Ivonne Andrea Mantilla Gonzalez, Florian Meyer, V. Turau
In the Industrial Internet of Things (i.e., IIoT), the standardization of open technologies and protocols has achieved seamless data exchange between machines and other physical systems from different manufacturers. At the MAC sublayer, the industry-standard protocols IEEE 802.15.4 Time Slot Channel Hopping (TSCH) and Deterministic and Synchronous Multi-channel Extension (DSME) show promising properties for high adaptability and dynamically changing traffic. However, performance comparison between these MAC protocols rarely has gone beyond a simulation phase. This work presents the results of such a comparison on physically deployed networks using the facilities of the FIT-IoTLab. The evaluation includes fully implementing an IIoT protocol stack based on MQTT in Contiki-NG. It comprises the integration of DSME as part of Contiki-NG’s software stack through OpenDSME, the only publicly available implementation of DSME. Results show that both protocols suit IIoT applications, particularly for data collection. The comparison between TSCH and DSME also includes an evaluation of distributed schedulers for both MAC modes and one autonomous scheduler for TSCH within a UDP protocol stack.
{"title":"A Comprehensive Performance Comparison of IEEE 802.15.4 DSME and TSCH in a Realistic IoT Scenario for Industrial Applications","authors":"Ivonne Andrea Mantilla Gonzalez, Florian Meyer, V. Turau","doi":"10.1145/3595188","DOIUrl":"https://doi.org/10.1145/3595188","url":null,"abstract":"In the Industrial Internet of Things (i.e., IIoT), the standardization of open technologies and protocols has achieved seamless data exchange between machines and other physical systems from different manufacturers. At the MAC sublayer, the industry-standard protocols IEEE 802.15.4 Time Slot Channel Hopping (TSCH) and Deterministic and Synchronous Multi-channel Extension (DSME) show promising properties for high adaptability and dynamically changing traffic. However, performance comparison between these MAC protocols rarely has gone beyond a simulation phase. This work presents the results of such a comparison on physically deployed networks using the facilities of the FIT-IoTLab. The evaluation includes fully implementing an IIoT protocol stack based on MQTT in Contiki-NG. It comprises the integration of DSME as part of Contiki-NG’s software stack through OpenDSME, the only publicly available implementation of DSME. Results show that both protocols suit IIoT applications, particularly for data collection. The comparison between TSCH and DSME also includes an evaluation of distributed schedulers for both MAC modes and one autonomous scheduler for TSCH within a UDP protocol stack.","PeriodicalId":29764,"journal":{"name":"ACM Transactions on Internet of Things","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85202341","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}
Bo-yan Zhang, Boyu Jiang, Rong Zheng, Xiaoping Zhang, Jun Yu Li, Q. Xu
Continuous monitoring of human vital signs using non-contact mmWave radars is attractive due to their ability to penetrate garments and operate under different lighting conditions. Unfortunately, most prior research requires subjects to stay at a fixed distance from radar sensors and to remain still during monitoring. These restrictions limit the applications of radar vital sign monitoring in real life scenarios. In this article, we address these limitations and present Pi-ViMo, a non-contact Physiology-inspired Robust Vital Sign Monitoring system, using mmWave radars. We first derive a multi-scattering point model for the human body, and introduce a coherent combining of multiple scatterings to enhance the quality of estimated chest-wall movements. It enables vital sign estimations of subjects at any location in a radar’s field of view (FoV). We then propose a template matching method to extract human vital signs by adopting physical models of respiration and cardiac activities. The proposed method is capable to separate respiration and heartbeat in the presence of micro-level random body movements (RBM) when a subject is at any location within the field of view of a radar. Experiments in a radar testbed show average respiration rate errors of 6% and heart rate errors of 11.9% for the stationary subjects, and average errors of 13.5% for respiration rate and 13.6% for heart rate for subjects under different RBMs.
{"title":"Pi-ViMo: Physiology-inspired Robust Vital Sign Monitoring using mmWave Radars","authors":"Bo-yan Zhang, Boyu Jiang, Rong Zheng, Xiaoping Zhang, Jun Yu Li, Q. Xu","doi":"10.1145/3589347","DOIUrl":"https://doi.org/10.1145/3589347","url":null,"abstract":"Continuous monitoring of human vital signs using non-contact mmWave radars is attractive due to their ability to penetrate garments and operate under different lighting conditions. Unfortunately, most prior research requires subjects to stay at a fixed distance from radar sensors and to remain still during monitoring. These restrictions limit the applications of radar vital sign monitoring in real life scenarios. In this article, we address these limitations and present Pi-ViMo, a non-contact Physiology-inspired Robust Vital Sign Monitoring system, using mmWave radars. We first derive a multi-scattering point model for the human body, and introduce a coherent combining of multiple scatterings to enhance the quality of estimated chest-wall movements. It enables vital sign estimations of subjects at any location in a radar’s field of view (FoV). We then propose a template matching method to extract human vital signs by adopting physical models of respiration and cardiac activities. The proposed method is capable to separate respiration and heartbeat in the presence of micro-level random body movements (RBM) when a subject is at any location within the field of view of a radar. Experiments in a radar testbed show average respiration rate errors of 6% and heart rate errors of 11.9% for the stationary subjects, and average errors of 13.5% for respiration rate and 13.6% for heart rate for subjects under different RBMs.","PeriodicalId":29764,"journal":{"name":"ACM Transactions on Internet of Things","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89614177","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}
With the widespread use of Internet of Things (IoT) devices and the arrival of the 5G era, edge computing has become an attractive paradigm to serve end-users and provide better QoS. Many efforts have been paid to provision some merging public network services at the network edge. We reveal that it is very common that specific users call for private and isolated edge services to preserve data privacy and enable other security intentions. However, it still remains open to fulfill such kind of mixed requests in edge computing. In this article, we propose a cooperative edge computing framework, i.e., HyEdge, to offer both public and private edge services systematically. To fully exploit the benefits of this novel framework, we define the problem of optimal request scheduling over a given placement solution of hybrid edge servers to minimize the response delay. This problem is further modeled as a mixed integer non-linear programming problem (MINLP), which is typically NP-hard. Accordingly, we propose the partition-based optimization method, which can efficiently solve this NP-hard problem via the problem decomposition and the branch and bound strategies. We finally conduct extensive evaluations with a real-world dataset to measure the performance of our method. The results indicate that the proposed method achieves elegant performance with low computation complexity.
{"title":"HyEdge: A Cooperative Edge Computing Framework for Provisioning Private and Public Services","authors":"Siyuan Gu, Deke Guo, Guoming Tang, Lailong Luo, Yuchen Sun, Xueshan Luo","doi":"10.1145/3585078","DOIUrl":"https://doi.org/10.1145/3585078","url":null,"abstract":"With the widespread use of Internet of Things (IoT) devices and the arrival of the 5G era, edge computing has become an attractive paradigm to serve end-users and provide better QoS. Many efforts have been paid to provision some merging public network services at the network edge. We reveal that it is very common that specific users call for private and isolated edge services to preserve data privacy and enable other security intentions. However, it still remains open to fulfill such kind of mixed requests in edge computing. In this article, we propose a cooperative edge computing framework, i.e., HyEdge, to offer both public and private edge services systematically. To fully exploit the benefits of this novel framework, we define the problem of optimal request scheduling over a given placement solution of hybrid edge servers to minimize the response delay. This problem is further modeled as a mixed integer non-linear programming problem (MINLP), which is typically NP-hard. Accordingly, we propose the partition-based optimization method, which can efficiently solve this NP-hard problem via the problem decomposition and the branch and bound strategies. We finally conduct extensive evaluations with a real-world dataset to measure the performance of our method. The results indicate that the proposed method achieves elegant performance with low computation complexity.","PeriodicalId":29764,"journal":{"name":"ACM Transactions on Internet of Things","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76548224","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}
Over the past decade, IoT has gained huge momentum in terms of technological exploration, integration, and its various applications even after having a resource-bound architecture. It is challenging to run any high-end security protocol(s) on Edge devices. These devices are highly vulnerable toward numerous cyber-attacks. IoT network nodes need peer-to-peer security, which is possible if there exists proper mutual authentication among network devices. A secure session key needs to be established among source and destination nodes before sending the sensitive data. To generate these session keys, a strong cryptosystem is required to share parameters securely over a wireless network. In this article, we utilize a Rubik's cube puzzle-based cryptosystem to exchange parameters among peers and generate session key(s). Blockchain technology is incorporated in the proposed model to provide anonymity of token transactions, on the basis of which the network devices exchange services. A session key pool randomizer is used to avoid network probabilistic attacks. Our hybrid model is capable of generating secure session keys that can be used for mutual authentication and reliable data transferring tasks. Cyber-attacks resistance and performance results were verified using standard tools, which gave industry level promising results in terms of efficiency, light weightiness, and practical applications.
{"title":"A Rubik's Cube Cryptosystem-based Authentication and Session Key Generation Model Driven in Blockchain Environment for IoT Security","authors":"Ankit Attkan, V. Ranga, Priyanka Ahlawat","doi":"10.1145/3586578","DOIUrl":"https://doi.org/10.1145/3586578","url":null,"abstract":"Over the past decade, IoT has gained huge momentum in terms of technological exploration, integration, and its various applications even after having a resource-bound architecture. It is challenging to run any high-end security protocol(s) on Edge devices. These devices are highly vulnerable toward numerous cyber-attacks. IoT network nodes need peer-to-peer security, which is possible if there exists proper mutual authentication among network devices. A secure session key needs to be established among source and destination nodes before sending the sensitive data. To generate these session keys, a strong cryptosystem is required to share parameters securely over a wireless network. In this article, we utilize a Rubik's cube puzzle-based cryptosystem to exchange parameters among peers and generate session key(s). Blockchain technology is incorporated in the proposed model to provide anonymity of token transactions, on the basis of which the network devices exchange services. A session key pool randomizer is used to avoid network probabilistic attacks. Our hybrid model is capable of generating secure session keys that can be used for mutual authentication and reliable data transferring tasks. Cyber-attacks resistance and performance results were verified using standard tools, which gave industry level promising results in terms of efficiency, light weightiness, and practical applications.","PeriodicalId":29764,"journal":{"name":"ACM Transactions on Internet of Things","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73622741","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}
This article deals with an artificial intelligence (AI) framework to support Internet-of-everything (IoE) applications over sixth-generation wireless (6G) networks. An integrated IoE-Edge Intelligence ecosystem is designed to effectively face the problems of Virtual Machines (VMs) placement based on their popularity, computation offloading optimization, and system reliability improvement predicting compute nodes faults. The main objective of the article is to increase performance in terms of minimization of worst end-to-end (e2e) delay, percentage of requests in outage, and the enhancement of reliability. The article focuses on the following main issues: (i) proposal of a channel-aware federated learning (FL) approach to forecast the popularity of the VMs required by IoE devices; (ii) use of an AI-based channel conditions forecasting module at the benefits of the FL process; (iii) development of a suitable VMs placement on the basis of their popularity and of an efficient tasks allocation technique based on a modified version of the auction theory (AT) and a proper matching game; (iv) enhancement of the system reliability by an echo-state-network (ESN), located on each computation node and running in the background to predict failures and anticipate tasks migration. Numerical results validate the effectiveness of the proposed strategy for IoE applications over 6G networks.
{"title":"A Channel-aware FL Approach for Virtual Machine Placement in 6G Edge Intelligent Ecosystems","authors":"Benedetta Picano, R. Fantacci","doi":"10.1145/3584705","DOIUrl":"https://doi.org/10.1145/3584705","url":null,"abstract":"This article deals with an artificial intelligence (AI) framework to support Internet-of-everything (IoE) applications over sixth-generation wireless (6G) networks. An integrated IoE-Edge Intelligence ecosystem is designed to effectively face the problems of Virtual Machines (VMs) placement based on their popularity, computation offloading optimization, and system reliability improvement predicting compute nodes faults. The main objective of the article is to increase performance in terms of minimization of worst end-to-end (e2e) delay, percentage of requests in outage, and the enhancement of reliability. The article focuses on the following main issues: (i) proposal of a channel-aware federated learning (FL) approach to forecast the popularity of the VMs required by IoE devices; (ii) use of an AI-based channel conditions forecasting module at the benefits of the FL process; (iii) development of a suitable VMs placement on the basis of their popularity and of an efficient tasks allocation technique based on a modified version of the auction theory (AT) and a proper matching game; (iv) enhancement of the system reliability by an echo-state-network (ESN), located on each computation node and running in the background to predict failures and anticipate tasks migration. Numerical results validate the effectiveness of the proposed strategy for IoE applications over 6G networks.","PeriodicalId":29764,"journal":{"name":"ACM Transactions on Internet of Things","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80955899","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}
Adeola Bannis, Shijia Pan, Carlos Ruiz, John Shen, Hae Young Noh, Pei Zhang
IoT (Internet of Things) devices, such as network-enabled wearables, are carried by increasingly more people throughout daily life. Information from multiple devices can be aggregated to gain insights into a person’s behavior or status. For example, an elderly care facility could monitor patients for falls by combining fitness bracelet data with video of the entire class. For this aggregated data to be useful to each person, we need a multi-modality association of the devices’ physical ID (i.e., location, the user holding it, visual appearance) with a virtual ID (e.g., IP address/available services). Existing approaches for multi-modality association often require intentional interaction or direct line-of-sight to the device, which is infeasible for a large number of users or when the device is obscured by clothing. We present IDIoT, a calibration-free passive sensing approach that fuses motion sensor information with camera footage of an area to estimate the body location of motion sensors carried by a user. We characterize results across three baselines to highlight how different fusing methodology results better than earlier IMU-vision fusion algorithms. From this characterization, we determine IDIoT is more robust to errors such as missing frames or miscalibration that frequently occur in IMU-vision matching systems.
物联网(Internet of Things)设备，如支持网络的可穿戴设备，越来越多的人在日常生活中携带。来自多个设备的信息可以聚合起来，以了解一个人的行为或状态。例如，一家老年护理机构可以通过将健身手环数据与整个课程的视频相结合来监测患者的跌倒情况。为了使这些聚合数据对每个人都有用，我们需要将设备的物理ID(例如，位置，持有它的用户，视觉外观)与虚拟ID(例如，IP地址/可用服务)进行多模态关联。现有的多模态关联方法通常需要有意的交互或设备的直接视线，这对于大量用户或设备被衣服遮挡时是不可行的。我们提出了一种无需校准的被动传感方法IDIoT，它将运动传感器信息与一个区域的摄像机镜头融合在一起，以估计用户携带的运动传感器的身体位置。我们描述了三个基线的结果，以突出不同的融合方法如何比早期的imu -视觉融合算法效果更好。根据这一特性，我们确定IDIoT对imu -视觉匹配系统中经常出现的缺失帧或校准错误等错误具有更强的鲁棒性。
{"title":"IDIoT: Multimodal Framework for Ubiquitous Identification and Assignment of Human-carried Wearable Devices","authors":"Adeola Bannis, Shijia Pan, Carlos Ruiz, John Shen, Hae Young Noh, Pei Zhang","doi":"10.1145/3579832","DOIUrl":"https://doi.org/10.1145/3579832","url":null,"abstract":"IoT (Internet of Things) devices, such as network-enabled wearables, are carried by increasingly more people throughout daily life. Information from multiple devices can be aggregated to gain insights into a person’s behavior or status. For example, an elderly care facility could monitor patients for falls by combining fitness bracelet data with video of the entire class. For this aggregated data to be useful to each person, we need a multi-modality association of the devices’ physical ID (i.e., location, the user holding it, visual appearance) with a virtual ID (e.g., IP address/available services). Existing approaches for multi-modality association often require intentional interaction or direct line-of-sight to the device, which is infeasible for a large number of users or when the device is obscured by clothing. We present IDIoT, a calibration-free passive sensing approach that fuses motion sensor information with camera footage of an area to estimate the body location of motion sensors carried by a user. We characterize results across three baselines to highlight how different fusing methodology results better than earlier IMU-vision fusion algorithms. From this characterization, we determine IDIoT is more robust to errors such as missing frames or miscalibration that frequently occur in IMU-vision matching systems.","PeriodicalId":29764,"journal":{"name":"ACM Transactions on Internet of Things","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81888394","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}
Roman Trüb, Reto Da Forno, Andreas Biri, J. Beutel, L. Thiele
In many real-world wireless IoT networks, the application dictates the location of the nodes and therefore the link characteristics are inhomogeneous. Furthermore, nodes may in many scenarios only communicate with the Internet-attached gateway via multiple hops. If an energy-efficient short-range modulation scheme is used, nodes that are reachable only via high-path-loss links cannot communicate. Using a more energy-demanding long-range modulation allows connecting more nodes but would be inefficient for nodes that are easily reachable via low-path-loss links. Combining multiple modulations is challenging, as low-power radios usually only support the use of a single modulation at a time. In this article, we present the Long-Short-Range (LSR) protocol which supports low-power multi-hop communication using multiple modulations and is suited for networks with inhomogeneous link characteristics. To reduce the inherent redundancy of long-range modulations, we present a method to determine the connectivity graph of the network during regular data communication without adding significant overhead. In simulations, we show that LSR allows for reducing power consumption significantly for many scenarios when compared to a state-of-the-art multi-hop communication protocol using a single long-range modulation. We demonstrate the applicability of LSR with an implementation on real hardware and a testbed with long-range links.
{"title":"LSR: Energy-Efficient Multi-Modulation Communication for Inhomogeneous Wireless IoT Networks","authors":"Roman Trüb, Reto Da Forno, Andreas Biri, J. Beutel, L. Thiele","doi":"10.1145/3579366","DOIUrl":"https://doi.org/10.1145/3579366","url":null,"abstract":"In many real-world wireless IoT networks, the application dictates the location of the nodes and therefore the link characteristics are inhomogeneous. Furthermore, nodes may in many scenarios only communicate with the Internet-attached gateway via multiple hops. If an energy-efficient short-range modulation scheme is used, nodes that are reachable only via high-path-loss links cannot communicate. Using a more energy-demanding long-range modulation allows connecting more nodes but would be inefficient for nodes that are easily reachable via low-path-loss links. Combining multiple modulations is challenging, as low-power radios usually only support the use of a single modulation at a time. In this article, we present the Long-Short-Range (LSR) protocol which supports low-power multi-hop communication using multiple modulations and is suited for networks with inhomogeneous link characteristics. To reduce the inherent redundancy of long-range modulations, we present a method to determine the connectivity graph of the network during regular data communication without adding significant overhead. In simulations, we show that LSR allows for reducing power consumption significantly for many scenarios when compared to a state-of-the-art multi-hop communication protocol using a single long-range modulation. We demonstrate the applicability of LSR with an implementation on real hardware and a testbed with long-range links.","PeriodicalId":29764,"journal":{"name":"ACM Transactions on Internet of Things","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2023-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82699432","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}
Farooq Dar, M. Liyanage, Marko Radeta, Zhigang Yin, Agustin Zuniga, Sokol Kosta, S. Tarkoma, P. Nurmi, Huber Flores
Underwater environments are emerging as a new frontier for data science thanks to an increase in deployments of underwater sensor technology. Challenges in operating computing underwater combined with a lack of high-speed communication technology covering most aquatic areas means that there is a significant delay between the collection and analysis of data. This in turn limits the scale and complexity of the applications that can operate based on these data. In this article, we develop underwater fog computing support using low-cost micro-clouds and demonstrate how they can be used to deliver cost-effective support for data-heavy underwater applications. We develop a proof-of-concept micro-cloud prototype and use it to perform extensive benchmarks that evaluate the suitability of underwater micro-clouds for diverse underwater data science scenarios. We conduct rigorous tests in both controlled and field deployments, using river and sea waters. We also address technical challenges in enabling underwater fogs, evaluating the performance of different communication interfaces and demonstrating how accelerometers can be used to detect the likelihood of communication failures and determine which communication interface to use. Our work offers a cost-effective way to increase the scale and complexity of underwater data science applications, and demonstrates how off-the-shelf devices can be adopted for this purpose.
{"title":"Upscaling Fog Computing in Oceans for Underwater Pervasive Data Science Using Low-Cost Micro-Clouds","authors":"Farooq Dar, M. Liyanage, Marko Radeta, Zhigang Yin, Agustin Zuniga, Sokol Kosta, S. Tarkoma, P. Nurmi, Huber Flores","doi":"10.1145/3575801","DOIUrl":"https://doi.org/10.1145/3575801","url":null,"abstract":"Underwater environments are emerging as a new frontier for data science thanks to an increase in deployments of underwater sensor technology. Challenges in operating computing underwater combined with a lack of high-speed communication technology covering most aquatic areas means that there is a significant delay between the collection and analysis of data. This in turn limits the scale and complexity of the applications that can operate based on these data. In this article, we develop underwater fog computing support using low-cost micro-clouds and demonstrate how they can be used to deliver cost-effective support for data-heavy underwater applications. We develop a proof-of-concept micro-cloud prototype and use it to perform extensive benchmarks that evaluate the suitability of underwater micro-clouds for diverse underwater data science scenarios. We conduct rigorous tests in both controlled and field deployments, using river and sea waters. We also address technical challenges in enabling underwater fogs, evaluating the performance of different communication interfaces and demonstrating how accelerometers can be used to detect the likelihood of communication failures and determine which communication interface to use. Our work offers a cost-effective way to increase the scale and complexity of underwater data science applications, and demonstrates how off-the-shelf devices can be adopted for this purpose.","PeriodicalId":29764,"journal":{"name":"ACM Transactions on Internet of Things","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89231177","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}
IoT systems based on Digital Twins (DTs) — virtual copies of physical objects and systems — can be very effective to enable data-driven services and promote better control and decisions, in particular by exploiting distributed approaches where cloud and edge computing cooperate effectively. In this context, digital twins deployed on the edge represents a new strategic element to design a new wave of distributed cyber-physical applications. Existing approaches are generally focused on fragmented and domain-specific monolithic solutions and are mainly associated to model-driven, simulative or descriptive visions. The idea of extending the DTs role to support last-mile digitalization and interoperability through a set of general purpose and well-defined properties and capabilities is still underinvestigated. In this paper, we present the novel Edge Digital Twins (EDT) architectural model and its implementation, enabling the lightweight replication of physical devices providing an efficient digital abstraction layer to support the autonomous and standard collaboration of things and services. We model the core capabilities with respect to the recent definition of the state of the art, present the software architecture and a prototype implementation. Extensive experimental analysis shows the obtained performance in multiple IoT application contexts and compares them with that of state-of-the-art approaches.
{"title":"A Flexible and Modular Architecture for Edge Digital Twin: Implementation and Evaluation","authors":"Marco Picone, M. Mamei, F. Zambonelli","doi":"10.1145/3573206","DOIUrl":"https://doi.org/10.1145/3573206","url":null,"abstract":"IoT systems based on Digital Twins (DTs) — virtual copies of physical objects and systems — can be very effective to enable data-driven services and promote better control and decisions, in particular by exploiting distributed approaches where cloud and edge computing cooperate effectively. In this context, digital twins deployed on the edge represents a new strategic element to design a new wave of distributed cyber-physical applications. Existing approaches are generally focused on fragmented and domain-specific monolithic solutions and are mainly associated to model-driven, simulative or descriptive visions. The idea of extending the DTs role to support last-mile digitalization and interoperability through a set of general purpose and well-defined properties and capabilities is still underinvestigated. In this paper, we present the novel Edge Digital Twins (EDT) architectural model and its implementation, enabling the lightweight replication of physical devices providing an efficient digital abstraction layer to support the autonomous and standard collaboration of things and services. We model the core capabilities with respect to the recent definition of the state of the art, present the software architecture and a prototype implementation. Extensive experimental analysis shows the obtained performance in multiple IoT application contexts and compares them with that of state-of-the-art approaches.","PeriodicalId":29764,"journal":{"name":"ACM Transactions on Internet of Things","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79084546","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}
Klervie Toczé, Ali J. Fahs, G. Pierre, S. Nadjm-Tehrani
Deciding where to handle services and tasks, as well as provisioning an adequate amount of computing resources for this handling, is a main challenge of edge computing systems. Moreover, latency-sensitive services constrain the type and location of edge devices that can provide the needed resources. When available resources are scarce there is a possibility that some resource allocation requests are denied. In this work, we propose the VioLinn system to tackle the joint problems of task placement, service placement, and edge device provisioning. Dealing with latency-sensitive services is achieved through proximity-aware algorithms that ensure the tasks are handled close to the end-user. Moreover, the concept of spare edge device is introduced to handle sudden load variations in time and space without having to continuously overprovision. Several spare device selection algorithms are proposed with different cost/performance tradeoffs. Evaluations are performed both in a Kubernetes-based testbed and using simulations and show the benefit of using spare devices for handling localized load spikes with higher quality of service (QoS) and lower computing resource usage. The study of the different algorithms shows that it is possible to achieve this increase in QoS with different tradeoffs against cost and performance.
{"title":"VioLinn: Proximity-aware Edge Placementwith Dynamic and Elastic Resource Provisioning","authors":"Klervie Toczé, Ali J. Fahs, G. Pierre, S. Nadjm-Tehrani","doi":"10.1145/3573125","DOIUrl":"https://doi.org/10.1145/3573125","url":null,"abstract":"Deciding where to handle services and tasks, as well as provisioning an adequate amount of computing resources for this handling, is a main challenge of edge computing systems. Moreover, latency-sensitive services constrain the type and location of edge devices that can provide the needed resources. When available resources are scarce there is a possibility that some resource allocation requests are denied. In this work, we propose the VioLinn system to tackle the joint problems of task placement, service placement, and edge device provisioning. Dealing with latency-sensitive services is achieved through proximity-aware algorithms that ensure the tasks are handled close to the end-user. Moreover, the concept of spare edge device is introduced to handle sudden load variations in time and space without having to continuously overprovision. Several spare device selection algorithms are proposed with different cost/performance tradeoffs. Evaluations are performed both in a Kubernetes-based testbed and using simulations and show the benefit of using spare devices for handling localized load spikes with higher quality of service (QoS) and lower computing resource usage. The study of the different algorithms shows that it is possible to achieve this increase in QoS with different tradeoffs against cost and performance.","PeriodicalId":29764,"journal":{"name":"ACM Transactions on Internet of Things","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83501019","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：