Android is a popular platform designed for mobile devices. It consists of a customized Linux kernel, middleware, and a few core applications such as the Phone application. The middleware, commonly referred to as the Android framework, provides libraries and runtime services to applications. Applications in Android are written mainly in Java. Once compiled, Android transforms its applications into the Dalvik Executable (or DEX) format to minimize the memory footprint. Android uses a Java VM called Dalvik to execute DEX bytecode. Unlike other mobile OSes, Android has a unique permission mechanism. At development time, an application developer needs to explicitly request permissions by including them in an application configuration file. We refer to this configuration file simply as the manifest invthe remainder of the paper. At installation time, each uservneeds to review the permissions that the application requestsvand explicitly grant them.
{"title":"Android Security via Static Program Analysis","authors":"Feng Shen","doi":"10.1145/3086467.3086469","DOIUrl":"https://doi.org/10.1145/3086467.3086469","url":null,"abstract":"Android is a popular platform designed for mobile devices. It consists of a customized Linux kernel, middleware, and a few core applications such as the Phone application. The middleware, commonly referred to as the Android framework, provides libraries and runtime services to applications. Applications in Android are written mainly in Java. Once compiled, Android transforms its applications into the Dalvik Executable (or DEX) format to minimize the memory footprint. Android uses a Java VM called Dalvik to execute DEX bytecode. Unlike other mobile OSes, Android has a unique permission mechanism. At development time, an application developer needs to explicitly request permissions by including them in an application configuration file. We refer to this configuration file simply as the manifest invthe remainder of the paper. At installation time, each uservneeds to review the permissions that the application requestsvand explicitly grant them.","PeriodicalId":126435,"journal":{"name":"Proceedings of the 2017 Workshop on MobiSys 2017 Ph.D. Forum","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116714077","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}
What happens after your PhD? This talk will be about my personal (evolving) take on how to start an academic career after a PhD. The PhD process is an intense apprenticeship experience that lasts 6 or more years. The advisor guides you through the process, teaches you how to research, write papers, and give talks. But the next stage is equally exciting and unnerving: starting your own research agenda, forming a research group, getting grants and funding, and teaching. I will discuss some aspects that (I think) are important for a robust start to your research career, including serendipity, grabbing opportunities, and just keeping your head down and believing in good work. I will use some examples from the research in my lab to discuss what worked and what did not work.
{"title":"Starting your Research Career after a PhD","authors":"A. Balasubramanian","doi":"10.1145/3086467.3097272","DOIUrl":"https://doi.org/10.1145/3086467.3097272","url":null,"abstract":"What happens after your PhD? This talk will be about my personal (evolving) take on how to start an academic career after a PhD. The PhD process is an intense apprenticeship experience that lasts 6 or more years. The advisor guides you through the process, teaches you how to research, write papers, and give talks. But the next stage is equally exciting and unnerving: starting your own research agenda, forming a research group, getting grants and funding, and teaching. I will discuss some aspects that (I think) are important for a robust start to your research career, including serendipity, grabbing opportunities, and just keeping your head down and believing in good work. I will use some examples from the research in my lab to discuss what worked and what did not work.","PeriodicalId":126435,"journal":{"name":"Proceedings of the 2017 Workshop on MobiSys 2017 Ph.D. Forum","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131673871","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}
Today, mobile devices are equipped with powerful processors along with various on-device sensors. Over the past few years, deep learning has become the dominant approach in the field of machine learning due to its impressive performance. We envision that in the near future, powered by deep learning, mobile devices will become more intelligent and revolutionize a wide range of applications. In this paper, we discuss the challenges of enabling deep learning on mobile platforms. Our work is to propose a deep learning framework that achieves state-of-the-art performance with low overhead on resource-limited mobile platforms. Our preliminary results show that deep learning can efficiently solve object recognition problem under noisy real world environment.
{"title":"Mobile Sensing Through Deep Learning","authors":"Xiao Zeng","doi":"10.1145/3086467.3086476","DOIUrl":"https://doi.org/10.1145/3086467.3086476","url":null,"abstract":"Today, mobile devices are equipped with powerful processors along with various on-device sensors. Over the past few years, deep learning has become the dominant approach in the field of machine learning due to its impressive performance. We envision that in the near future, powered by deep learning, mobile devices will become more intelligent and revolutionize a wide range of applications. In this paper, we discuss the challenges of enabling deep learning on mobile platforms. Our work is to propose a deep learning framework that achieves state-of-the-art performance with low overhead on resource-limited mobile platforms. Our preliminary results show that deep learning can efficiently solve object recognition problem under noisy real world environment.","PeriodicalId":126435,"journal":{"name":"Proceedings of the 2017 Workshop on MobiSys 2017 Ph.D. Forum","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126485686","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}
It is our great pleasure to welcome you to the ACM MobiSys 2017 PhD Forum workshop in Niagara Falls. For the past several years, the PhD Forum has been a regular event of the ACM MobiSys conference. The forum provides a highly interactive, supportive, and friendly environment for PhD students to present and discuss their research with other students and experienced researchers from both academia and industry. In addition to providing feedback and advice, this forum also provides an excellent opportunity for students to build their professional network. This forum is best suited to students who are far enough along in their PhD such that constructive and effective discussions on their thesis can be had. Participants will receive feedback regarding key challenges to solve, research approaches and strategies, as well as the suitability of their research methodologies. This year, the workshop program will consist of three technical sessions with two keynote speakers. The opening keynote will be given by Professor He Wang from Purdue University, followed by our first technical session on Mobile Sensing. Another keynote speech will be given by Dr. Aruna Balasubramanian from Stony Brook University, followed by our last two sessions on Mobile Systems and Wireless Communication and Security.
{"title":"Proceedings of the 2017 Workshop on MobiSys 2017 Ph.D. Forum","authors":"Kevin Boos, Shubham Jain, Tianxing Li","doi":"10.1145/3086467","DOIUrl":"https://doi.org/10.1145/3086467","url":null,"abstract":"It is our great pleasure to welcome you to the ACM MobiSys 2017 PhD Forum workshop in Niagara Falls. For the past several years, the PhD Forum has been a regular event of the ACM MobiSys conference. \u0000 \u0000The forum provides a highly interactive, supportive, and friendly environment for PhD students to present and discuss their research with other students and experienced researchers from both academia and industry. In addition to providing feedback and advice, this forum also provides an excellent opportunity for students to build their professional network. This forum is best suited to students who are far enough along in their PhD such that constructive and effective discussions on their thesis can be had. Participants will receive feedback regarding key challenges to solve, research approaches and strategies, as well as the suitability of their research methodologies. \u0000 \u0000This year, the workshop program will consist of three technical sessions with two keynote speakers. The opening keynote will be given by Professor He Wang from Purdue University, followed by our first technical session on Mobile Sensing. Another keynote speech will be given by Dr. Aruna Balasubramanian from Stony Brook University, followed by our last two sessions on Mobile Systems and Wireless Communication and Security.","PeriodicalId":126435,"journal":{"name":"Proceedings of the 2017 Workshop on MobiSys 2017 Ph.D. Forum","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115094747","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}
Conventional wireless camera systems and the computations running on them for machine vision applications are demanding power-wise. The battery life of wearable camera systems (such as Google Glass) is under an hour when operating with full capacity. Similarly, due to power requirements, surveillance cameras need to be plugged in, which decreases their reliability because cutting the wire would totally disable the camera. In addition, it limits their deployment to places that have access to power wires. My recent work (WISPCam) enabled battery-free image capture by harvesting energy from Radio Frequency signals, but there is a long wait time between receiving consecutive images due to the large power consumption of the camera. The proposed work would extend from my current projects to explore reasons causing cameras to consume significant amount of power and presents ways to eliminate them. In addition, this proposal presents some novel techniques to reduce wearable camera systems' power consumption by exploring low-power hardware architectures and algorithms.
{"title":"Toward Battery-free Smart Cameras","authors":"Saman Naderiparizi","doi":"10.1145/3086467.3086472","DOIUrl":"https://doi.org/10.1145/3086467.3086472","url":null,"abstract":"Conventional wireless camera systems and the computations running on them for machine vision applications are demanding power-wise. The battery life of wearable camera systems (such as Google Glass) is under an hour when operating with full capacity. Similarly, due to power requirements, surveillance cameras need to be plugged in, which decreases their reliability because cutting the wire would totally disable the camera. In addition, it limits their deployment to places that have access to power wires. My recent work (WISPCam) enabled battery-free image capture by harvesting energy from Radio Frequency signals, but there is a long wait time between receiving consecutive images due to the large power consumption of the camera. The proposed work would extend from my current projects to explore reasons causing cameras to consume significant amount of power and presents ways to eliminate them. In addition, this proposal presents some novel techniques to reduce wearable camera systems' power consumption by exploring low-power hardware architectures and algorithms.","PeriodicalId":126435,"journal":{"name":"Proceedings of the 2017 Workshop on MobiSys 2017 Ph.D. Forum","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115915791","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}
In this paper, we propose an easy-to-install and sustainable setup for BigRoad, a system that supports driving and road data acquisition using COTS devices such as smartphones and IMUs. The in-vehicle setup includes energy harvesting modules and a low power motion-based switch to keep the system running for a sufficiently long time without human operations. The device calibration mechanism makes the system independent of vehicle models, steering wheel positions and IMU placements. The system could further leverage infrastructures in the vehicle to design an energy-efficient method for unusual events detection.
{"title":"Enabling Large-Scale Road Data Acquisition with an Easy-to-Install and Sustainable Setup","authors":"Luyang Liu","doi":"10.1145/3086467.3086471","DOIUrl":"https://doi.org/10.1145/3086467.3086471","url":null,"abstract":"In this paper, we propose an easy-to-install and sustainable setup for BigRoad, a system that supports driving and road data acquisition using COTS devices such as smartphones and IMUs. The in-vehicle setup includes energy harvesting modules and a low power motion-based switch to keep the system running for a sufficiently long time without human operations. The device calibration mechanism makes the system independent of vehicle models, steering wheel positions and IMU placements. The system could further leverage infrastructures in the vehicle to design an energy-efficient method for unusual events detection.","PeriodicalId":126435,"journal":{"name":"Proceedings of the 2017 Workshop on MobiSys 2017 Ph.D. Forum","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122196691","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}
Energy efficiency is a key factor in developing mobile sensing applications. Despite its importance, such laborious and time-consuming energy evaluation process makes developers reluctant to perform the measurement during the development. To this end, we propose a novel context-driven energy assessment system, which utilizes the unique characteristic of MSA's energy consumption pattern. We implemented the energy emulation environment, which supports accurate energy estimation in the development environment and repetitive evaluations for the same real-life situations. The evaluation shows that our environment achieves a reasonable energy estimation accuracy of 95.9%.
{"title":"A Context-driven Energy Assessment for Energy-aware Development of Mobile Sensing Applications","authors":"Seungchul Lee","doi":"10.1145/3086467.3086473","DOIUrl":"https://doi.org/10.1145/3086467.3086473","url":null,"abstract":"Energy efficiency is a key factor in developing mobile sensing applications. Despite its importance, such laborious and time-consuming energy evaluation process makes developers reluctant to perform the measurement during the development. To this end, we propose a novel context-driven energy assessment system, which utilizes the unique characteristic of MSA's energy consumption pattern. We implemented the energy emulation environment, which supports accurate energy estimation in the development environment and repetitive evaluations for the same real-life situations. The evaluation shows that our environment achieves a reasonable energy estimation accuracy of 95.9%.","PeriodicalId":126435,"journal":{"name":"Proceedings of the 2017 Workshop on MobiSys 2017 Ph.D. Forum","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115881902","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}
Given the likely government mandate, every new vehicle in the near future is expected to have the capability of "talking" to each other. DSRC is the primary technology that has been developed to implement this capability. Via DSRC technology, vehicles are able to periodically share their status information with other nearby traffic participants, thereby improving situational awareness among all traffic participants. Although much prior work has demonstrated that DSRC technology is adequate to support safety message exchanges, several challenges remain, among which the coexistence of legacy wireless technologies, such as Wi-Fi, and DSRC in the 5.9 GHz band is actively discussed in both the U.S. and Europe. Compared to conventional spectrum sharing scenarios, such as unlicensed devices sharing TV whitespaces, the safety-critical nature of DSRC transmissions places stricter requirements on the effectiveness of spectrum sharing mechanisms. As part of my thesis, I conduct such an analysis by identifying fundamental challenges of sharing the 5.9 GHz band between DSRC and Wi-Fi, providing guidance on challenging scenarios where Wi-Fi devices are not able to provide adequate protection to DSRC devices, and evaluating the performance of two recently proposed spectrum sharing mechanisms, Detect&Vacate and Detect&Mitigate, under these challenging scenarios.
{"title":"Spectrum Sharing of Wi-Fi and DSRC In The 5.9 GHz Band","authors":"Bin Cheng","doi":"10.1145/3086467.3086468","DOIUrl":"https://doi.org/10.1145/3086467.3086468","url":null,"abstract":"Given the likely government mandate, every new vehicle in the near future is expected to have the capability of \"talking\" to each other. DSRC is the primary technology that has been developed to implement this capability. Via DSRC technology, vehicles are able to periodically share their status information with other nearby traffic participants, thereby improving situational awareness among all traffic participants. Although much prior work has demonstrated that DSRC technology is adequate to support safety message exchanges, several challenges remain, among which the coexistence of legacy wireless technologies, such as Wi-Fi, and DSRC in the 5.9 GHz band is actively discussed in both the U.S. and Europe. Compared to conventional spectrum sharing scenarios, such as unlicensed devices sharing TV whitespaces, the safety-critical nature of DSRC transmissions places stricter requirements on the effectiveness of spectrum sharing mechanisms. As part of my thesis, I conduct such an analysis by identifying fundamental challenges of sharing the 5.9 GHz band between DSRC and Wi-Fi, providing guidance on challenging scenarios where Wi-Fi devices are not able to provide adequate protection to DSRC devices, and evaluating the performance of two recently proposed spectrum sharing mechanisms, Detect&Vacate and Detect&Mitigate, under these challenging scenarios.","PeriodicalId":126435,"journal":{"name":"Proceedings of the 2017 Workshop on MobiSys 2017 Ph.D. Forum","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121579953","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}
{"title":"Session details: Wireless Communication and Security","authors":"Tianxing Li","doi":"10.1145/3257294","DOIUrl":"https://doi.org/10.1145/3257294","url":null,"abstract":"","PeriodicalId":126435,"journal":{"name":"Proceedings of the 2017 Workshop on MobiSys 2017 Ph.D. Forum","volume":"25 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115694317","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}
In resource-constrained environments, organizations helping disadvantaged communities often rely on mobile devices as their field worker's primary computing device. While over two-thirds of the world's population have mobile phones, less than half the world's population is connected to the Internet [14]. Thus, many existing mobile frameworks that rely on Internet connectivity are not well suited to long periods of disconnected data collection and management. Furthermore, many existing frameworks are generally aimed at developers or users with significant technical skills and/or financial resources, making it difficult for organizations in resource-constrained communities to adapt mobile frameworks to their highly context dependent field deployments. My research focuses on creating tools that adapt mobile technologies to meet the needs of under-served populations by creating a modular, service-based mobile application framework suited to disconnected data management. The aim is to enable organizations to create domain-independent mobile applications by leveraging customizable frameworks designed to adapt to extreme mobile networking conditions. Designing flexible tools that are configurable by global development organizations necessitates new abstractions that are usable by non-programmers with limited technical expertise. These abstractions should be based on open standards to enable interoperability with other tools to establish an ecosystem of modules that can be used together or independently to create custom information management solutions.
{"title":"Extended Abstract: Building Mobile Application Frameworks for Disconnected Data Management","authors":"Waylon Brunette","doi":"10.1145/3086467.3086475","DOIUrl":"https://doi.org/10.1145/3086467.3086475","url":null,"abstract":"In resource-constrained environments, organizations helping disadvantaged communities often rely on mobile devices as their field worker's primary computing device. While over two-thirds of the world's population have mobile phones, less than half the world's population is connected to the Internet [14]. Thus, many existing mobile frameworks that rely on Internet connectivity are not well suited to long periods of disconnected data collection and management. Furthermore, many existing frameworks are generally aimed at developers or users with significant technical skills and/or financial resources, making it difficult for organizations in resource-constrained communities to adapt mobile frameworks to their highly context dependent field deployments. My research focuses on creating tools that adapt mobile technologies to meet the needs of under-served populations by creating a modular, service-based mobile application framework suited to disconnected data management. The aim is to enable organizations to create domain-independent mobile applications by leveraging customizable frameworks designed to adapt to extreme mobile networking conditions. Designing flexible tools that are configurable by global development organizations necessitates new abstractions that are usable by non-programmers with limited technical expertise. These abstractions should be based on open standards to enable interoperability with other tools to establish an ecosystem of modules that can be used together or independently to create custom information management solutions.","PeriodicalId":126435,"journal":{"name":"Proceedings of the 2017 Workshop on MobiSys 2017 Ph.D. Forum","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127858092","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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