Thus, this paper goes beyond existing work and examines the internals of Android. We discuss the implications and challenges of adapting Android constructs and core system services for real-time and present a solution for each. Our system is unique in that it redesigns Android's internal components, replaces Android's Java VM (Dalvik) with a real-time VM, and leverages off-the-shelf real-time OSes. We demonstrate the feasibility and predictability of our solution by evaluating it on three different platforms---an x86 PC, a LEON3 embedded board, and a Nexus S smartphone. The evaluation results show that our design can successfully provide predictability to Android applications, even under heavy load.
本文介绍了RTDroid，它是Android的一个变体，为Android应用程序提供可预测性。尽管人们对在实时环境中采用Android很感兴趣，但令人惊讶的是，很少有人研究Android对实时系统的适用性。现有的工作只提供了传统问题的解决方案，包括虚拟机层的实时垃圾收集和内核级的实时调度和资源管理。虽然解决这些问题至关重要，但这还远远不够。毕竟，Android是一个庞大的系统，不仅仅是一个Java虚拟机和一个内核。因此，本文超越了现有的工作，并研究了Android的内部。我们讨论了实时调整Android结构和核心系统服务的含义和挑战，并提出了各自的解决方案。我们的系统的独特之处在于，它重新设计了Android的内部组件，用实时VM取代了Android的Java VM (Dalvik)，并利用了现成的实时操作系统。我们通过在三个不同的平台(x86 PC、LEON3嵌入式板和Nexus S智能手机)上评估我们的解决方案来证明其可行性和可预测性。评估结果表明，我们的设计可以成功地为Android应用程序提供可预测性，即使在高负载下。
{"title":"Real-time android with RTDroid","authors":"Yin Yan, Shaun Cosgrove, Varun Anand, Amit Kulkarni, Sree Harsha Konduri, Steven Y. Ko, Lukasz Ziarek","doi":"10.1145/2594368.2594381","DOIUrl":"https://doi.org/10.1145/2594368.2594381","url":null,"abstract":"This paper presents RTDroid, a variant of Android that provides predictability to Android applications. Although there has been much interest in adopting Android in real-time contexts, surprisingly little work has been done to examine the suitability of Android for real-time systems. Existing work only provides solutions to traditional problems, including real-time garbage collection at the virtual machine layer and kernel-level real-time scheduling and resource management. While it is critical to address these issues, it is by no means sufficient. After all, Android is a vast system that is more than a Java virtual machine and a kernel. Thus, this paper goes beyond existing work and examines the internals of Android. We discuss the implications and challenges of adapting Android constructs and core system services for real-time and present a solution for each. Our system is unique in that it redesigns Android's internal components, replaces Android's Java VM (Dalvik) with a real-time VM, and leverages off-the-shelf real-time OSes. We demonstrate the feasibility and predictability of our solution by evaluating it on three different platforms---an x86 PC, a LEON3 embedded board, and a Nexus S smartphone. The evaluation results show that our design can successfully provide predictability to Android applications, even under heavy load.","PeriodicalId":131209,"journal":{"name":"Proceedings of the 12th annual international conference on Mobile systems, applications, and services","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117093533","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}
Cory Cornelius, Ronald A. Peterson, Joseph Skinner, R. Halter, D. Kotz
Body-area networks of pervasive wearable devices are increasingly used for health monitoring, personal assistance, entertainment, and home automation. In an ideal world, a user would simply wear their desired set of devices with no configuration necessary: the devices would discover each other, recognize that they are on the same person, construct a secure communications channel, and recognize the user to which they are attached. In this paper we address a portion of this vision by offering a wearable system that unobtrusively recognizes the person wearing it. Because it can recognize the user, our system can properly label sensor data or personalize interactions. Our recognition method uses bioimpedance, a measurement of how tissue responds when exposed to an electrical current. By collecting bioimpedance samples using a small wearable device we designed, our system can determine that (a)the wearer is indeed the expected person and (b)~the device is physically on the wearer's body. Our recognition method works with 98% balanced-accuracy under a cross-validation of a day's worth of bioimpedance samples from a cohort of 8 volunteer subjects. We also demonstrate that our system continues to recognize a subset of these subjects even several months later. Finally, we measure the energy requirements of our system as implemented on a Nexus~S smart phone and custom-designed module for the Shimmer sensing platform.
{"title":"A wearable system that knows who wears it","authors":"Cory Cornelius, Ronald A. Peterson, Joseph Skinner, R. Halter, D. Kotz","doi":"10.1145/2594368.2594369","DOIUrl":"https://doi.org/10.1145/2594368.2594369","url":null,"abstract":"Body-area networks of pervasive wearable devices are increasingly used for health monitoring, personal assistance, entertainment, and home automation. In an ideal world, a user would simply wear their desired set of devices with no configuration necessary: the devices would discover each other, recognize that they are on the same person, construct a secure communications channel, and recognize the user to which they are attached. In this paper we address a portion of this vision by offering a wearable system that unobtrusively recognizes the person wearing it. Because it can recognize the user, our system can properly label sensor data or personalize interactions. Our recognition method uses bioimpedance, a measurement of how tissue responds when exposed to an electrical current. By collecting bioimpedance samples using a small wearable device we designed, our system can determine that (a)the wearer is indeed the expected person and (b)~the device is physically on the wearer's body. Our recognition method works with 98% balanced-accuracy under a cross-validation of a day's worth of bioimpedance samples from a cohort of 8 volunteer subjects. We also demonstrate that our system continues to recognize a subset of these subjects even several months later. Finally, we measure the energy requirements of our system as implemented on a Nexus~S smart phone and custom-designed module for the Shimmer sensing platform.","PeriodicalId":131209,"journal":{"name":"Proceedings of the 12th annual international conference on Mobile systems, applications, and services","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126549011","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}
He Wang, Xuan Bao, Romit Roy Choudhury, Srihari Nelakuditi
We envision augmented-reality applications in which an individual looks at other people through her camera-enabled glass (e.g., Google Glass) and obtains information about them. While face recognition would be one approach to this problem, we believe that it may not be always possible to see a person’s face. Our technique is complementary to face recognition, and exploits the intuition that human motion patterns and clothing colors can together encode several bits of information. Treating this information as a “temporary fingerprint”, it may be feasible to recognize an individual with reasonable consistency, while allowing her to turn off the fingerprint when privacy is of concern. We develop InSight, a system implemented using Android Galaxy smartphones and videos taken from Google Glasses. Results from real world experiments involving up to 21 people show that 8 seconds of their motion patterns together with their clothing colors can discriminate them. These results suggest that face recognition may not be the only option for recognizing humans; human diversity lends itself to sensing and could also serve as an effective identifier.
{"title":"Demo: Recognizing humans without face recognition","authors":"He Wang, Xuan Bao, Romit Roy Choudhury, Srihari Nelakuditi","doi":"10.1145/2594368.2601480","DOIUrl":"https://doi.org/10.1145/2594368.2601480","url":null,"abstract":"We envision augmented-reality applications in which an individual looks at other people through her camera-enabled glass (e.g., Google Glass) and obtains information about them. While face recognition would be one approach to this problem, we believe that it may not be always possible to see a person’s face. Our technique is complementary to face recognition, and exploits the intuition that human motion patterns and clothing colors can together encode several bits of information. Treating this information as a “temporary fingerprint”, it may be feasible to recognize an individual with reasonable consistency, while allowing her to turn off the fingerprint when privacy is of concern. We develop InSight, a system implemented using Android Galaxy smartphones and videos taken from Google Glasses. Results from real world experiments involving up to 21 people show that 8 seconds of their motion patterns together with their clothing colors can discriminate them. These results suggest that face recognition may not be the only option for recognizing humans; human diversity lends itself to sensing and could also serve as an effective identifier.","PeriodicalId":131209,"journal":{"name":"Proceedings of the 12th annual international conference on Mobile systems, applications, and services","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123096536","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}
The smartphone has become an important part of our daily lives. However, the user experience is still far from being optimal. In particular, despite the rapid hardware upgrades, current smartphones often suffer various unpredictable delays during operation, e.g., when launching an application, leading to poor user experience. This video features our study of storage impact on smartphone application delay. We conduct the first large-scale measurement study on the I/O delay of Android using the data collected from our application running on 1009 devices within 130 days. We observe that Android devices spend up to 58% of their CPU active time waiting for storage I/Os to complete. This negatively affects the smartphone's overall application performance, and results in slow response time. Further investigation, among others, reveals that reads experience up to a 626% slowdown in the presence of concurrent writes. The obtained knowledge is used to design and implement a system called SmartIO that reduces the application delay by prioritizing reads over writes, and grouping them based on assigned priorities. SmartIO is implemented on the Android platform and evaluated extensively on several groups of popular applications. The results from the 20 researched applications demonstrate that SmartIO reduces launch delays by up to 37.8%, and run-time delays by up to 29.6%.
{"title":"Video: study of storage impact on smartphone application delay","authors":"David T. Nguyen, Gang Zhou, G. Xing","doi":"10.1145/2594368.2602431","DOIUrl":"https://doi.org/10.1145/2594368.2602431","url":null,"abstract":"The smartphone has become an important part of our daily lives. However, the user experience is still far from being optimal. In particular, despite the rapid hardware upgrades, current smartphones often suffer various unpredictable delays during operation, e.g., when launching an application, leading to poor user experience. This video features our study of storage impact on smartphone application delay. We conduct the first large-scale measurement study on the I/O delay of Android using the data collected from our application running on 1009 devices within 130 days. We observe that Android devices spend up to 58% of their CPU active time waiting for storage I/Os to complete. This negatively affects the smartphone's overall application performance, and results in slow response time. Further investigation, among others, reveals that reads experience up to a 626% slowdown in the presence of concurrent writes. The obtained knowledge is used to design and implement a system called SmartIO that reduces the application delay by prioritizing reads over writes, and grouping them based on assigned priorities. SmartIO is implemented on the Android platform and evaluated extensively on several groups of popular applications. The results from the 20 researched applications demonstrate that SmartIO reduces launch delays by up to 37.8%, and run-time delays by up to 29.6%.","PeriodicalId":131209,"journal":{"name":"Proceedings of the 12th annual international conference on Mobile systems, applications, and services","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115779568","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}
Growing commercial development of WSN/WBAN/IoT solutions will eventually lead to their ubiquitous deployment. Inevitably, there will be environments that contain many independent, co-located networks with overlapping areas of wireless coverage. Examples of high density scenarios include transit stations and urban housing. Because these various networks and applications will be owned by different people and because they mostly operate in ISM bands, there is no trusted authority that can coordinate their activity. Cross-technology interference has been widely studied, e.g. between IEEE 802.11 and IEEE 802.15.4, but very little work has addressed inter-network interference between co-located WSNs using the same communication technology. However, the potentially large number of co-located networks and fairly small number of channels suggests that this will not be an unusual situation. The risk of external frames being received and misinterpreted as local frames is studied in [2], which emphasized the need for authentication on all frames. Interference between co-located IEEE 802.15.4 PANs is demonstrated in [3]. This work reflects a similar interest in timing and interference interactions between networks that can receive and identify, but not decrypt, each other’s frames. The diversity of IEEE 802.15.4-based WSN protocols is the motivating use case. These protocols use the same PHY/ MAC in very different ways, from pure unslotted CSMA to the scheduled mesh in WirelessHART. Such significant differences in channel access mechanisms can lead to adverse interactions between independent networks, which will not be able to explicitly negotiate (or even infer) how to share the channel efficiently. Thus the long-term goal of this work-in-progress is to motivate the development of architecture and design principles that can mitigate problems of inter-network interference. As a specific example, consider two kinds of asynchronous MAC layers. Figure 1 shows interactions between networks using an X-MAC [1] type protocol (i.e. sender strobes, receivers periodically listen) and an RI-MAC [4] type protocol
{"title":"Poster: Motivating an inter-networking architecture for WSN/IoT","authors":"L. Feeney","doi":"10.1145/2594368.2601449","DOIUrl":"https://doi.org/10.1145/2594368.2601449","url":null,"abstract":"Growing commercial development of WSN/WBAN/IoT solutions will eventually lead to their ubiquitous deployment. Inevitably, there will be environments that contain many independent, co-located networks with overlapping areas of wireless coverage. Examples of high density scenarios include transit stations and urban housing. Because these various networks and applications will be owned by different people and because they mostly operate in ISM bands, there is no trusted authority that can coordinate their activity. Cross-technology interference has been widely studied, e.g. between IEEE 802.11 and IEEE 802.15.4, but very little work has addressed inter-network interference between co-located WSNs using the same communication technology. However, the potentially large number of co-located networks and fairly small number of channels suggests that this will not be an unusual situation. The risk of external frames being received and misinterpreted as local frames is studied in [2], which emphasized the need for authentication on all frames. Interference between co-located IEEE 802.15.4 PANs is demonstrated in [3]. This work reflects a similar interest in timing and interference interactions between networks that can receive and identify, but not decrypt, each other’s frames. The diversity of IEEE 802.15.4-based WSN protocols is the motivating use case. These protocols use the same PHY/ MAC in very different ways, from pure unslotted CSMA to the scheduled mesh in WirelessHART. Such significant differences in channel access mechanisms can lead to adverse interactions between independent networks, which will not be able to explicitly negotiate (or even infer) how to share the channel efficiently. Thus the long-term goal of this work-in-progress is to motivate the development of architecture and design principles that can mitigate problems of inter-network interference. As a specific example, consider two kinds of asynchronous MAC layers. Figure 1 shows interactions between networks using an X-MAC [1] type protocol (i.e. sender strobes, receivers periodically listen) and an RI-MAC [4] type protocol","PeriodicalId":131209,"journal":{"name":"Proceedings of the 12th annual international conference on Mobile systems, applications, and services","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131852197","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}
A well-known bottleneck of contemporary mobile devices is the inefficient and error-prone touchscreen keyboard. We have developed UbiK, an alternative portable text-entry method that allows user to type on a piece of paper, placed on solid surfaces like wood desktop. UbiK leverages the microphones on a mobile device to accurately localize the keystrokes through fine-grained acoustic fingerprinting. We have implemented UbiK as an Android application. Our experiments demonstrate that UbiK is able to achieve above 95% of localization accuracy. In this demonstration, we will show how Ubik works with an external paper keyboard (Figure 1) for a smartphone and a 7-inch tablet. User participation will be welcome in this live demo.
{"title":"Demo: A paper keyboard for mobile devices","authors":"Junjue Wang, Kaichen Zhao, Xinyu Zhang, Chunyi Peng","doi":"10.1145/2594368.2601476","DOIUrl":"https://doi.org/10.1145/2594368.2601476","url":null,"abstract":"A well-known bottleneck of contemporary mobile devices is the inefficient and error-prone touchscreen keyboard. We have developed UbiK, an alternative portable text-entry method that allows user to type on a piece of paper, placed on solid surfaces like wood desktop. UbiK leverages the microphones on a mobile device to accurately localize the keystrokes through fine-grained acoustic fingerprinting. We have implemented UbiK as an Android application. Our experiments demonstrate that UbiK is able to achieve above 95% of localization accuracy. In this demonstration, we will show how Ubik works with an external paper keyboard (Figure 1) for a smartphone and a 7-inch tablet. User participation will be welcome in this live demo.","PeriodicalId":131209,"journal":{"name":"Proceedings of the 12th annual international conference on Mobile systems, applications, and services","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115791506","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}
Kyungmin Lee, David Chu, Eduardo Cuervo, A. Wolman, J. Flinn
Playing games on mobile devices is very popular. Recently, cloud gaming – where datacenter servers execute the games on behalf of thin clients that merely transmit UI input events and display output rendered by the servers – has emerged as an interesting alternative to traditional clientside game execution. Cloud Gaming-as-a-Service (GaaS) offers several advantages salient to mobile clients. First, users with low end devices can get the same high quality experience as users with high end devices. Second, mobile game developers avoid two challenges that arise with the huge diversity of mobile devices: platform compatibility headaches and per-platform performance tuning. Third, upgrading servers (e.g., for bug fixes, game updates, etc.) becomes far easier than redeploying new software to clients. Finally, players can select from a vast library of games and instantly play any of them. However, GaaS on mobile devices faces a key technical dilemma: how can players attain real-time interactivity in the face of wide-area latency? Real-time interactivity means client input events should be quickly reflected on the client display. User studies have shown that players are sensitive to as little as 60 ms latency, and are aggravated at latencies in excess of 100 ms [1]. A further delay degradation from 150 ms to 250 ms lowers user engagement by 75% [2]. Instead, we propose to mitigate wide-area latency via speculative execution. We present DeLorean a system that delivers real-time gaming interactivity as fast as traditional local client-side execution, despite with network latencies. DeLorean’s basic approach combines input prediction with speculative execution to render mulitple possible frame outputs which could occur RTT milliseconds in the future. DeLorean employs the following techniques to accomplish this. Future Input Prediction: Given the user’s historical tendencies and recent behavior, we show that some categories of user actions are highly predictable. We develop a Markovbased prediction model that examines recent user input to forecast expected future input. We use two techniques to improve prediction quality: supersampling of input events,
{"title":"Demo: DeLorean: using speculation to enable low-latency continuous interaction for mobile cloud gaming","authors":"Kyungmin Lee, David Chu, Eduardo Cuervo, A. Wolman, J. Flinn","doi":"10.1145/2594368.2601474","DOIUrl":"https://doi.org/10.1145/2594368.2601474","url":null,"abstract":"Playing games on mobile devices is very popular. Recently, cloud gaming – where datacenter servers execute the games on behalf of thin clients that merely transmit UI input events and display output rendered by the servers – has emerged as an interesting alternative to traditional clientside game execution. Cloud Gaming-as-a-Service (GaaS) offers several advantages salient to mobile clients. First, users with low end devices can get the same high quality experience as users with high end devices. Second, mobile game developers avoid two challenges that arise with the huge diversity of mobile devices: platform compatibility headaches and per-platform performance tuning. Third, upgrading servers (e.g., for bug fixes, game updates, etc.) becomes far easier than redeploying new software to clients. Finally, players can select from a vast library of games and instantly play any of them. However, GaaS on mobile devices faces a key technical dilemma: how can players attain real-time interactivity in the face of wide-area latency? Real-time interactivity means client input events should be quickly reflected on the client display. User studies have shown that players are sensitive to as little as 60 ms latency, and are aggravated at latencies in excess of 100 ms [1]. A further delay degradation from 150 ms to 250 ms lowers user engagement by 75% [2]. Instead, we propose to mitigate wide-area latency via speculative execution. We present DeLorean a system that delivers real-time gaming interactivity as fast as traditional local client-side execution, despite with network latencies. DeLorean’s basic approach combines input prediction with speculative execution to render mulitple possible frame outputs which could occur RTT milliseconds in the future. DeLorean employs the following techniques to accomplish this. Future Input Prediction: Given the user’s historical tendencies and recent behavior, we show that some categories of user actions are highly predictable. We develop a Markovbased prediction model that examines recent user input to forecast expected future input. We use two techniques to improve prediction quality: supersampling of input events,","PeriodicalId":131209,"journal":{"name":"Proceedings of the 12th annual international conference on Mobile systems, applications, and services","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115833749","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}
A recent analysis[3] indicates that most user interactions with smartphones are short. Specifically, 80% of the apps are used for less than two minutes. With such brief interactions, apps should be rapid and responsive. However, the same study reports that many apps incur significant delays during launch and run-time. This work addresses two key research questions towards achieving rapid app response. (1) How does disk I/O performance affect smartphone app response time? (2) How can we improve app performance with I/O optimization techniques? We address the questions via following contributions. First, through a large-scale measurement study based on the data collected within 130 days from 1009 Android devices using an app[2] we developed, we find that Android devices spend a significant portion of their CPU active time (up to 58%) waiting for storage I/Os to complete, also known as iowait (Figure 1). This negatively affects the smartphone’s overall app performance, and results in slow response time. Further investigation reveals that a read experiences up to 626% slowdown when blocked by a concurrent write. Additionally, the results indicate significant asymmetry in the slowdown of one I/O type due to another. Finally, we study the speedup of concurrent I/Os, and the results suggest that reads benefit more from concurrency.
{"title":"Poster: Towards reducing smartphone application delay through read/write isolation","authors":"David T. Nguyen, Gang Zhou, G. Xing","doi":"10.1145/2594368.2601458","DOIUrl":"https://doi.org/10.1145/2594368.2601458","url":null,"abstract":"A recent analysis[3] indicates that most user interactions with smartphones are short. Specifically, 80% of the apps are used for less than two minutes. With such brief interactions, apps should be rapid and responsive. However, the same study reports that many apps incur significant delays during launch and run-time. This work addresses two key research questions towards achieving rapid app response. (1) How does disk I/O performance affect smartphone app response time? (2) How can we improve app performance with I/O optimization techniques? We address the questions via following contributions. First, through a large-scale measurement study based on the data collected within 130 days from 1009 Android devices using an app[2] we developed, we find that Android devices spend a significant portion of their CPU active time (up to 58%) waiting for storage I/Os to complete, also known as iowait (Figure 1). This negatively affects the smartphone’s overall app performance, and results in slow response time. Further investigation reveals that a read experiences up to 626% slowdown when blocked by a concurrent write. Additionally, the results indicate significant asymmetry in the slowdown of one I/O type due to another. Finally, we study the speedup of concurrent I/Os, and the results suggest that reads benefit more from concurrency.","PeriodicalId":131209,"journal":{"name":"Proceedings of the 12th annual international conference on Mobile systems, applications, and services","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122528439","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}
This paper describes WalkCompass, a system that exploits smartphone sensors to estimate the direction in which a user is walking. We find that several smartphone localization systems in the recent past, including our own, make a simplifying assumption that the user's walking direction is known. In trying to relax this assumption, we were not able to find a generic solution from past work. While intuition suggests that the walking direction should be detectable through the accelerometer, in reality this direction gets blended into various other motion patterns during the act of walking, including up and down bounce, side-to-side sway, swing of arms or legs, etc. Moreover, the walking direction is in the phone's local coordinate system (e.g., along Y axis), and translation to global directions, such as 45 degree North, can be challenging when the compass is itself erroneous. WalkCompass copes with these challenges and develops a stable technique to estimate the user's walking direction within a few steps. Results drawn from 15 different environments demonstrate median error of less than 8 degrees, across 6 different users, 3 surfaces, and 3 holding positions. While there is room for improvement, we believe our current system can be immediately useful to various applications centered around localization and human activity recognition.
{"title":"I am a smartphone and i can tell my user's walking direction","authors":"Nirupam Roy, He Wang, Romit Roy Choudhury","doi":"10.1145/2594368.2594392","DOIUrl":"https://doi.org/10.1145/2594368.2594392","url":null,"abstract":"This paper describes WalkCompass, a system that exploits smartphone sensors to estimate the direction in which a user is walking. We find that several smartphone localization systems in the recent past, including our own, make a simplifying assumption that the user's walking direction is known. In trying to relax this assumption, we were not able to find a generic solution from past work. While intuition suggests that the walking direction should be detectable through the accelerometer, in reality this direction gets blended into various other motion patterns during the act of walking, including up and down bounce, side-to-side sway, swing of arms or legs, etc. Moreover, the walking direction is in the phone's local coordinate system (e.g., along Y axis), and translation to global directions, such as 45 degree North, can be challenging when the compass is itself erroneous. WalkCompass copes with these challenges and develops a stable technique to estimate the user's walking direction within a few steps. Results drawn from 15 different environments demonstrate median error of less than 8 degrees, across 6 different users, 3 surfaces, and 3 holding positions. While there is room for improvement, we believe our current system can be immediately useful to various applications centered around localization and human activity recognition.","PeriodicalId":131209,"journal":{"name":"Proceedings of the 12th annual international conference on Mobile systems, applications, and services","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126252913","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}
Soumendra Nanda, B. DeCleene, V. Firoiu, M. Leung, Yingbo Song, C. Tao
Wireless researchers face the practical challenge of evaluating the performance of new routing protocols for very large-scale heterogeneous mobile systems. While simulation platforms, tools and techniques have matured, doubts remain about the broad validity of simulated results when applied to real world situations. Wireless network emulation provides a middle ground between simulations and real-world testing. However, emulation environments are complex to run and cost-prohibitive for larger-scale tests. In order to maximize fidelity while managing complexity and costs, we developed a common framework that unifies simulation-based analysis and emulation experiment tools, in order to produce calibrated and scalable performance evaluations.
{"title":"Poster: Scalable evaluation for wireless mobile systems","authors":"Soumendra Nanda, B. DeCleene, V. Firoiu, M. Leung, Yingbo Song, C. Tao","doi":"10.1145/2594368.2601450","DOIUrl":"https://doi.org/10.1145/2594368.2601450","url":null,"abstract":"Wireless researchers face the practical challenge of evaluating the performance of new routing protocols for very large-scale heterogeneous mobile systems. While simulation platforms, tools and techniques have matured, doubts remain about the broad validity of simulated results when applied to real world situations. Wireless network emulation provides a middle ground between simulations and real-world testing. However, emulation environments are complex to run and cost-prohibitive for larger-scale tests. In order to maximize fidelity while managing complexity and costs, we developed a common framework that unifies simulation-based analysis and emulation experiment tools, in order to produce calibrated and scalable performance evaluations.","PeriodicalId":131209,"journal":{"name":"Proceedings of the 12th annual international conference on Mobile systems, applications, and services","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127570172","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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