Mohamed Ibrahim, Ali Rostami, Bo Yu, Hansi Liu, M. Jawahar, Viet Nguyen, M. Gruteser, F. Bai, R. Howard
Driver assistance and vehicular automation would greatly benefit from uninterrupted lane-level vehicle positioning, especially in challenging environments like metropolitan cities. In this paper, we explore whether the WiFi Fine Time Measurement (FTM) protocol, with its robust, accurate ranging capability, can complement current GPS and odometry systems to achieve lane-level positioning in urban canyons. We introduce Wi-Go, a system that simultaneously tracks vehicles and maps WiFi access point positions by coherently fusing WiFi FTMs, GPS, and vehicle odometry information together. Wi-Go also adaptively controls the FTM messaging rate from clients to prevent high bandwidth usage and congestion, while maximizing the tracking accuracy. Wi-Go achieves lane-level vehicle positioning (1.3 m median and 2.9 m 90-percentile error), an order of magnitude improvement over vehicle built-in GPS, through vehicle experiments in the urban canyons of Manhattan, New York City, as well as in suburban areas (0.8 m median and 3.2 m 90-percentile error).
{"title":"Wi-Go: accurate and scalable vehicle positioning using WiFi fine timing measurement","authors":"Mohamed Ibrahim, Ali Rostami, Bo Yu, Hansi Liu, M. Jawahar, Viet Nguyen, M. Gruteser, F. Bai, R. Howard","doi":"10.1145/3386901.3388944","DOIUrl":"https://doi.org/10.1145/3386901.3388944","url":null,"abstract":"Driver assistance and vehicular automation would greatly benefit from uninterrupted lane-level vehicle positioning, especially in challenging environments like metropolitan cities. In this paper, we explore whether the WiFi Fine Time Measurement (FTM) protocol, with its robust, accurate ranging capability, can complement current GPS and odometry systems to achieve lane-level positioning in urban canyons. We introduce Wi-Go, a system that simultaneously tracks vehicles and maps WiFi access point positions by coherently fusing WiFi FTMs, GPS, and vehicle odometry information together. Wi-Go also adaptively controls the FTM messaging rate from clients to prevent high bandwidth usage and congestion, while maximizing the tracking accuracy. Wi-Go achieves lane-level vehicle positioning (1.3 m median and 2.9 m 90-percentile error), an order of magnitude improvement over vehicle built-in GPS, through vehicle experiments in the urban canyons of Manhattan, New York City, as well as in suburban areas (0.8 m median and 3.2 m 90-percentile error).","PeriodicalId":345029,"journal":{"name":"Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126316794","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}
Higher privileged trust anchors such as thin hypervisors and Trust-Zone have been adopted to protect mobile OSs. For instance, the Samsung Knox security platform implements a kernel integrity monitor based on a hardware-assisted virtualization technique for 64-bit devices. Although it protects the OS kernel integrity, the monitoring platform itself can be a target of attackers if it encompasses exploitable bugs. In this paper, we propose SelMon, a portable way of self-protecting kernel integrity monitors without introducing another higher privileged trust anchor. To this end, we first logically separate the regions of the integrity monitor into two parts: privileged and non-privileged regions. Then, we ensure that only the privileged region code can access the critical data objects that can be exploited to compromise the monitor integrity (e.g., the hypervisor page table). The non-critical operations in terms of preserving the monitor integrity are conducted in the non-privileged region. In addition to the privilege separation, we also illustrate how to utilize the general hardware features, watchpoint and data execution prevention (DEP), to ensure the robustness of the separation. In the evaluation, it was found that our approach imposes a negligible overhead of 2% in the worst case with SPEC CPU2006.
{"title":"SelMon","authors":"Jinsoo Jang, Brent Byunghoon Kang","doi":"10.1145/3386901.3389023","DOIUrl":"https://doi.org/10.1145/3386901.3389023","url":null,"abstract":"Higher privileged trust anchors such as thin hypervisors and Trust-Zone have been adopted to protect mobile OSs. For instance, the Samsung Knox security platform implements a kernel integrity monitor based on a hardware-assisted virtualization technique for 64-bit devices. Although it protects the OS kernel integrity, the monitoring platform itself can be a target of attackers if it encompasses exploitable bugs. In this paper, we propose SelMon, a portable way of self-protecting kernel integrity monitors without introducing another higher privileged trust anchor. To this end, we first logically separate the regions of the integrity monitor into two parts: privileged and non-privileged regions. Then, we ensure that only the privileged region code can access the critical data objects that can be exploited to compromise the monitor integrity (e.g., the hypervisor page table). The non-critical operations in terms of preserving the monitor integrity are conducted in the non-privileged region. In addition to the privilege separation, we also illustrate how to utilize the general hardware features, watchpoint and data execution prevention (DEP), to ensure the robustness of the separation. In the evaluation, it was found that our approach imposes a negligible overhead of 2% in the worst case with SPEC CPU2006.","PeriodicalId":345029,"journal":{"name":"Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120896403","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}
Ju Wang, Liqiong Chang, S. Aggarwal, Omid Salehi-Abari, Srinivasan Keshav
Intelligent irrigation based on measurements of soil moisture levels in every pot in a greenhouse can not only improve plant productivity and quality but also save water. However, existing soil moisture sensors are too expensive to deploy in every pot. We therefore introduce GreenTag, a low-cost RFID-based soil moisture sensing system whose accuracy is comparable to that of an expensive soil moisture sensor. Our key idea is to attach two RFID tags to a plant's container so that changes in soil moisture content are reflected in their Differential Minimum Response Threshold (DMRT) metric at the reader. We show that a low-pass filtered DMRT metric is robust to changes both in the RF environment (e.g., from human movement) and in pot locations. In a realistic setting, GreenTag achieves a 90-percentile moisture estimation errors of 5%, which is comparable to the 4% errors using expensive soil moisture sensors. Moreover, this accuracy is maintained despite changes in the RF environment and container locations. We also show the effectiveness of GreenTag in a real greenhouse.
{"title":"Soil moisture sensing with commodity RFID systems","authors":"Ju Wang, Liqiong Chang, S. Aggarwal, Omid Salehi-Abari, Srinivasan Keshav","doi":"10.1145/3386901.3388940","DOIUrl":"https://doi.org/10.1145/3386901.3388940","url":null,"abstract":"Intelligent irrigation based on measurements of soil moisture levels in every pot in a greenhouse can not only improve plant productivity and quality but also save water. However, existing soil moisture sensors are too expensive to deploy in every pot. We therefore introduce GreenTag, a low-cost RFID-based soil moisture sensing system whose accuracy is comparable to that of an expensive soil moisture sensor. Our key idea is to attach two RFID tags to a plant's container so that changes in soil moisture content are reflected in their Differential Minimum Response Threshold (DMRT) metric at the reader. We show that a low-pass filtered DMRT metric is robust to changes both in the RF environment (e.g., from human movement) and in pot locations. In a realistic setting, GreenTag achieves a 90-percentile moisture estimation errors of 5%, which is comparable to the 4% errors using expensive soil moisture sensors. Moreover, this accuracy is maintained despite changes in the RF environment and container locations. We also show the effectiveness of GreenTag in a real greenhouse.","PeriodicalId":345029,"journal":{"name":"Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121475215","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}
Many users have reported that their smartphones shut off unexpectedly, even when they show >30% remaining battery capacity. After examining the problem from both the user and phone sides, we discovered the cause of these unexpected shutoffs to be a large and dynamic internal voltage drop of the phone battery, which is, in turn, caused by the dynamics of both battery's internal resistance and the phone's discharge current. To fix these unexpected shutoffs, we design a novel Battery-aware Power Management (BPM) middleware that accounts for these dual-dynamics in phone operation. Specifically, BPM profiles the battery's internal resistance --- which varies with battery state-of-charge (SoC), temperature, and aging --- using a novel duty-cycled charging method. BPM then regulates, at run-time, the phone's discharge current based on the constructed battery profile. We have implemented and evaluated BPM on 4 commodity smartphones from different OEMs with the latest battery firmware, demonstrating that BPM prevents unexpected phone shutoffs and extends their operation time by 1.16--2.03X. Our user study, which includes 121 mobile phone users, also corroborates BPM's usefulness/attractiveness.
{"title":"Causes and fixes of unexpected phone shutoffs","authors":"Youngmoon Lee, Liang He, K. Shin","doi":"10.1145/3386901.3389024","DOIUrl":"https://doi.org/10.1145/3386901.3389024","url":null,"abstract":"Many users have reported that their smartphones shut off unexpectedly, even when they show >30% remaining battery capacity. After examining the problem from both the user and phone sides, we discovered the cause of these unexpected shutoffs to be a large and dynamic internal voltage drop of the phone battery, which is, in turn, caused by the dynamics of both battery's internal resistance and the phone's discharge current. To fix these unexpected shutoffs, we design a novel Battery-aware Power Management (BPM) middleware that accounts for these dual-dynamics in phone operation. Specifically, BPM profiles the battery's internal resistance --- which varies with battery state-of-charge (SoC), temperature, and aging --- using a novel duty-cycled charging method. BPM then regulates, at run-time, the phone's discharge current based on the constructed battery profile. We have implemented and evaluated BPM on 4 commodity smartphones from different OEMs with the latest battery firmware, demonstrating that BPM prevents unexpected phone shutoffs and extends their operation time by 1.16--2.03X. Our user study, which includes 121 mobile phone users, also corroborates BPM's usefulness/attractiveness.","PeriodicalId":345029,"journal":{"name":"Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131157293","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}
Fengyuan Zhu, Yuda Feng, Qianru Li, Xiaohua Tian, Xinbing Wang
Recently proposed OFDMA backscatter could improve both concurrency and spectrum allocation flexibility for backscatter systems based on OFDM. However, we find that it is remarkably inefficient for the existing design to scale up in prototyping: it requires one-by-one offline computation to obtain tags' operating parameters, in order to ensure orthogonality among subcarriers in the system; moreover, the tag hardware has to be dedicatedly modified offline before being assigned multiple subcarriers. The inefficiency is caused by the current analog frequency synthesis design for the tag. This paper proposes DigiScatter, an OFDMA backscatter system realizing digital frequency synthesis, which provides an efficient prototyping approach for large-scale OFDMA backscatter networks. In DigiScatter, we for the first time integrate IDFT into the tag design; such a simple but effective improvement enables the system to support high concurrency and flexible spectrum resource allocation through pure software configurations in an online manner. We build a prototype and conduct comprehensive experiments to validate our design. DigiScatter physically realizes 100 and 300 concurrent OFDMA backscatter transmissions in 2.4GHz and 900MHz respectively, and provides frequency synthesis capability for supporting 1019 concurrent transmissions.
{"title":"DigiScatter","authors":"Fengyuan Zhu, Yuda Feng, Qianru Li, Xiaohua Tian, Xinbing Wang","doi":"10.1145/3386901.3388914","DOIUrl":"https://doi.org/10.1145/3386901.3388914","url":null,"abstract":"Recently proposed OFDMA backscatter could improve both concurrency and spectrum allocation flexibility for backscatter systems based on OFDM. However, we find that it is remarkably inefficient for the existing design to scale up in prototyping: it requires one-by-one offline computation to obtain tags' operating parameters, in order to ensure orthogonality among subcarriers in the system; moreover, the tag hardware has to be dedicatedly modified offline before being assigned multiple subcarriers. The inefficiency is caused by the current analog frequency synthesis design for the tag. This paper proposes DigiScatter, an OFDMA backscatter system realizing digital frequency synthesis, which provides an efficient prototyping approach for large-scale OFDMA backscatter networks. In DigiScatter, we for the first time integrate IDFT into the tag design; such a simple but effective improvement enables the system to support high concurrency and flexible spectrum resource allocation through pure software configurations in an online manner. We build a prototype and conduct comprehensive experiments to validate our design. DigiScatter physically realizes 100 and 300 concurrent OFDMA backscatter transmissions in 2.4GHz and 900MHz respectively, and provides frequency synthesis capability for supporting 1019 concurrent transmissions.","PeriodicalId":345029,"journal":{"name":"Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services","volume":"1 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114018661","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}
Backscatter communication, in which data is conveyed through reflecting excitation signals, has been advocated as a promising green technology for Internet of Things (IoT). Existing backscatter solutions however are mostly centralized, relying on a single excitation source, typically within one hop. Though recent works have demonstrated the viability of multi-hop backscatter, the excitation signal remains centralized, which attenuates quickly and fundamentally limits the communication scope. For long-range and high-quality communication, distributed excitations are expected and also naturally available as ambient signals (WiFi, BLE, cellular, FM, light, sound, etc.), albeit not being explored for boosting nearby tags for relaying. Given the existence of distributed excitation, a relay tag has to be decodable, i.e., be able to first decode its previous hop's information and then backscatter to the next hop with a boost from a nearby excitation whenever possible. In this paper, we present DecRel, a decodable tag relay solution towards a backscatter sensor mesh for universal and scalable deployment with distributed excitation. DecRel is also an innovative wireless sensor architecture for simultaneous sensing and relay. It incorporates a relay path that uses envelope detection for decoding, and a sensing path that converts its own sensor data into a baseband for amplitude-demodulation by the next hop tag's relay path. The two paths then backscatter their respective data to different frequencies to avoid interference. We have built a working DecRel tag prototype using FPGA, discrete components, and off-the-shelf analog devices. Our experiments show superior performance of DecRel as compared with the state-of-the-art non-decodable tag relay: specifically, a digital baseband's multi-hop throughput of up to 40Kbps (200x improvement), an analog baseband's equivalent multi-hop throughput of up to 768Kbps (3000x improvement), and a tag-to-tag distance of up to 4.8m (10x improvement) with a hop count of up to 6. DecRel tag consumes 337.9μW of power using IC design.
{"title":"Towards scalable backscatter sensor mesh with decodable relay and distributed excitation","authors":"Jia Zhao, Wei Gong, Jiangchuan Liu","doi":"10.1145/3386901.3388942","DOIUrl":"https://doi.org/10.1145/3386901.3388942","url":null,"abstract":"Backscatter communication, in which data is conveyed through reflecting excitation signals, has been advocated as a promising green technology for Internet of Things (IoT). Existing backscatter solutions however are mostly centralized, relying on a single excitation source, typically within one hop. Though recent works have demonstrated the viability of multi-hop backscatter, the excitation signal remains centralized, which attenuates quickly and fundamentally limits the communication scope. For long-range and high-quality communication, distributed excitations are expected and also naturally available as ambient signals (WiFi, BLE, cellular, FM, light, sound, etc.), albeit not being explored for boosting nearby tags for relaying. Given the existence of distributed excitation, a relay tag has to be decodable, i.e., be able to first decode its previous hop's information and then backscatter to the next hop with a boost from a nearby excitation whenever possible. In this paper, we present DecRel, a decodable tag relay solution towards a backscatter sensor mesh for universal and scalable deployment with distributed excitation. DecRel is also an innovative wireless sensor architecture for simultaneous sensing and relay. It incorporates a relay path that uses envelope detection for decoding, and a sensing path that converts its own sensor data into a baseband for amplitude-demodulation by the next hop tag's relay path. The two paths then backscatter their respective data to different frequencies to avoid interference. We have built a working DecRel tag prototype using FPGA, discrete components, and off-the-shelf analog devices. Our experiments show superior performance of DecRel as compared with the state-of-the-art non-decodable tag relay: specifically, a digital baseband's multi-hop throughput of up to 40Kbps (200x improvement), an analog baseband's equivalent multi-hop throughput of up to 768Kbps (3000x improvement), and a tag-to-tag distance of up to 4.8m (10x improvement) with a hop count of up to 6. DecRel tag consumes 337.9μW of power using IC design.","PeriodicalId":345029,"journal":{"name":"Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127059558","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}
Haehyun Cho, Jinbum Park, Donguk Kim, Ziming Zhao, Yan Shoshitaishvili, Adam Doupé, Gail-Joon Ahn
Cache side-channel attacks abuse microarchitectural designs meant to optimize memory access to infer information about victim processes, threatening data privacy and security. Recently, the ARM architecture has come into the spotlight of cache side-channel attacks with its unprecedented growth in the market. We propose SmokeBomb, a novel cache side-channel mitigation that functions by explicitly ensuring a private space for each process to safely access sensitive data. The heart of the idea is to use the L1 cache of the CPU core as a private space by which SmokeBomb can give consistent results against cache attacks on the sensitive data, and thus, an attacker cannot distinguish specific data used by the victim. Our experimental results show that SmokeBomb can effectively prevent currently formalized cache attack methods.
{"title":"SmokeBomb","authors":"Haehyun Cho, Jinbum Park, Donguk Kim, Ziming Zhao, Yan Shoshitaishvili, Adam Doupé, Gail-Joon Ahn","doi":"10.1145/3386901.3388888","DOIUrl":"https://doi.org/10.1145/3386901.3388888","url":null,"abstract":"Cache side-channel attacks abuse microarchitectural designs meant to optimize memory access to infer information about victim processes, threatening data privacy and security. Recently, the ARM architecture has come into the spotlight of cache side-channel attacks with its unprecedented growth in the market. We propose SmokeBomb, a novel cache side-channel mitigation that functions by explicitly ensuring a private space for each process to safely access sensitive data. The heart of the idea is to use the L1 cache of the CPU core as a private space by which SmokeBomb can give consistent results against cache attacks on the sensitive data, and thus, an attacker cannot distinguish specific data used by the victim. Our experimental results show that SmokeBomb can effectively prevent currently formalized cache attack methods.","PeriodicalId":345029,"journal":{"name":"Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services","volume":"16 Suppl5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130198002","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}
As video calls and personal broadcasting become popular, the demand for mobile live streaming over cellular uplink channels is growing fast. However, current live streaming solutions are known to suffer from frequent uplink throughput fluctuations causing unnecessary video stalls and quality drops. As a remedy to this problem, we propose PERCEIVE, a deep learning-based uplink throughput prediction framework. PERCEIVE exploits a 2-stage LSTM (Long Short Term Memory) design and makes throughput predictions for the next 100ms. Our extensive evaluations show that PERCEIVE, trained with LTE network traces from three major operators in the U.S., achieves high accuracy in the uplink throughput prediction with only 7.67% mean absolute error and outperforms existing prediction techniques. We integrate PERCEIVE with WebRTC, a popular video streaming platform from Google, as a rate adaptation module. Our implementation on the Android phone demonstrates that it can improve PSNR by up to 6dB (4x) over the default WebRTC while providing less streaming latency.
{"title":"PERCEIVE","authors":"Jinsung Lee, Sungyong Lee, Jongyun Lee, Sandesh Dhawaskar Sathyanarayana, Hyoyoung Lim, Jihoon Lee, Xiaoqing Zhu, Sangeeta Ramakrishnan, D. Grunwald, Kyunghan Lee, Sangtae Ha","doi":"10.1145/3386901.3388911","DOIUrl":"https://doi.org/10.1145/3386901.3388911","url":null,"abstract":"As video calls and personal broadcasting become popular, the demand for mobile live streaming over cellular uplink channels is growing fast. However, current live streaming solutions are known to suffer from frequent uplink throughput fluctuations causing unnecessary video stalls and quality drops. As a remedy to this problem, we propose PERCEIVE, a deep learning-based uplink throughput prediction framework. PERCEIVE exploits a 2-stage LSTM (Long Short Term Memory) design and makes throughput predictions for the next 100ms. Our extensive evaluations show that PERCEIVE, trained with LTE network traces from three major operators in the U.S., achieves high accuracy in the uplink throughput prediction with only 7.67% mean absolute error and outperforms existing prediction techniques. We integrate PERCEIVE with WebRTC, a popular video streaming platform from Google, as a rate adaptation module. Our implementation on the Android phone demonstrates that it can improve PSNR by up to 6dB (4x) over the default WebRTC while providing less streaming latency.","PeriodicalId":345029,"journal":{"name":"Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123995744","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}
Akarsh Prabhakara, Vaibhav Singh, Swarun Kumar, Anthony G. Rowe
In this paper, we demonstrate Osprey, a tire wear sensor presented in [4]. Osprey makes use of commodity automotive, mmWave RADAR, places it in the tire well of automobiles to image the tire and then measures the tire wear. Osprey measures accurate tire wear continuously while being resilient to road debris and without embedding any electronics in tires. Osprey achieves this by building a super resolution algorithm based on Inverse Synthetic Aperture RADAR imaging and by embedding thin metallic strips along coded patterns in the grooves to combat debris. Here, we implement Osprey on a tire rotation rig and demonstrate the ability to measure tire wear (with and without debris) accurately and detect potentially harmful foreign objects.
{"title":"Osprey demo: a mmwave approach to tire wear sensing","authors":"Akarsh Prabhakara, Vaibhav Singh, Swarun Kumar, Anthony G. Rowe","doi":"10.1145/3386901.3396601","DOIUrl":"https://doi.org/10.1145/3386901.3396601","url":null,"abstract":"In this paper, we demonstrate Osprey, a tire wear sensor presented in [4]. Osprey makes use of commodity automotive, mmWave RADAR, places it in the tire well of automobiles to image the tire and then measures the tire wear. Osprey measures accurate tire wear continuously while being resilient to road debris and without embedding any electronics in tires. Osprey achieves this by building a super resolution algorithm based on Inverse Synthetic Aperture RADAR imaging and by embedding thin metallic strips along coded patterns in the grooves to combat debris. Here, we implement Osprey on a tire rotation rig and demonstrate the ability to measure tire wear (with and without debris) accurately and detect potentially harmful foreign objects.","PeriodicalId":345029,"journal":{"name":"Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115032894","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}
Artur Balanuta, Nuno Pereira, Swarun Kumar, Anthony G. Rowe
Conventional wireless communication systems are typically designed assuming a single transmitter-receiver pair for each link. In Low-Power Wide-Area Networks (LP-WANs), this one-to-one design paradigm is often overly pessimistic in terms of link budget because client packets are frequently detected by multiple gateways (i.e. one-to-many). Prior work has shown massive improvement in performance when specialized hardware is used to coherently combine signals at the physical layer. In this paper, we explore the potential of using multiple receivers at the MAC and link layer where these performance gains are often neglected. We present an approach called Opportunistic Packet Recovery (OPR) that targets the most likely corrupt bits across a set of packets that suffered failed CRCs at multiple LoRa LP-WAN base-stations. We see that bit errors are often disjoint across receivers, which aids in collaborative error detection. OPR leverages this to provide increasing gain in error recovery as a function of the number of receiving gateways. Since LP-WAN networks can easily offload packet processing to the cloud, there is ample compute time per packet (order of seconds) to search for bit permutations that would restore packet integrity. Link layer corrections have the advantage of being immediately applicable to the millions of already deployed LP-WAN systems without additional hardware or expensive RF front-ends. We experimentally demonstrate that OPR can correct up to 72% of packets that would normally have failed, when they are captured by multiple gateways.
{"title":"A cloud-optimized link layer for low-power wide-area networks","authors":"Artur Balanuta, Nuno Pereira, Swarun Kumar, Anthony G. Rowe","doi":"10.1145/3386901.3388915","DOIUrl":"https://doi.org/10.1145/3386901.3388915","url":null,"abstract":"Conventional wireless communication systems are typically designed assuming a single transmitter-receiver pair for each link. In Low-Power Wide-Area Networks (LP-WANs), this one-to-one design paradigm is often overly pessimistic in terms of link budget because client packets are frequently detected by multiple gateways (i.e. one-to-many). Prior work has shown massive improvement in performance when specialized hardware is used to coherently combine signals at the physical layer. In this paper, we explore the potential of using multiple receivers at the MAC and link layer where these performance gains are often neglected. We present an approach called Opportunistic Packet Recovery (OPR) that targets the most likely corrupt bits across a set of packets that suffered failed CRCs at multiple LoRa LP-WAN base-stations. We see that bit errors are often disjoint across receivers, which aids in collaborative error detection. OPR leverages this to provide increasing gain in error recovery as a function of the number of receiving gateways. Since LP-WAN networks can easily offload packet processing to the cloud, there is ample compute time per packet (order of seconds) to search for bit permutations that would restore packet integrity. Link layer corrections have the advantage of being immediately applicable to the millions of already deployed LP-WAN systems without additional hardware or expensive RF front-ends. We experimentally demonstrate that OPR can correct up to 72% of packets that would normally have failed, when they are captured by multiple gateways.","PeriodicalId":345029,"journal":{"name":"Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124175039","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：