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检索条件"任意字段=IEEE International Conference on Distributed Computing in Sensor Systems"

共 30758 条记录，以下是391-400 订阅

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A Comparison of On-Mote Lossy Compression Algorithms for Wireless Seismic Data Acquisition

A Comparison of On-Mote Lossy Compression Algorithms for Wir...

引用

9th ieee international conference on distributed computing in sensor systems (DCOSS)

作者： Rubin, Marc J. Wakin, Michael B. Camp, Tracy Colorado Sch Mines Dept Elect Engn & Comp Sci Golden CO 80401 USA

ISBN: (纸本)9781479946181

In this article, we rigorously compare compressive sampling (CS) to four state of the art, on-mote, lossy compression algorithms (K-run-length encoding (KRLE), lightweight temporal compression (LTC), wavelet quantization thresholding and run-length encoding (WQTR), and a low-pass filtered fast Fourier transform (FFT)). Specifically, we first simulate lossy compression on two real-world seismic data sets, and we then evaluate algorithm performance using implementations on real hardware. In terms of compression rates, recovered signal error, power consumption, and classification accuracy of a seismic event detection task (on decompressed signals), results show that CS performs comparable to (and in many cases better than) the other algorithms evaluated. The main benefit to users is that CS, a lightweight and non-adaptive compression technique, can guarantee a desired level of compression performance (and thus, radio usage and power consumption) without subjugating recovered signal quality. Our contribution is a novel and rigorous comparison of five state of the art, on-mote, lossy compression algorithms in simulation on real-world data sets and implemented on hardware.

关键词： compressive sampling compressive sensing lossy compression seismic wireless sensor networks lossy compression Compressed sensing Earthquakes Wireless sensor networks state of the art seismic data acquisition Dataset compression ratio

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ReFrAEN: a Reconfigurable Vibration Analysis Framework for Constrained sensor Nodes 17

ReFrAEN: a Reconfigurable Vibration Analysis Framework for C...

引用

17th Annual ieee international conference on distributed computing in sensor systems (ieee DCOSS)

作者： Thangarajan, Ashok Samraj Yang, Fan Joosen, Wouter Michiels, Sam Hughes, Danny Katholieke Univ Leuven Imec DistriNet Leuven Belgium

ISBN: (纸本)9781665439299

Vibration monitoring uses data gathered from accelerometers to study kinetic phenomena in applications such as: structural health monitoring and predictive maintenance. The Internet of Things (IoT) has the potential to greatly expand the range and scope of vibration monitoring applications by delivering long-life wireless sensors that can be cost-effectively embedded in hard to reach places such as;within machines, infrastructure or the built environment. However, achieving this vision is difficult due to the stringent resource constraints of contemporary IoT devices and networks. This has led the research community to develop a creative range of application-specific near-sensor processing firmware. However, systematic support for generic vibration monitoring on resource-poor IoT networks remains an open problem. We tackle this challenge by introducing ReFrAEN, a software framework that efficiently enables a wide range of vibration monitoring applications on IoT networks. ReFrAEN achieves this through a deeply configurable combination of compression techniques and data processing algorithms. These features allow end-users to effectively trade-off between resource consumption and data resolution in order to meet battery life constraints while preserving sufficient data quality to support the target application. Our evaluation shows that ReFrAEN is capable of identifying bearing faults, while dramatically improving battery lifetime and reducing latency in comparison to prior approaches.

关键词： IoT Near sensor Processing Vibration Monitoring

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A Fast and Fault-Tolerant distributed Algorithm for Near-Optimal TDMA Scheduling in WSNs

A Fast and Fault-Tolerant Distributed Algorithm for Near-Opt...

引用

9th ieee international conference on distributed computing in sensor systems (DCOSS)

作者： Bhatia, Ashutosh Hansdah, R. C. Indian Inst Sci Dept Comp Sci & Automat Bangalore 560012 Karnataka India

ISBN: (纸本)9781479946181

The time division multiple access (TDMA) based channel access mechanisms perform better than the contention based channel access mechanisms, in terms of channel utilization, reliability and power consumption, specially for high data rate applications in wireless sensor networks (WSNs). Most of the existing distributed TDMA scheduling techniques can be classified as either static or dynamic. The primary purpose of static TDMA scheduling algorithms is to improve the channel utilization by generating a schedule of smaller length. But, they usually take longer time to schedule, and hence, are not suitable for WSNs, in which the network topology changes dynamically. On the other hand, dynamic TDMA scheduling algorithms generate a schedule quickly, but they are not efficient in terms of generated schedule length. In this paper, we propose a novel scheme for TDMA scheduling in WSNs, which can generate a compact schedule similar to static scheduling algorithms, while its runtime performance can be matched with those of dynamic scheduling algorithms. Furthermore, the proposed distributed TDMA scheduling algorithm has the capability to trade-off schedule length with the time required to generate the schedule. This would allow the developers of WSNs, to tune the performance, as per the requirement of prevalent WSN applications, and the requirement to perform re-scheduling. Finally, the proposed TDMA scheduling is fault-tolerant to packet loss due to erroneous wireless channel. The algorithm has been simulated using the Castalia simulator to compare its performance with those of others in terms of generated schedule length and the time required to generate the TDMA schedule. Simulation results show that the proposed algorithm generates a compact schedule in a very less time.

关键词： Wireless sensor Networks Media Access Control TDMA scheduling

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Information-driven sensor Selection for Energy-Efficient Human Motion Tracking

Information-driven Sensor Selection for Energy-Efficient Hum...

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9th ieee international conference on distributed computing in sensor systems (DCoSS)

作者： Tham, Chen-Khong Han, Mingding Natl Univ Singapore Dept Elect & Comp Engn Singapore 117548 Singapore

ISBN: (纸本)9780769550411

In this paper, we address the issue of human motion tracking in a smart space using a wireless sensor network with a small number of ultrasonic sensors. Ultrasonic sensing is preferable in situations where video monitoring is prohibited due to privacy concerns or is ruled out due to its higher cost and energy consumption. Unlike other common tracking techniques, the schemes proposed in this paper do not require the tracked person to wear a tag. In order to conserve energy, a single ultrasonic sensor that provides maximum information gain is selected. We use the Extended Kalman Filter (EKF) which provides robust state estimates from noisy signals as well as an uncertainty measure in the form of the state covariance, and propose the use of a process model which copes better with missed detections compared to the commonly used constant velocity process model. We propose two sensor selection schemes: (i) Current Node sensor Selection (CNSS), and (ii) distributed Neighbourhood node sensor Election (DNSE), and evaluate their performance in terms of tracking accuracy, target detection ratio and sensor network lifetime.

关键词： Kalman filters nonlinear filters object detection target tracking ultrasonic equipment wireless sensor networks

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Overlapped Mobile Charging for sensor Networks 40

Overlapped Mobile Charging for Sensor Networks

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40th ieee international conference on distributed computing systems (ICDCS)

作者： Zhang, Sheng Liang, Yu Qian, Zhuzhong Xiao, Mingjun Ge, Jidong Wu, Jie Lu, Sanglu Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China Univ Sci & Technol China Sch Comp Sci & Technol Suzhou Inst Adv Study Hefei Peoples R China Temple Univ Dept Comp & Informat Sci Philadelphia PA 19122 USA

ISBN: (纸本)9781728170022

In this paper, we consider a fundamental problem: given one mobile charger that can charge multiple sensor nodes simultaneously, how we can schedule it to charge a given WSN to maximize the energy usage effectiveness (EUE)? We propose a novel charging paradigm Overlapped Mobile Charging (OMC) the first of its kind to the best of our knowledge. Firstly, OMC clusters sensor nodes into multiple non-overlapped sets using k-means evaluated by the Davies-Bouldin Index, such that the sensor nodes in each set have similar recharging cycles. Secondly, for each set of sensor nodes, OMC further divides them into multiple overlapped groups, and charges each group at different locations for different time durations to make sure that each overlapped sensor node just receives its required energy from multiple charging locations.

关键词： sensor nodes

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Resilient distributed Diffusion for Multi-task Estimation 14

Resilient Distributed Diffusion for Multi-task Estimation

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14th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Li, Jiani Koutsoukos, Xenofon Vanderbilt Univ Inst Software Integrated Syst 221 Kirkland Hall Nashville TN 37235 USA

ISBN: (纸本)9781538654705

distributed diffusion is a powerful algorithm for multi-task state estimation which enables networked agents to interact with neighbors to process input data and diffuse information across the network. Compared to a centralized approach, diffusion offers multiple advantages that include robustness to node and link failures. In this paper, we consider distributed diffusion for multi-task estimation where networked agents must estimate distinct but correlated states of interest by processing streaming data. By exploiting the adaptive weights used for diffusing information, we develop attack models that drive normal agents to converge to states selected by the attacker. The attack models can be used for both stationary and non-stationary state estimation. In addition, we develop a resilient distributed diffusion algorithm under the assumption that the number of compromised nodes in the neighborhood of each normal node is bounded by F and we show that resilience may be obtained at the cost of performance degradation. Finally, we evaluate the proposed attack models and resilient distributed diffusion algorithm using stationary and non-stationary multi-target localization.

关键词： Estimation Resilience Integrated circuits distributed databases Adaptation models Degradation Task analysis

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Data Selection for Maximum Coverage in sensor Networks with Cost Constraints

Data Selection for Maximum Coverage in Sensor Networks with ...

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9th ieee international conference on distributed computing in sensor systems (DCOSS)

作者： Rager, Scott T. Ciftcioglu, Ertugrul N. La Porta, Thomas F. Leung, Alice Dron, William Ramanathan, Ram Hancock, John Penn State Univ University Pk PA 16802 USA Raytheon BBN Technol Cambridge MA 02138 USA Artistech Inc Fairfax VA 22030 USA

ISBN: (纸本)9781479946181

In many deployments of wireless sensor networks (WSNs), the primary goal is to collect and deliver data from many nodes to a data sink. This goal must be met while considering limited resources, such as battery life, in the wireless nodes. In this work, we propose considering the content of generated data to make intelligent data and node selection decisions. We formally present the problem of maximizing coverage of this collected data while restricting individual node costs to remain within a given budget and provide an algorithm that provides the optimal solution. Next we consider the related problem of finding the optimal long-term average coverage subject to average cost constraints and give its solution, which uses Lyapunov Optimization techniques. For real world implementations, we also provide computationally feasible approximation algorithms of both problems along with proven bounds on their performance, including a novel technique that uses virtual queues for the average maximum coverage problem. Finally, we provide simulation results of all proposed algorithms. These results not only demonstrate the benefits of considering data content in scheduling, but also show the advantages from using the long-term average solution and the near-optimal performance of our greedy virtual queue approximation algorithm.

关键词： Approximation algorithms

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Synthetic Traffic Signs Dataset for Traffic Sign Detection & Recognition In distributed Smart systems 17

Synthetic Traffic Signs Dataset for Traffic Sign Detection &...

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17th Annual ieee international conference on distributed computing in sensor systems (ieee DCOSS)

作者： Siniosoglou, Ilias Sarigiannidis, Panagiotis Spyridis, Yannis Khadka, Anish Efstathopoulos, Georgios Lagkas, Thomas Univ Western Macedonia Dept Elect & Comp Engn Kozani Greece 0 Infin Ltd London England Int Hellen Univ Dept Comp Sci Kavala Campus Kavala Greece

ISBN: (纸本)9781665439299

Traffic sign recognition (TSR) is a key aspect involved in the development of robust automated transportation systems. It inherently involves the task of traffic sign detection (TSD), which can be challenging due to traffic signs often being subject to deterioration or occlusion, caused by various environmental factors, or through actions of vandalism. Even though, notable advancements have been achieved in the areas of TSR and TSD, few studies have provided robust algorithms, able to be generalized in real-world applications. This mostly stems from the lack of an extensive traffic sign dataset, standardized for benchmarking purposes. In light of the aforementioned, this paper presents a novel traffic sign dataset, which consists of the Carla Traffic Sign Detection (CTSD), and the Carla Traffic Sign Recognition Dataset (CATERED), targeting the detection and recognition processes respectively. Using the proposed dataset for training and evaluation, a deep Auto-Encoder algorithm is presented, demonstrating high accuracy in detecting and recognizing the distorted traffic signs. Finally, the system is further extended to a federated learning environment, exemplifying its applicability in modern decentralized and interconnected architectures.

关键词： Traffic Sign Recognition Traffic Sign Detection Autoencoder Federated Learning Image synthesis Image classification Anomaly Detection

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Pattern Regulator: Protecting Temporal Usage Privacy for Wireless Body Area sensor Networks

Pattern Regulator: Protecting Temporal Usage Privacy for Wir...

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33rd ieee international conference on distributed computing systems (ICDCS)

作者： Yao, Lan Li, Xiangyang Yu, Ge Northeastern Univ Shenyang 110819 Peoples R China IIT Chicago IL 60616 USA

ISBN: (纸本)9781479932474;9780769550237

In a wireless body area sensor network (WBAN), biosensors are implanted or worn on an individual to acquire medical data for a clinical diagnosis or physical monitoring. Traditionally, authentication and cryptography techniques are used to achieve the data confidentiality and privacy of a WBAN system. However, for WBAN systems, besides data itself, the pattern of data transmission may leak critical information about the user. For example, various medical sensors deliver data in different patterns and these patterns leak many critical facts, e. g., what sensors are used (which implies diseases the individual may have), and how frequent the sensor is sampling (which implies how urgent some abnormal observation is about a patient). In this work, to address this challenge, we design a regulator, which packs real data session into a type-independent transmission model at transmission layer. All valid data packets are equably sent at the frequency defined by the regulator and at the same length to clutter the inherent pace of valid data transmission and other parameters. We also propose a strategy PAS to minimize the overhead while preventing attackers from locating the patients. Our extensive experiments validate our regulator and PAS design.

关键词： body area networks body sensor networks clutter cryptography data communication

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(POSTER) SmartTwins: Secure and Auditable DLT-based Digital Twins for the WoT 18

(POSTER) SmartTwins: Secure and Auditable DLT-based Digital ...

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18th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Pittaras, Iakovos Polyzos, George C. Athens Univ Econ & Business Sch Informat Sci & Technol Dept Informat Mobile Multimedia Lab Athens Greece

ISBN: (纸本)9781665495127

Digital Twins and the Internet of Things (IoT) are two of the most prominent recent concepts and technologies. The IoT supports many applications that merge the physical with the cyber world. This highlights the need for improved security. Here, we argue that digital twins can help in securing and strengthening the IoT by using them for interacting with the actual IoT devices. While most digital twins implementations are centralized, we propose to integrate distributed Ledger Technologies (DLTs) and digital twins into the IoT to realize decentralized, secure, available, flexible, and auditable blockchain-based IoT services for IoT devices that follow the W3C Web of Things (WoT) standards. In this work, we present the design of SmartTwin, a blockchain-based digital twin framework for which we provide two different implementations using two different blockchains, we present the design trade-offs, and we discuss future research and development directions.

关键词： Digital Twins distributed Ledger Technologies Internet of Things Sensing Actuation Blockchain Ethereum Hyperledger Fabric Auditability Availability

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