Pub Date : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00017
Sirat Samyoun, M. A. S. Mondol, J. Stankovic
Stress increases the risk of several mental and physical health problems like anxiety, hypertension, and cardiovascular diseases. Better guidance and interventions towards mitigating the impact of stress can be provided if stress can be monitored continuously. The recent proliferation of wearable devices and their capability in measuring several physiological signals related to stress have created the opportunity to measure stress continuously in the wild. Wearable devices used to measure physiological signals are mostly placed on the wrist and the chest. Though currently chest sensors, with/without wrist sensors, provide better results in detecting stress than using wrist sensors only, chest devices are not as convenient and prevalent as wrist devices, particularly in the free-living context. In this paper, we present a solution to detect stress using wrist sensors that emulate the gold standard chest sensors. Data from wrist sensors are translated into the data from chest sensors, and the translated data is used for stress detection without requiring the users to wear any device on the chest. We evaluated our solution using a public dataset, and results show that our solution detects stress with accuracy comparable to the gold standard chest devices which are impractical for daily use.
{"title":"Stress Detection via Sensor Translation","authors":"Sirat Samyoun, M. A. S. Mondol, J. Stankovic","doi":"10.1109/DCOSS49796.2020.00017","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00017","url":null,"abstract":"Stress increases the risk of several mental and physical health problems like anxiety, hypertension, and cardiovascular diseases. Better guidance and interventions towards mitigating the impact of stress can be provided if stress can be monitored continuously. The recent proliferation of wearable devices and their capability in measuring several physiological signals related to stress have created the opportunity to measure stress continuously in the wild. Wearable devices used to measure physiological signals are mostly placed on the wrist and the chest. Though currently chest sensors, with/without wrist sensors, provide better results in detecting stress than using wrist sensors only, chest devices are not as convenient and prevalent as wrist devices, particularly in the free-living context. In this paper, we present a solution to detect stress using wrist sensors that emulate the gold standard chest sensors. Data from wrist sensors are translated into the data from chest sensors, and the translated data is used for stress detection without requiring the users to wear any device on the chest. We evaluated our solution using a public dataset, and results show that our solution detects stress with accuracy comparable to the gold standard chest devices which are impractical for daily use.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131079088","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}
Pub Date : 2020-05-01DOI: 10.1109/dcoss49796.2020.00083
{"title":"DCOSS 2020 Index","authors":"","doi":"10.1109/dcoss49796.2020.00083","DOIUrl":"https://doi.org/10.1109/dcoss49796.2020.00083","url":null,"abstract":"","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134009058","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}
Pub Date : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00078
D. Heeger, J. Plusquellic
Implementing a full set of security features within IoT devices is challenging because of constraints on the available resources and power consumption. Nevertheless, such devices must be capable of carrying out mutual authentication with gateways and servers before exchanging data. There are a wide variety of authentication methods that can be used including those based on physically unclonable functions (PUFs), PKI, encryption, and secure hash elements such as MD5 and SHA-3. This work assesses the time and energy associated with authentication protocols in the context of Long Range (LoRa), which is an emerging low-power wide-area network (LPWAN) technology used in IoT devices. LoRa has configurable settings that affect the bandwidth and transmission range. We assess the transmit time, which is proportional to energy consumption, of different authentication techniques over a variety of LoRa configurations and address the level of security provided by the authentication protocols. Our findings suggest that PUF-based authentication is well suited for RF devices operating within an energy and data rate constrained LoRa environment. We propose a PUF-based authentication protocol called PARCE that significantly reduces the RF transmissions for IoT devices.
{"title":"Analysis of IoT Authentication Over LoRa","authors":"D. Heeger, J. Plusquellic","doi":"10.1109/DCOSS49796.2020.00078","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00078","url":null,"abstract":"Implementing a full set of security features within IoT devices is challenging because of constraints on the available resources and power consumption. Nevertheless, such devices must be capable of carrying out mutual authentication with gateways and servers before exchanging data. There are a wide variety of authentication methods that can be used including those based on physically unclonable functions (PUFs), PKI, encryption, and secure hash elements such as MD5 and SHA-3. This work assesses the time and energy associated with authentication protocols in the context of Long Range (LoRa), which is an emerging low-power wide-area network (LPWAN) technology used in IoT devices. LoRa has configurable settings that affect the bandwidth and transmission range. We assess the transmit time, which is proportional to energy consumption, of different authentication techniques over a variety of LoRa configurations and address the level of security provided by the authentication protocols. Our findings suggest that PUF-based authentication is well suited for RF devices operating within an energy and data rate constrained LoRa environment. We propose a PUF-based authentication protocol called PARCE that significantly reduces the RF transmissions for IoT devices.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134475570","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}
Pub Date : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00067
Theofanis P. Raptis
Wireless power transfer technologies lead the way towards new paradigms for pervasive networking and have already penetrated the mobile and portable user device research and market. Their use is not only limited to charging devices like smartphones wirelessly by using a central wireless charger, but it is also extended to peer-to-peer (P2P) wireless crowd charging, when a user device shares energy directly with another user device. This paper surveys the literature over the period 20142020 on both P2P and central wireless crowd charging from the point of view of algorithmic applications as it applies to ubiquitously networked user devices and identifies some open research challenges for the future.
{"title":"Wireless Crowd Charging Applications: Taxonomy and Research Directions","authors":"Theofanis P. Raptis","doi":"10.1109/DCOSS49796.2020.00067","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00067","url":null,"abstract":"Wireless power transfer technologies lead the way towards new paradigms for pervasive networking and have already penetrated the mobile and portable user device research and market. Their use is not only limited to charging devices like smartphones wirelessly by using a central wireless charger, but it is also extended to peer-to-peer (P2P) wireless crowd charging, when a user device shares energy directly with another user device. This paper surveys the literature over the period 20142020 on both P2P and central wireless crowd charging from the point of view of algorithmic applications as it applies to ubiquitously networked user devices and identifies some open research challenges for the future.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130397881","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}
Pub Date : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00020
Md. Tahmid Rashid, Yang Zhang, D. Zhang, Dong Wang
Forest fires cause irreversible damages worldwide every year. Monitoring wildfire propagation is thus a vital task in mitigating forest fires. While computational model-based wildfire prediction methods provide reasonable accuracy in monitoring wildfire behavior, they are often limited due to the lack of constant availability of real-time meteorological data. In contrast, social-media-driven drone sensing (SDS) is emerging as a new sensing paradigm that detects the early signs of forest fires from online social media feeds and drives the drones for reliable sensing. However, due to the scarcity of social media data in remote regions and limited flight times of drones, SDS solutions often underperform in large-scale forest fires. In this paper, we present CompDrone, a wildfire monitoring framework that exploits the collective strengths of computational wildfire modeling and SDS for reliable wildfire monitoring. Two critical challenges exist to integrate computational modeling and SDS together: i) limited availability of social signals in the regions of a forest fire; and ii) predicting the regions of fire where the drones should be dispatched to. To solve the above challenges, the CompDrone framework leverages techniques from cellular automata, constrained optimization, and game theory. The evaluation results using a real-world wildfire dataset show that CompDrone outperforms the state-of-the-art schemes in effectively predicting wildfire propagation.
{"title":"CompDrone: Towards Integrated Computational Model and Social Drone Based Wildfire Monitoring","authors":"Md. Tahmid Rashid, Yang Zhang, D. Zhang, Dong Wang","doi":"10.1109/DCOSS49796.2020.00020","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00020","url":null,"abstract":"Forest fires cause irreversible damages worldwide every year. Monitoring wildfire propagation is thus a vital task in mitigating forest fires. While computational model-based wildfire prediction methods provide reasonable accuracy in monitoring wildfire behavior, they are often limited due to the lack of constant availability of real-time meteorological data. In contrast, social-media-driven drone sensing (SDS) is emerging as a new sensing paradigm that detects the early signs of forest fires from online social media feeds and drives the drones for reliable sensing. However, due to the scarcity of social media data in remote regions and limited flight times of drones, SDS solutions often underperform in large-scale forest fires. In this paper, we present CompDrone, a wildfire monitoring framework that exploits the collective strengths of computational wildfire modeling and SDS for reliable wildfire monitoring. Two critical challenges exist to integrate computational modeling and SDS together: i) limited availability of social signals in the regions of a forest fire; and ii) predicting the regions of fire where the drones should be dispatched to. To solve the above challenges, the CompDrone framework leverages techniques from cellular automata, constrained optimization, and game theory. The evaluation results using a real-world wildfire dataset show that CompDrone outperforms the state-of-the-art schemes in effectively predicting wildfire propagation.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128005323","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}
Pub Date : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00059
N. Balaji, Jyothsna Kilaru, Oscar Morales-Ponce
We present a synchronous robotic testbed called SyROF that allows fast implementation of robotic swarms. Our main goal is to lower the entry barriers to cooperative-robot systems for undergraduate and graduate students. The testbed provides a high-level programming environment that allows the implementation of Timed Input/Output Automata (TIOA). Sy-ROF offers the following unique characteristics: 1) a transparent mechanism to synchronize robot maneuvers, 2) a membership service with a failure detector, and 3) a transparent service to provide common knowledge in every round. These characteristics are fundamental to simplifying the implementation of robotic swarms. The software is organized in five layers: The lower layer consists of a real-time publish-subscribe system that allows efficient communication between tasks. The next layer is an implementation of a Kalman filter to estimate the position, orientation, and speed of the robot. The third layer consists of a synchronizer that synchronously executes the robot maneuvers, provides common knowledge to all the active participants, and handles failures. The fifth layer consists of the programming environment.
{"title":"Synchronous Robotic Framework","authors":"N. Balaji, Jyothsna Kilaru, Oscar Morales-Ponce","doi":"10.1109/DCOSS49796.2020.00059","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00059","url":null,"abstract":"We present a synchronous robotic testbed called SyROF that allows fast implementation of robotic swarms. Our main goal is to lower the entry barriers to cooperative-robot systems for undergraduate and graduate students. The testbed provides a high-level programming environment that allows the implementation of Timed Input/Output Automata (TIOA). Sy-ROF offers the following unique characteristics: 1) a transparent mechanism to synchronize robot maneuvers, 2) a membership service with a failure detector, and 3) a transparent service to provide common knowledge in every round. These characteristics are fundamental to simplifying the implementation of robotic swarms. The software is organized in five layers: The lower layer consists of a real-time publish-subscribe system that allows efficient communication between tasks. The next layer is an implementation of a Kalman filter to estimate the position, orientation, and speed of the robot. The third layer consists of a synchronizer that synchronously executes the robot maneuvers, provides common knowledge to all the active participants, and handles failures. The fifth layer consists of the programming environment.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"217 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117240412","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}
Pub Date : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00042
R. Meneguette
Software Defined Networks (SDNs) has become a promising network architecture in which it decouples the forwarding of messages with the controller, providing greater flexibility in managing the network, making it programmable. SDN can assist intelligent transport systems by providing a communication infrastructure in order to assist demand of service requests requested by users. In this work, we described about the concepts related to the infrastructures for intelligent transport systems using SDN based on vehicular networks. Finally, we discuss challenges.
{"title":"Software Defined Networks: Challenges for SDN as an Infrastructure for Intelligent Transport Systems based on Vehicular Networks","authors":"R. Meneguette","doi":"10.1109/DCOSS49796.2020.00042","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00042","url":null,"abstract":"Software Defined Networks (SDNs) has become a promising network architecture in which it decouples the forwarding of messages with the controller, providing greater flexibility in managing the network, making it programmable. SDN can assist intelligent transport systems by providing a communication infrastructure in order to assist demand of service requests requested by users. In this work, we described about the concepts related to the infrastructures for intelligent transport systems using SDN based on vehicular networks. Finally, we discuss challenges.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122973788","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}
Pub Date : 2020-05-01DOI: 10.1109/dcoss49796.2020.00009
{"title":"The Second International Workshop on Urban Computing (UrbCom) - Message from the Workshop Chairs","authors":"","doi":"10.1109/dcoss49796.2020.00009","DOIUrl":"https://doi.org/10.1109/dcoss49796.2020.00009","url":null,"abstract":"","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115548286","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}
Pub Date : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00026
Absar-Ul-Haque Ahmar, Emekcan Aras, T. D. Nguyen, Sam Michiels, W. Joosen, D. Hughes
Low power wide area networks (LPWANs) are being applied in many Internet of Things applications around the globe. These technologies offer economic coverage of wide areas, while retaining low power operation. LoRaWAN is a key technology in this space, with a world-wide presence and millions of devices deployed in the field. Despite this early success, recent research has shown that LoRa performs poorly in dense deployments with a high degree of contention. Furthermore, LoRa is not robust against selective jamming attacks. In this paper, we propose CRAM: a cryptographic frequency hopping MAC protocol designed for the LoRa physical layer that reduces contention by fairly exploiting all available frequency space, while making it significantly more difficult to perform selective jamming. Our evaluation shows that CRAM significantly reduces contention, thereby dramatically increasing scalability and reliability in comparison to the standard LoRa protocol.
{"title":"CRAM: Robust Medium Access Control for LPWAN using Cryptographic Frequency Hopping","authors":"Absar-Ul-Haque Ahmar, Emekcan Aras, T. D. Nguyen, Sam Michiels, W. Joosen, D. Hughes","doi":"10.1109/DCOSS49796.2020.00026","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00026","url":null,"abstract":"Low power wide area networks (LPWANs) are being applied in many Internet of Things applications around the globe. These technologies offer economic coverage of wide areas, while retaining low power operation. LoRaWAN is a key technology in this space, with a world-wide presence and millions of devices deployed in the field. Despite this early success, recent research has shown that LoRa performs poorly in dense deployments with a high degree of contention. Furthermore, LoRa is not robust against selective jamming attacks. In this paper, we propose CRAM: a cryptographic frequency hopping MAC protocol designed for the LoRa physical layer that reduces contention by fairly exploiting all available frequency space, while making it significantly more difficult to perform selective jamming. Our evaluation shows that CRAM significantly reduces contention, thereby dramatically increasing scalability and reliability in comparison to the standard LoRa protocol.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123056168","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}
Pub Date : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00056
Kelly Rael, G. Fragkos, J. Plusquellic, Eirini-Eleni Tsiropoulou
In this paper, an Unmanned Aerial Vehicles (UAVs) - enabled human Internet of Things (IoT) architecture is introduced to enable the rescue operations in public safety systems (PSSs). Initially, the first responders select in an autonomous manner the disaster area that they will support by considering the dynamic socio-physical changes of the surrounding environment and following a set of gradient ascent reinforcement learning algorithms. Then, the victims create coalitions among each other and the first responders at each disaster area based on the expected- maximization approach. Finally, the first responders select the UAVs that communicate with the Emergency Control Center (ECC), to which they will report the collected data from the disaster areas by adopting a set of log-linear reinforcement learning algorithms. The overall distributed UAV-enabled human Internet of Things architecture is evaluated via detailed numerical results that highlight its key operational features and the performance benefits of the proposed framework.
{"title":"UAV-enabled Human Internet of Things","authors":"Kelly Rael, G. Fragkos, J. Plusquellic, Eirini-Eleni Tsiropoulou","doi":"10.1109/DCOSS49796.2020.00056","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00056","url":null,"abstract":"In this paper, an Unmanned Aerial Vehicles (UAVs) - enabled human Internet of Things (IoT) architecture is introduced to enable the rescue operations in public safety systems (PSSs). Initially, the first responders select in an autonomous manner the disaster area that they will support by considering the dynamic socio-physical changes of the surrounding environment and following a set of gradient ascent reinforcement learning algorithms. Then, the victims create coalitions among each other and the first responders at each disaster area based on the expected- maximization approach. Finally, the first responders select the UAVs that communicate with the Emergency Control Center (ECC), to which they will report the collected data from the disaster areas by adopting a set of log-linear reinforcement learning algorithms. The overall distributed UAV-enabled human Internet of Things architecture is evaluated via detailed numerical results that highlight its key operational features and the performance benefits of the proposed framework.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123703011","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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