In low-power wireless networking, new applications such as cooperative robots or industrial closed-loop control demand for network-wide consensus at low-latency and high reliability. Distributed consensus protocols is a mature field of research in a wired context, but has received little attention in low-power wireless settings. In this paper, we present A2: Agreement in the Air, a system that brings distributed consensus to low-power multi-hop networks. A2 introduces Synchrotron, a synchronous transmissions kernel that builds a robust mesh by exploiting the capture effect, frequency hopping with parallel channels, and link-layer security. A2 builds on top of this reliable base layer and enables the two- and three-phase commit protocols, as well as network services such as group membership, hopping sequence distribution and re-keying. We evaluate A2 on four public testbeds with different deployment densities and sizes. A2 requires only 475 ms to complete a two-phase commit over 180 nodes. The resulting duty cycle is 0.5% for 1-minute intervals. We show that A2 achieves zero losses end-to-end over long experiments, representing millions of data points. When adding controlled failures, we show that two-phase commit ensures transaction consistency in A2 while three-phase commit provides liveness at the expense of inconsistency under specific failure scenarios.
{"title":"Network-wide Consensus Utilizing the Capture Effect in Low-power Wireless Networks","authors":"Beshr Al Nahas, S. Duquennoy, O. Landsiedel","doi":"10.1145/3131672.3131685","DOIUrl":"https://doi.org/10.1145/3131672.3131685","url":null,"abstract":"In low-power wireless networking, new applications such as cooperative robots or industrial closed-loop control demand for network-wide consensus at low-latency and high reliability. Distributed consensus protocols is a mature field of research in a wired context, but has received little attention in low-power wireless settings. In this paper, we present A2: Agreement in the Air, a system that brings distributed consensus to low-power multi-hop networks. A2 introduces Synchrotron, a synchronous transmissions kernel that builds a robust mesh by exploiting the capture effect, frequency hopping with parallel channels, and link-layer security. A2 builds on top of this reliable base layer and enables the two- and three-phase commit protocols, as well as network services such as group membership, hopping sequence distribution and re-keying. We evaluate A2 on four public testbeds with different deployment densities and sizes. A2 requires only 475 ms to complete a two-phase commit over 180 nodes. The resulting duty cycle is 0.5% for 1-minute intervals. We show that A2 achieves zero losses end-to-end over long experiments, representing millions of data points. When adding controlled failures, we show that two-phase commit ensures transaction consistency in A2 while three-phase commit provides liveness at the expense of inconsistency under specific failure scenarios.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121351212","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. Amarasinghe, C. Suduwella, Charitha Elvitigala, Lasith Niroshan, Rangana Jayashanka Amaraweera, K. Gunawardana, Prabash Kumarasinghe, K. Zoysa, C. Keppetiyagama
Dengue is one of the deadly and fast spreading diseases in Sri Lanka. The female Aedes mosquito is the dengue vector and these mosquitoes breed in clear and non-flowing water. The Public Health Inspectors (PHIs) are tasked with detecting and eliminating such water collection areas. However, they face the problem of detecting potential breeding sites in hard-to-reach areas. With the technological development, the drones come as one of the most cost effective unmanned vehicles to access the places that a man cannot access. This paper presents a novel approach for identifying mosquito breeding areas via drone images through the distinct coloration of those areas by applying the Histogram of Oriented Gradients (HOG) algorithm. Using the HOG algorithm, we detect potential water retention areas using drone images.
登革热是斯里兰卡致命且传播迅速的疾病之一。雌伊蚊是登革热病媒，这些蚊子在清澈和不流动的水中繁殖。公共卫生检查员的任务是发现和消除这些集水区。然而，他们面临着在难以到达的地区发现潜在繁殖地点的问题。随着技术的发展，无人机成为最具成本效益的无人驾驶工具之一，可以进入人类无法进入的地方。本文提出了一种基于定向梯度直方图(Histogram of Oriented Gradients, HOG)算法，利用无人机图像中不同颜色的区域识别蚊虫孳生区域的新方法。使用HOG算法，我们使用无人机图像检测潜在的水潴留区域。
{"title":"A Machine Learning Approach for Identifying Mosquito Breeding Sites via Drone Images","authors":"A. Amarasinghe, C. Suduwella, Charitha Elvitigala, Lasith Niroshan, Rangana Jayashanka Amaraweera, K. Gunawardana, Prabash Kumarasinghe, K. Zoysa, C. Keppetiyagama","doi":"10.1145/3131672.3136986","DOIUrl":"https://doi.org/10.1145/3131672.3136986","url":null,"abstract":"Dengue is one of the deadly and fast spreading diseases in Sri Lanka. The female Aedes mosquito is the dengue vector and these mosquitoes breed in clear and non-flowing water. The Public Health Inspectors (PHIs) are tasked with detecting and eliminating such water collection areas. However, they face the problem of detecting potential breeding sites in hard-to-reach areas. With the technological development, the drones come as one of the most cost effective unmanned vehicles to access the places that a man cannot access. This paper presents a novel approach for identifying mosquito breeding areas via drone images through the distinct coloration of those areas by applying the Histogram of Oriented Gradients (HOG) algorithm. Using the HOG algorithm, we detect potential water retention areas using drone images.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123302221","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}
Through the investigation of the mathematical model of hologram-based indoor localization system using RFID, this paper reveals two potential deficiencies about accuracy and gives the machine learning interpretation of the model. Exploiting the methods from machine learning and the thought of hierarchy, the output accuracy and the efficiency of the model can be further boosted. Simulation and experiment show that the enhanced model can halve mean error and attain 9x execution speed improvement.
{"title":"Real-time and Nearly Ideal Hologram for RFID-based Indoor Localization","authors":"Haonan Chen, Dong Wang","doi":"10.1145/3131672.3136994","DOIUrl":"https://doi.org/10.1145/3131672.3136994","url":null,"abstract":"Through the investigation of the mathematical model of hologram-based indoor localization system using RFID, this paper reveals two potential deficiencies about accuracy and gives the machine learning interpretation of the model. Exploiting the methods from machine learning and the thought of hierarchy, the output accuracy and the efficiency of the model can be further boosted. Simulation and experiment show that the enhanced model can halve mean error and attain 9x execution speed improvement.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121512651","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}
Stationless bike sharing systems allow the bikes to be dropped off freely and to be found through GPS localization. Such flexibility has made it highly popular in an increasing number of cities. However, GPS often performs poorly in urban areas with dense high-rise building, making bikes search a challenging task. This paper proposes a novel cooperative GPS approach to address the problem. The method first organizes a group of shared bikes into a network, called a BikeNet, in a crowdsourcing manner. Then the constructed network maps all the nodes' GPS raw measurements to a lead node's view, to determine an accurate GPS location for each node. Experiment results show that BikeNet improves the localization accuracy by 2.96x and 4.8x, compared with the classic GPS method.
{"title":"Cooperative GPS Localization for Stationless Shared Bikes","authors":"Kongyang Chen, Guang Tan","doi":"10.1145/3131672.3136957","DOIUrl":"https://doi.org/10.1145/3131672.3136957","url":null,"abstract":"Stationless bike sharing systems allow the bikes to be dropped off freely and to be found through GPS localization. Such flexibility has made it highly popular in an increasing number of cities. However, GPS often performs poorly in urban areas with dense high-rise building, making bikes search a challenging task. This paper proposes a novel cooperative GPS approach to address the problem. The method first organizes a group of shared bikes into a network, called a BikeNet, in a crowdsourcing manner. Then the constructed network maps all the nodes' GPS raw measurements to a lead node's view, to determine an accurate GPS location for each node. Experiment results show that BikeNet improves the localization accuracy by 2.96x and 4.8x, compared with the classic GPS method.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122122520","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 protocols in low-power wireless networks require a leader to bootstrap and maintain their operation. For example, Chaos and Glossy networks need an initiator to synchronize and initiate the communication rounds. Commonly, these protocols use a fixed, compile-time defined node as the leader. In this work, we tackle the challenge of dynamically bootstrapping the network and electing a leader in low-power wireless scenarios.
{"title":"Network Bootstrapping and Leader Election Utilizing the Capture Effect in Low-power Wireless Networks","authors":"Beshr Al Nahas, S. Duquennoy, O. Landsiedel","doi":"10.1145/3131672.3137002","DOIUrl":"https://doi.org/10.1145/3131672.3137002","url":null,"abstract":"Many protocols in low-power wireless networks require a leader to bootstrap and maintain their operation. For example, Chaos and Glossy networks need an initiator to synchronize and initiate the communication rounds. Commonly, these protocols use a fixed, compile-time defined node as the leader. In this work, we tackle the challenge of dynamically bootstrapping the network and electing a leader in low-power wireless scenarios.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115093021","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}
L. Hanschke, C. Renner, Jannick Brockmann, Tobias Hamann, Jannes Peschel, Alexander Schell, Alexander Sowarka
The restricted energy budget of energy-harvesting sensor nodes demands algorithms for adaptive duty-cycling. However, their comparison and development is hindered by the lack of reproducibility of environmental conditions. We enable replaying recorded light conditions by building an affordable light box. Our self-developed control circuit and high power LEDs allow us to repeatedly replay real environmental illumination data through current and voltage traces. This allows us to directly compare the behavior of nodes running different energy-aware and -predictive algorithms.
{"title":"Light in the Box: Reproducible Lighting Conditions for Solar-Powered Sensor Nodes","authors":"L. Hanschke, C. Renner, Jannick Brockmann, Tobias Hamann, Jannes Peschel, Alexander Schell, Alexander Sowarka","doi":"10.1145/3131672.3136981","DOIUrl":"https://doi.org/10.1145/3131672.3136981","url":null,"abstract":"The restricted energy budget of energy-harvesting sensor nodes demands algorithms for adaptive duty-cycling. However, their comparison and development is hindered by the lack of reproducibility of environmental conditions. We enable replaying recorded light conditions by building an affordable light box. Our self-developed control circuit and high power LEDs allow us to repeatedly replay real environmental illumination data through current and voltage traces. This allows us to directly compare the behavior of nodes running different energy-aware and -predictive algorithms.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121403118","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}
Traffic congestion adversely impacts our lives. Traffic estimation resorting to mobile (crowdsensing) probes is a challenging task. We present key challenges for accurate and real-time traffic estimation resorting to crowdsensing data, namely data sparsity, user trip diversity, population bias, data quality, among others. We propose solutions to address some of these issues and demonstrate the relevance of others through an exploratory data analysis.
{"title":"On the Challenges of Mobile Crowdsensing for Traffic Estimation","authors":"D. S. Gil, P. D’orey, Ana Aguiar","doi":"10.1145/3131672.3136958","DOIUrl":"https://doi.org/10.1145/3131672.3136958","url":null,"abstract":"Traffic congestion adversely impacts our lives. Traffic estimation resorting to mobile (crowdsensing) probes is a challenging task. We present key challenges for accurate and real-time traffic estimation resorting to crowdsensing data, namely data sparsity, user trip diversity, population bias, data quality, among others. We propose solutions to address some of these issues and demonstrate the relevance of others through an exploratory data analysis.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126077477","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}
Xinyu Liu, Xiangxiang Xu, Xinlei Chen, Enhan Mai, H. Noh, Pei Zhang, Lin Zhang
Low-cost sensors are widely used to realize large-scale deployment for sensing systems. In this paper, we discuss challenges in using industrial-grade gas sensors for air quality monitoring. To overcome variation due to system errors, we present a framework for individualized calibration. Within the framework, multiple regression and interpolation methods are prepared for alternative optimization on fitting sensors' response to gas concentration.
{"title":"Individualized Calibration of Industrial-Grade Gas Sensors in Air Quality Sensing System","authors":"Xinyu Liu, Xiangxiang Xu, Xinlei Chen, Enhan Mai, H. Noh, Pei Zhang, Lin Zhang","doi":"10.1145/3131672.3136998","DOIUrl":"https://doi.org/10.1145/3131672.3136998","url":null,"abstract":"Low-cost sensors are widely used to realize large-scale deployment for sensing systems. In this paper, we discuss challenges in using industrial-grade gas sensors for air quality monitoring. To overcome variation due to system errors, we present a framework for individualized calibration. Within the framework, multiple regression and interpolation methods are prepared for alternative optimization on fitting sensors' response to gas concentration.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125124041","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}
L. Feeney, R. Hartung, C. Rohner, U. Kulau, L. Wolf, P. Gunningberg
We describe a testbed for studying battery discharge behavior and the lifetime of wireless devices under controlled temperature conditions and present preliminary measurement results.
{"title":"Towards realistic lifetime estimation in battery-powered IoT devices","authors":"L. Feeney, R. Hartung, C. Rohner, U. Kulau, L. Wolf, P. Gunningberg","doi":"10.1145/3131672.3136985","DOIUrl":"https://doi.org/10.1145/3131672.3136985","url":null,"abstract":"We describe a testbed for studying battery discharge behavior and the lifetime of wireless devices under controlled temperature conditions and present preliminary measurement results.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"230 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133588412","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}
Jason Koh, S. Sandha, Bharathan Balaji, Daniel Crawl, I. Altintas, Rajesh E. Gupta, M. Srivastava
Today large amount of data is generated by cities. Many of the datasets are openly available and are contributed by different sectors, government bodies and institutions. The new data can affect our understanding of the issues faced by cities and can support evidence based policies. However usage of data is limited due to difficulty in assimilating data from different sources. Open datasets often lack uniform structure which limits its analysis using traditional database systems. In this paper we present Citadel, a data hub for cities. Citadel's goal is to support end to end knowledge discovery cyber-infrastructure for effective analysis and policy support. Citadel is designed to ingest large amount of heterogeneous data and supports multiple use cases by encouraging data sharing in cities. Our poster presents the proposed features, architecture, implementation details and initial results.
{"title":"Data Hub Architecture for Smart Cities","authors":"Jason Koh, S. Sandha, Bharathan Balaji, Daniel Crawl, I. Altintas, Rajesh E. Gupta, M. Srivastava","doi":"10.1145/3131672.3137001","DOIUrl":"https://doi.org/10.1145/3131672.3137001","url":null,"abstract":"Today large amount of data is generated by cities. Many of the datasets are openly available and are contributed by different sectors, government bodies and institutions. The new data can affect our understanding of the issues faced by cities and can support evidence based policies. However usage of data is limited due to difficulty in assimilating data from different sources. Open datasets often lack uniform structure which limits its analysis using traditional database systems. In this paper we present Citadel, a data hub for cities. Citadel's goal is to support end to end knowledge discovery cyber-infrastructure for effective analysis and policy support. Citadel is designed to ingest large amount of heterogeneous data and supports multiple use cases by encouraging data sharing in cities. Our poster presents the proposed features, architecture, implementation details and initial results.","PeriodicalId":424262,"journal":{"name":"Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133781400","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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