Pub Date : 2018-04-17DOI: 10.1109/IoTDI.2018.00019
Junghee Lee, Monobrata Debnath, A. Patki, Mostafa Hasan, C. Nicopoulos
Thanks to advances in semiconductor and communication technologies, a multitude of devices can be connected over a network. This widespread interconnectivity among disparate devices has ushered the era of Internet-of-Things (IoT). After IoT devices are developed and tested, they are integrated within a system and eventually deployed. Due to the complex nature of IoT systems, however, they may fail even after deployment. In a large-scale IoT system, an automatic diagnosis technique is imperative, because it may take too much time and effort to investigate a large number of devices. In this paper, a faulty device identification technique is proposed that is based on very lightweight processor-level architectural support. A hardware-based monitoring agent is incorporated within a processor, and connected to a separate monitoring program when an examination is required. By analyzing information collected by the agent, the monitoring program determines whether the device under monitoring is working correctly, or not. The experimental results demonstrate that the proposed technique can detect 92.66% of failures, with merely 1.55% false alarms.
{"title":"Hardware-Based Online Self-Diagnosis for Faulty Device Identification in Large-Scale IoT Systems","authors":"Junghee Lee, Monobrata Debnath, A. Patki, Mostafa Hasan, C. Nicopoulos","doi":"10.1109/IoTDI.2018.00019","DOIUrl":"https://doi.org/10.1109/IoTDI.2018.00019","url":null,"abstract":"Thanks to advances in semiconductor and communication technologies, a multitude of devices can be connected over a network. This widespread interconnectivity among disparate devices has ushered the era of Internet-of-Things (IoT). After IoT devices are developed and tested, they are integrated within a system and eventually deployed. Due to the complex nature of IoT systems, however, they may fail even after deployment. In a large-scale IoT system, an automatic diagnosis technique is imperative, because it may take too much time and effort to investigate a large number of devices. In this paper, a faulty device identification technique is proposed that is based on very lightweight processor-level architectural support. A hardware-based monitoring agent is incorporated within a processor, and connected to a separate monitoring program when an examination is required. By analyzing information collected by the agent, the monitoring program determines whether the device under monitoring is working correctly, or not. The experimental results demonstrate that the proposed technique can detect 92.66% of failures, with merely 1.55% false alarms.","PeriodicalId":149725,"journal":{"name":"2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121531689","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 : 2018-04-17DOI: 10.1109/IoTDI.2018.00049
Zhihe Zhao, Jiaheng Wang, Chenxu Fu, Dawei Liu, Bailiang Li
The research on the green roof is of great importance in the field of urban beautification and improving ecological effect. According to the previous research, plants have shown a significant impact on the absorption of PM2.5. Therefore, it is justified that the appropriate planting design or some particular combinations of plants can be considered as a solution, dealing with the urban fine particulate matter (PM2.5). This paper presented a work in progress on developing wireless sensor networks (WSN) system based on a prototype wind tunnel, which is used for the simulation of the green roof. Several data collection processes are handled by this system, where the concentration of PM2.5, wind speed, temperature & relative humidity are obtained and stored in the database simultaneously. Additionally, users are able to real-timely define their commands in details, controlling the sensor's height through a GUI on the website. Experimental and simulation results and measurements have verified the validity of the wind tunnel module as well as the reliability of the sensor network. The system can be operated on thousands of devices when the packet delay maintained in a low level.
{"title":"Demo Abstract: Smart City: A Real-Time Environmental Monitoring System on Green Roof","authors":"Zhihe Zhao, Jiaheng Wang, Chenxu Fu, Dawei Liu, Bailiang Li","doi":"10.1109/IoTDI.2018.00049","DOIUrl":"https://doi.org/10.1109/IoTDI.2018.00049","url":null,"abstract":"The research on the green roof is of great importance in the field of urban beautification and improving ecological effect. According to the previous research, plants have shown a significant impact on the absorption of PM2.5. Therefore, it is justified that the appropriate planting design or some particular combinations of plants can be considered as a solution, dealing with the urban fine particulate matter (PM2.5). This paper presented a work in progress on developing wireless sensor networks (WSN) system based on a prototype wind tunnel, which is used for the simulation of the green roof. Several data collection processes are handled by this system, where the concentration of PM2.5, wind speed, temperature & relative humidity are obtained and stored in the database simultaneously. Additionally, users are able to real-timely define their commands in details, controlling the sensor's height through a GUI on the website. Experimental and simulation results and measurements have verified the validity of the wind tunnel module as well as the reliability of the sensor network. The system can be operated on thousands of devices when the packet delay maintained in a low level.","PeriodicalId":149725,"journal":{"name":"2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126392226","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 : 2018-04-17DOI: 10.1109/IoTDI.2018.00045
Arman Pouraghily, Md. Nazmul Islam, S. Kundu, T. Wolf
Over past two decades, the idea of Internet of Things has been adopted widely as a solution to many societal problems in different areas. These areas include but are not limited to healthcare, transportation, environment, etc. Low cost overhead of Internet connectivity feature has been the main contributing factor in the widespread use of such devices in building different IoT solutions. The original stovepipe architecture of IoT systems limits the possibility of sharing the hardware infrastructure of IoT solutions and therefore is the main barrier against novel solutions. In recent year, however, there have been efforts to come up with solutions for sharing the hardware infrastructure and therefore pave the way for innovative solutions by amortizing the capital cost of setting up the hardware. In this work, we propose an architectural guideline for blockchain enabled IoT devices which facilitates sharing them between multiple blockchain ecosystems and at the same time, ensures the exclusive access to them seamlessly through blockchain smart contracts.
{"title":"Poster Abstract: Privacy in Blockchain-Enabled IoT Devices","authors":"Arman Pouraghily, Md. Nazmul Islam, S. Kundu, T. Wolf","doi":"10.1109/IoTDI.2018.00045","DOIUrl":"https://doi.org/10.1109/IoTDI.2018.00045","url":null,"abstract":"Over past two decades, the idea of Internet of Things has been adopted widely as a solution to many societal problems in different areas. These areas include but are not limited to healthcare, transportation, environment, etc. Low cost overhead of Internet connectivity feature has been the main contributing factor in the widespread use of such devices in building different IoT solutions. The original stovepipe architecture of IoT systems limits the possibility of sharing the hardware infrastructure of IoT solutions and therefore is the main barrier against novel solutions. In recent year, however, there have been efforts to come up with solutions for sharing the hardware infrastructure and therefore pave the way for innovative solutions by amortizing the capital cost of setting up the hardware. In this work, we propose an architectural guideline for blockchain enabled IoT devices which facilitates sharing them between multiple blockchain ecosystems and at the same time, ensures the exclusive access to them seamlessly through blockchain smart contracts.","PeriodicalId":149725,"journal":{"name":"2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125925052","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 : 2018-04-17DOI: 10.1109/IoTDI.2018.00021
James Hong, A. Levy, Laurynas Riliskis, P. Levis
The Internet of Things (IoT) is changing the way we interact with everyday objects. "Smart" devices will reduce energy use, keep our homes safe, and improve our health. However, as recent attacks have shown, these devices also create tremendous security vulnerabilities in our computing networks. Securing all of these devices is a daunting task. In this paper, we argue that IoT device communications should be default-off and desired network communications must be explicitly enabled. Unlike traditional networked applications or devices like a web browser or PC, IoT applications and devices serve narrowly defined purposes and do not require access to all services in the network. Our proposal, Bark, a policy language and runtime for specifying and enforcing minimal access permissions in IoT networks, exploits this fact. Bark phrases access control policies in terms of natural questions (who, what, where, when, and how) and transforms them into transparently enforceable rules for IoT application protocols. Bark can express detailed rules such as "Let the lights see the luminosity of the bedroom sensor at any time" and "Let a device at my front door, if I approve it, unlock my smart lock for 30 seconds" in a way that is presentable and explainable to users. We implement Bark for Wi-Fi/IP and Bluetooth Low Energy (BLE) networks and evaluate its efficacy on several example applications and attacks.
{"title":"Don't Talk Unless I Say So! Securing the Internet of Things with Default-Off Networking","authors":"James Hong, A. Levy, Laurynas Riliskis, P. Levis","doi":"10.1109/IoTDI.2018.00021","DOIUrl":"https://doi.org/10.1109/IoTDI.2018.00021","url":null,"abstract":"The Internet of Things (IoT) is changing the way we interact with everyday objects. \"Smart\" devices will reduce energy use, keep our homes safe, and improve our health. However, as recent attacks have shown, these devices also create tremendous security vulnerabilities in our computing networks. Securing all of these devices is a daunting task. In this paper, we argue that IoT device communications should be default-off and desired network communications must be explicitly enabled. Unlike traditional networked applications or devices like a web browser or PC, IoT applications and devices serve narrowly defined purposes and do not require access to all services in the network. Our proposal, Bark, a policy language and runtime for specifying and enforcing minimal access permissions in IoT networks, exploits this fact. Bark phrases access control policies in terms of natural questions (who, what, where, when, and how) and transforms them into transparently enforceable rules for IoT application protocols. Bark can express detailed rules such as \"Let the lights see the luminosity of the bedroom sensor at any time\" and \"Let a device at my front door, if I approve it, unlock my smart lock for 30 seconds\" in a way that is presentable and explainable to users. We implement Bark for Wi-Fi/IP and Bluetooth Low Energy (BLE) networks and evaluate its efficacy on several example applications and attacks.","PeriodicalId":149725,"journal":{"name":"2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126017826","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 : 2018-04-17DOI: 10.1109/IoTDI.2018.00028
Dong Ma, Guohao Lan, Weitao Xu, Mahbub Hassan, Wen Hu
Piezoelectric energy harvesting (PEH), which converts ambient motion, stress, and vibrations into usable electricity, may help combat battery issues in a growing number of industrial and wearable Internet of things (IoTs). Recently, many works have convincingly demonstrated that PEH can also act as a self-powered sensor for detecting a wide range of machine and human contexts. These developments suggest that the same PEH hardware could be potentially used for simultaneous energy harvesting and sensing (SEHS), offering a new design space for low cost and low power IoT devices. Unfortunately, realization of SEHS is challenging as the energy harvesting process distorts the sensing signal. To achieve high quality sensing from PEH, the state-of-the-art uses separate PEHs for sensing and energy harvesting, which increases system complexity, form factor, and cost. In this paper, we propose a novel SEHS architecture, which combines energy harvesting and sensing in the same piece of PEH, and minimizes distortion in the sensing signal by applying a special filtering algorithm. We prototype the SEHS concept in the form factor of a shoe, and evaluate its energy harvesting as well as sensing performance with 20 subjects using gait recognition as a case study. We demonstrate that the SEHS prototype harvests up to 127% more energy and detects human gait with 8% higher accuracy while consuming 35% less power compared to the state-of-the-art.
{"title":"SEHS: Simultaneous Energy Harvesting and Sensing Using Piezoelectric Energy Harvester","authors":"Dong Ma, Guohao Lan, Weitao Xu, Mahbub Hassan, Wen Hu","doi":"10.1109/IoTDI.2018.00028","DOIUrl":"https://doi.org/10.1109/IoTDI.2018.00028","url":null,"abstract":"Piezoelectric energy harvesting (PEH), which converts ambient motion, stress, and vibrations into usable electricity, may help combat battery issues in a growing number of industrial and wearable Internet of things (IoTs). Recently, many works have convincingly demonstrated that PEH can also act as a self-powered sensor for detecting a wide range of machine and human contexts. These developments suggest that the same PEH hardware could be potentially used for simultaneous energy harvesting and sensing (SEHS), offering a new design space for low cost and low power IoT devices. Unfortunately, realization of SEHS is challenging as the energy harvesting process distorts the sensing signal. To achieve high quality sensing from PEH, the state-of-the-art uses separate PEHs for sensing and energy harvesting, which increases system complexity, form factor, and cost. In this paper, we propose a novel SEHS architecture, which combines energy harvesting and sensing in the same piece of PEH, and minimizes distortion in the sensing signal by applying a special filtering algorithm. We prototype the SEHS concept in the form factor of a shoe, and evaluate its energy harvesting as well as sensing performance with 20 subjects using gait recognition as a case study. We demonstrate that the SEHS prototype harvests up to 127% more energy and detects human gait with 8% higher accuracy while consuming 35% less power compared to the state-of-the-art.","PeriodicalId":149725,"journal":{"name":"2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133888032","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 : 2018-04-01DOI: 10.1109/IoTDI.2018.00039
Woochul Kang, Daeyeon Kim
Recently, deep learning is emerging as a state-of-the-art approach in delivering robust and highly accurate inference in many domains, including Internet-of-Things (IoT). Deep learning is already changing the way computers embedded in IoT devices to make intelligent decisions using sensor feeds in the real world. There have been significant efforts to develop light-weight and highly efficient deep learning inference mechanisms for resource-constrained mobile and IoT devices. Some approaches propose a hardware-based accelerator, and some approaches propose to reduce the amount of computation of deep learning models using various model compression techniques. Even though these efforts have demonstrated significant gains in performance and efficiency, they are not aware of the Quality-of-Service (QoS) requirements of various IoT applications, and, hence manifest unpredictable 'best-effort' performance in terms of inference latency, power consumption, resource usage, etc. In IoT devices with temporal constraints, such unpredictability might result in undesirable effects such as compromising safety. In this work, we present a novel deep learning inference runtime called, DeepRT. Unlike previous inference accelerators, DeepRT focuses on supporting predictable inference performance both temporally and spatially.
{"title":"Poster Abstract: DeepRT: A Predictable Deep Learning Inference Framework for IoT Devices","authors":"Woochul Kang, Daeyeon Kim","doi":"10.1109/IoTDI.2018.00039","DOIUrl":"https://doi.org/10.1109/IoTDI.2018.00039","url":null,"abstract":"Recently, deep learning is emerging as a state-of-the-art approach in delivering robust and highly accurate inference in many domains, including Internet-of-Things (IoT). Deep learning is already changing the way computers embedded in IoT devices to make intelligent decisions using sensor feeds in the real world. There have been significant efforts to develop light-weight and highly efficient deep learning inference mechanisms for resource-constrained mobile and IoT devices. Some approaches propose a hardware-based accelerator, and some approaches propose to reduce the amount of computation of deep learning models using various model compression techniques. Even though these efforts have demonstrated significant gains in performance and efficiency, they are not aware of the Quality-of-Service (QoS) requirements of various IoT applications, and, hence manifest unpredictable 'best-effort' performance in terms of inference latency, power consumption, resource usage, etc. In IoT devices with temporal constraints, such unpredictability might result in undesirable effects such as compromising safety. In this work, we present a novel deep learning inference runtime called, DeepRT. Unlike previous inference accelerators, DeepRT focuses on supporting predictable inference performance both temporally and spatially.","PeriodicalId":149725,"journal":{"name":"2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114465545","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 : 2018-04-01DOI: 10.1109/IoTDI.2018.00046
A. Jakaria, M. Rahman
The recent trend of collaborative operations of a network of Unmanned Aerial Vehicles (UAVs) to achieve a common objective has attracted the researchers, as well as commercial vendors. It has revolutionized the means of data collection to maximize mission performances. However, the collaborative UAVs need to be safe from cyberattacks to prevent catastrophe. They need to be able to collaborate with each other to avoid potential failure of a mission. As these smart devices are always targets of adversaries, they need to maintain safe communication with each other while avoiding fuel outage and mid-air collisions, as well as reducing the possibilities of being hacked. In this work, we present the idea of a formal verification tool that takes different UAV parameters, safety requirements, and resource constraints as input and verifies the network's safety.
{"title":"Poster Abstract: Safety Analysis for UAV Networks","authors":"A. Jakaria, M. Rahman","doi":"10.1109/IoTDI.2018.00046","DOIUrl":"https://doi.org/10.1109/IoTDI.2018.00046","url":null,"abstract":"The recent trend of collaborative operations of a network of Unmanned Aerial Vehicles (UAVs) to achieve a common objective has attracted the researchers, as well as commercial vendors. It has revolutionized the means of data collection to maximize mission performances. However, the collaborative UAVs need to be safe from cyberattacks to prevent catastrophe. They need to be able to collaborate with each other to avoid potential failure of a mission. As these smart devices are always targets of adversaries, they need to maintain safe communication with each other while avoiding fuel outage and mid-air collisions, as well as reducing the possibilities of being hacked. In this work, we present the idea of a formal verification tool that takes different UAV parameters, safety requirements, and resource constraints as input and verifies the network's safety.","PeriodicalId":149725,"journal":{"name":"2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134589357","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 : 2018-04-01DOI: 10.1109/IoTDI.2018.00054
Mahbubur Rahman, Dali Ismail, Abusayeed Saifullah
SNOW (Sensor Network Over White Spaces) has evolved as an enabling technology for Internet-of-Things (IoT) applications. To meet the future IoT demands, multiple SNOW networks will require to interact with each other, and thus demanding a scalable seamless integration between them. In this demonstration, we showcase seamless concurrent peer-to-peer (P2P) communications between multiple SNOW networks.
{"title":"Demo Abstract: Enabling Inter-SNOW Concurrent P2P Communications","authors":"Mahbubur Rahman, Dali Ismail, Abusayeed Saifullah","doi":"10.1109/IoTDI.2018.00054","DOIUrl":"https://doi.org/10.1109/IoTDI.2018.00054","url":null,"abstract":"SNOW (Sensor Network Over White Spaces) has evolved as an enabling technology for Internet-of-Things (IoT) applications. To meet the future IoT demands, multiple SNOW networks will require to interact with each other, and thus demanding a scalable seamless integration between them. In this demonstration, we showcase seamless concurrent peer-to-peer (P2P) communications between multiple SNOW networks.","PeriodicalId":149725,"journal":{"name":"2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116872029","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 : 2018-04-01DOI: 10.1109/IoTDI.2018.00037
Jayson G. Boubin, Shiqi Zhang, Venkata Mandadapu, Christopher Stewart
Unmanned aerial vehicles (UAV) enable novel but demanding computational workloads that exceed processing capacity of their onboard resources. Mobile and edge devices can support demanding workloads, but they increase network communication and power usage. These resource constraints block potentially transformative UAV applications that execute too slowly or use too much power. This poster presents early efforts to characterize computational demands of emerging UAV applications. We are building a selfie-drone benchmark. Our benchmark will capture processing metrics, e.g., CPU usage, cache misses, power usage, etc. It will also enable characterization across a wide range of local and edge setups. Our benchmark uses a micro services design, making it easy to move workload execution across multiple contexts. Early results show that our benchmark functions well, i.e., accurately detects faces and safely uses flight controls. Further, edge devices matter. A smart phone uses 4X less power than a laptop when executing our benchmark.
{"title":"Poster Abstract: Characterizing Computational Workloads in UAV Applications","authors":"Jayson G. Boubin, Shiqi Zhang, Venkata Mandadapu, Christopher Stewart","doi":"10.1109/IoTDI.2018.00037","DOIUrl":"https://doi.org/10.1109/IoTDI.2018.00037","url":null,"abstract":"Unmanned aerial vehicles (UAV) enable novel but demanding computational workloads that exceed processing capacity of their onboard resources. Mobile and edge devices can support demanding workloads, but they increase network communication and power usage. These resource constraints block potentially transformative UAV applications that execute too slowly or use too much power. This poster presents early efforts to characterize computational demands of emerging UAV applications. We are building a selfie-drone benchmark. Our benchmark will capture processing metrics, e.g., CPU usage, cache misses, power usage, etc. It will also enable characterization across a wide range of local and edge setups. Our benchmark uses a micro services design, making it easy to move workload execution across multiple contexts. Early results show that our benchmark functions well, i.e., accurately detects faces and safely uses flight controls. Further, edge devices matter. A smart phone uses 4X less power than a laptop when executing our benchmark.","PeriodicalId":149725,"journal":{"name":"2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"287 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113993838","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 : 2018-04-01DOI: 10.1109/IoTDI.2018.00048
Md. Golam Moula Mehedi Hasan, Amarjit Datta, M. Rahman
The rise of Autonomous Vehicles (AVs) indicates that AVs are soon going to be the juggernaut in car industry. The state-of-the-art technology used by the AVs makes ride-sharing a prominent and flexible way for transportation. In this case, the customers (i.e., who are sharing the AV) and the AV all should come into the picture to verify each other. However, When a user requests for a ride share or rent, the responding AV/IoT device does not have the sufficient capability to store, process, or verify each other. In the existing security solutions, every AV/IoT device typically needs to rely on a trusted third party, which invokes another trust issue. If the trusted third party is rogue or loses credibility, the whole system will collapse. This research aims at exploiting Blockchain to provide a secure and reliable way to communicate among devices with trusts. We implement our proposed Blockchain-based solution and demonstrate the solution on a synthetic case study.
{"title":"Poster Abstract: Chained of Things: A Secure and Dependable Design of Autonomous Vehicle Services","authors":"Md. Golam Moula Mehedi Hasan, Amarjit Datta, M. Rahman","doi":"10.1109/IoTDI.2018.00048","DOIUrl":"https://doi.org/10.1109/IoTDI.2018.00048","url":null,"abstract":"The rise of Autonomous Vehicles (AVs) indicates that AVs are soon going to be the juggernaut in car industry. The state-of-the-art technology used by the AVs makes ride-sharing a prominent and flexible way for transportation. In this case, the customers (i.e., who are sharing the AV) and the AV all should come into the picture to verify each other. However, When a user requests for a ride share or rent, the responding AV/IoT device does not have the sufficient capability to store, process, or verify each other. In the existing security solutions, every AV/IoT device typically needs to rely on a trusted third party, which invokes another trust issue. If the trusted third party is rogue or loses credibility, the whole system will collapse. This research aims at exploiting Blockchain to provide a secure and reliable way to communicate among devices with trusts. We implement our proposed Blockchain-based solution and demonstrate the solution on a synthetic case study.","PeriodicalId":149725,"journal":{"name":"2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131107546","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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