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

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Evaluating Worksharing Tasks on distributed Environments 22

Evaluating Worksharing Tasks on Distributed Environments

引用

ieee international conference on Cluster computing

作者： Maronas, Marcos Teruel, Xavier Bull, J. Mark Ayguade, Eduard Beltran, Vicenc Barcelona Supercomp Ctr BSC Barcelona Spain Univ Edinburgh EPCC Edinburgh Midlothian Scotland Univ Politecn Catalunya UPC Barcelona Spain

ISBN: (纸本)9781728166773

Hybrid programming is a promising approach to exploit clusters of multicore systems. Our focus is on the combination of MPI and tasking. This hybrid approach combines the low-latency and high throughput of MPI with the flexibility of tasking models and their inherent ability to handle load imbalance. However, combining tasking with standard MPI implementations can be a challenge. The Task-Aware MPI library (TAMPI) eases the development of applications combining tasking with MPI. TAMPI enables developers to overlap computation and communication phases by relying on the tasking data-flow execution model. Using this approach, the original computation that was distributed in many different MPI ranks is grouped together in fewer MPI ranks, and split into several tasks per rank. Nevertheless, programmers must be careful with task granularity. Too fine-grained tasks introduce too much overhead, while too coarse-grained tasks lead to lack of parallelism. An adequate granularity may not always exist, especially in distributed environments where the same amount of work is distributed among many more cores. Worksharing tasks are a special kind of tasks, recently proposed, that internally leverage worksharing techniques. By doing so, a single worksharing task may run in several cores concurrently. Nonetheless, the task management costs remain the same than a regular task. In this work, we study the combination of worksharing tasks and TAMPI on distributed environments using two well known mini-apps: HPCCG and LULESH. Our results show significant improvements using worksharing tasks compared to regular tasks, and to other state-of-the-art alternatives such as OpenMP worksharing.

关键词： Data-Flow Hybrid-Programming MPI+X Performance-Analysis Tasking

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distributed Optimization of Nonlinear, Non-Gaussian, Communication-Aware Information using Particle Methods

Distributed Optimization of Nonlinear, Non-Gaussian, Communi...

引用

ieee international conference on Robotics and Automation (ICRA)

作者： Moon, Sangwoo Frew, Eric W. Univ Colorado Ann & HJ Smead Aerosp Engn Sci Boulder CO 80303 USA

ISBN: (纸本)9781728173955

This paper presents a distributed optimization framework and its local utility design for communication-aware information gathering by mobile robotic sensor networks. The main idea of the optimization is that each robot decides based on its local utility that considers the decisions of other neighbor robots higher in a given hierarchy. The local utility is designed as conditional mutual information that captures sensing and communication properties. Sampling procedures using a specific measurement set and particle methods are applied to compute the designed utility, which allows nonlinear, non-Gaussian properties of targets, sensing, and communication. Simulation results describe the presented distributed optimization shows more improved estimates and entropy reduction than another approach that does not consider communication properties. Simulation results also verify the presented distributed optimization using the described approach for information computation has better results than using other approaches that simplify the communication-aware information.

关键词： Gaussian noise (electronic)

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Optimal sensor Management for Multiple Target Tracking Using Cooperative Unmanned Aerial Vehicles

Optimal Sensor Management for Multiple Target Tracking Using...

引用

international conference on Unmanned Aircraft systems (ICUAS)

作者： Baek, Stanley York, George US Air Force Acad Dept Elect & Comp Engn Usaf Acad CO 80840 USA

ISBN: (纸本)9781728142784

In this work, we consider collaborative unmanned aerial vehicles (UAVs) with a gimbaled sensor tracking multiple mobile surface targets, where the number of targets is greater than the number of UAVs. To this end, we have developed an efficient distributed software algorithm enabling a team of collaborative unmanned aerial vehicles to effectively detect and track multiple mobile ground targets. The software framework we present in this paper includes optimal sensor management technique to minimize the localization uncertainty of targets, efficient data association method, and a consensus decisionmaking algorithm to reach agreement on target assignments. Our novel strategy in this integrated framework of cooperative aerial robots effectively utilizes their sensing resources using the optimal sensor management technique as well as the consensus decision-making. Our results show that a team of n UAVs can effectively track more than 2n targets with acceptable localization uncertainties.

关键词： Decision making

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Integrating IoT and sensor Technologies for Smart Agriculture: Optimizing Crop Yield and Resource Management

Integrating IoT and Sensor Technologies for Smart Agricultur...

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Technology & Engineering Management conference - Asia Pacific (TEMSCON-ASPAC), ieee

作者： Manoj Ravishankar Suman Siddharth Anand Anil Yadav Sankit Ramkrishna Kassa Electronics & Telecommunication Department Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798350384659

ISBN: (纸本)9798350384666

This research paper explores the implementation of Smart Agriculture solutions in the context of modern farming. The project employs a range of sensor technologies, IoT devices, and cloud-based data analytics to collect, process, and provide real-time insights to farmers. The study’s objectives include enhancing data-driven decision-making, improving resource efficiency, ensuring environmental sustainability, and promoting affordability and accessibility for a wide range of farmers. The research methodology involved the deployment of advanced sensors, such as soil moisture, light intensity, temperature and humidity, and barometric pressure sensors, across an agricultural field. Data collected from these sensors was integrated into a cloud-based system, which allowed farmers to access real-time information and insights through a user-friendly interface. The results of the experimentation phase demonstrated the effectiveness of the system in optimizing irrigation schedules, enhancing crop health, and conserving resources. Challenges related to data accuracy, connectivity, and initial setup costs were addressed through calibration, network stability, and affordable subscription plans, ensuring the system’s practical applicability. This research paper contributes to the field of precision agriculture by providing an integrated, scalable, and accessible solution for farmers. The study emphasizes data-driven decision- making and sustainable farming practices, making it a valuable resource for enhancing agricultural productivity in the face of modern challenges.

关键词： Smart agriculture Temperature sensors Cloud computing Data analysis Real-time systems Resource management Internet of Things

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Understanding the United States’ 50 most populous counties’ COVID-19 healthcare outcomes through multiple regression across the Delta variant and Omicron variant times of dominance

Understanding the United States’ 50 most populous counties...

引用

international conference on distributed computing in sensor systems (DCOSS)

作者： Alexander Bruckhaus Yujia Zhang Aidin Abedi Sana Salehi Dominique Duncan USC Stevens Neuroimaging and Informatics Institute University of Southern California Los Angeles CA USA Department of Neurological Surgery University of Southern California Los Angeles CA USA USC Stevens Neuroimaging and Informatrics Institute University of Southern California Los Angeles CA USA

ISBN: (数字)9781665495127

ISBN: (纸本)9781665495134

As new variants of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continuously evolve and mutate, it is vital to understand how novel and emerging variants affect public health outcomes. Our understanding of COVID-19 can have significant impacts on how we approach measures to mitigate the virus’s deleterious effects on the world. Therefore, in this study, we aim to 1) quantify the relationships between county-characteristics, such as the proportion of residents vaccinated, and certain county-level health outcomes related to COVID-19 such as: case counts, death counts, positivity rates, infection rates, ICU occupancy levels, hospitalizations, and the proportion of ICU admissions due to COVID-19. We also aim to 2) compare these relationships across three different time periods - two periods where Delta was the dominant strain of the U.S. and one period where Omicron was the dominant strain of the U.S. In this study, we used multiple regression to measure the strength of relationships between healthcare outcomes and county characteristics from June 20, 2021 to March 19, 2022, which span across three time periods. The first two time periods, June 20, 2021 to September 18, 2021 and September 19, 2021 to December 18, 2021, are when Delta was dominant (> 50% of cases) in the U.S. and the third period, December 19, 2021 to March 19, 2022, is during Omicron’s dominance (up to March 19, 2022).

关键词： COVID-19 Sociology Complex networks Market research Time measurement sensor systems Statistics

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Towards Trusted Data on Decentralized IoT Applications: Integrating Blockchain in Constrained Devices

Towards Trusted Data on Decentralized IoT Applications: Inte...

引用

ieee international conference on Communications (ieee ICC) / Workshop on NOMA for 5G and Beyond

作者： Pincheira, Miguel Vecchio, Massimo FBK CREATE NET OpenloT Res Unit Trento Italy Univ Trento DISI Trento Italy

ISBN: (纸本)9781728174402

Blockchain technology is attracting the interest of the Internet of Things (IoT) domain as a decentralized platform for a trusted record of information. Thus, an increasing number of architectures have been proposed for integrating both technologies. However, few of them have focused on the sensing elements of the IoT systems, which are typically low-cost and resource-constrained devices. In this work, we propose an architecture that integrates blockchain at the sensor level, creating a chain of trust from the source of the data. To evaluate our proposal, we develop a cross-platform library for constrained IoT devices and deploy a full-fledged utilities management showcase using off-the-shelf hardware. From a device perspective, we measure the overhead that our architecture introduces in the system, in terms of memory and program space footprint, processing time, and power consumption. From the application perspective, we quantify the additional cost and delay incurred by using a public blockchain. Our results show that even constrained 8-bit devices with a 16-MHz AVR CPU can support the proposed solution. Moreover, the cost of maintaining a transparent record of daily resource consumption on the blockchain can be less than 1 USD a month.

关键词： Internet of Things blockchain distributed ledger smart contracts edge computing constrained devices transparency

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distributed Integrity Auditing of Cloud data using Edge computing and Blockchain

Distributed Integrity Auditing of Cloud data using Edge Comp...

引用

international Symposium on Advanced Networks and Telecommunication systems (ANTS)

作者： Amit Kumar Dwivedi Naveen Kumar Manik Lal Das IIIT Vadodara India DA-IICT Gandhinagar India

ISBN: (数字)9781665473408

ISBN: (纸本)9781665473415

Auditing of outsourced data is typically managed by an untrusted third party, which poses a crucial data integrity issue for the data owner and end users as well. A distributed auditing scheme comprises three primary participants - data owner, storage server, and end users. One of the main concerns in a distributed auditing setting is that a registered end user may get involved in auditing data files on behalf of the data owner. The reason behind involving end users to audit data files is to reduce computational cost at data owner. However, the approach increases the communication cost, as the data owner may receive multiple failure reports corresponding to the same corrupt file from different authorized users. In this paper, a secure and efficient distributed auditing scheme for outsourced data is presented using blockchain technology and edge computing. The proposed scheme uses blockchain for storing distinct failure reports. Edge nodes are used to handle local auditing task. The scheme is compared and analyzed with the existing distributed data integrity auditing schemes. It is shown that the proposed scheme is secure and outperforms other schemes in terms of computational cost at the data owner and communication cost used by the scheme participants.

关键词： Data privacy Costs Data integrity Data security Blockchains Computational efficiency Telecommunications

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Romanus: Robust Task Offloading in Modular Multi-sensor Autonomous Driving systems

Romanus: Robust Task Offloading in Modular Multi-Sensor Auto...

引用

ieee international conference on Computer-Aided Design

作者： Luke Chen Mohanad Odema Mohammad Abdullah Al Faruque Department of Electrical Engineering and Computer Science University of California Irvine California USA

Due to the high performance and safety requirements of self-driving applications, the complexity of modern autonomous driving systems (ADS) has been growing, instigating the need for more sophisticated hardware which could add to the energy footprint of the ADS platform. Addressing this, edge computing is poised to encompass self-driving applications, enabling the compute-intensive autonomy-related tasks to be offloaded for processing at compute-capable edge servers. Nonetheless, the intricate hardware architecture of ADS platforms, in addition to the stringent robustness demands, set forth complications for task offloading which are unique to autonomous driving. Hence, we present ROMANUS, a methodology for robust and efficient task offloading for modular ADS platforms with multi-sensor processing pipelines. Our methodology entails two phases: (i) the introduction of efficient offloading points along the execution path of the involved deep learning models, and (ii) the implementation of a runtime solution based on Deep Reinforcement Learning to adapt the operating mode according to variations in the perceived road scene complexity, network connectivity, and server load. Experiments on the object detection use case demonstrated that our approach is 14.99% more energy-efficient than pure local execution while achieving a 77.06% reduction in risky behavior from a robust-agnostic offloading baseline.

关键词： Deep learning Runtime Pipelines Object detection Robustness Hardware Energy efficiency

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Research on curve braking based on sensor fusion 5

Research on curve braking based on sensor fusion

引用

5th CAA international conference on Vehicular Control and Intelligence, CVCI 2021

作者： Li, Linhui Liang, Ruitian Zhang, Yifan Lian, Jing Guan, Xiaowei School of Automotive Engineering Dalian University of Technology Dalian China Hualu Zhida Technology Co. Ltd Dalian China

ISBN: (纸本)9781665408462

The stability of the braking process of the intelligent vehicle is mainly divided into two parts: the accurate selection of the braking target and the stability during a braking on curve. For the selection of braking targets, this paper uses sensor fusion to identify and fit lane lines, and establishes a road curvature estimation model, which is used to identify the target vehicle in front of the lane, thereby effectively reducing vehicle mis-braking. The emergency braking of a vehicle in a curve is prone to instability. To solve this problem, a sliding-mode controller is worked out based on the joint control of the yaw rate and the side slip angle, in order to calculate the additional yaw moment. Then the additional yaw moment is converted into the braking moment of the wheels, so as to realize that the actual yaw rate and the side slip angle of the center of mass can follow the ideal value well. Finally, using Prescan, Carsim and MATLAB/Simulink for joint simulation, the results show that the proposed target vehicle recognition strategy based on sensor fusion can effectively reduce the vehicle's mis-braking on curve, and after the torque is distributed through the designed sliding mode controller, it can effectively improve the braking stability of the vehicle. © 2021 ieee.

关键词： Vehicles

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distributed and Privacy Preserving Routing of Connected Vehicles to Minimize Congestion 17

Distributed and Privacy Preserving Routing of Connected Vehi...

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17th ieee international conference on Mobile Ad Hoc and Smart systems (ieee MASS)

作者： Boob, Surabhi Mahmood, Shakir Shahzad, Muhammad North Carolina State Univ Raleigh NC 27695 USA Natl Univ Sci & Technol Islamabad Pakistan

ISBN: (纸本)9781728198668

With a large number of connected vehicles on the roads, there is an opportunity to leverage their connectivity to minimize congestion on roads by calculating fast routes for vehicles in a way that each vehicle contributes as little to the congestion as possible. The existing commercial and research based approaches of calculating routes for vehicles suffer from one or more of the following two limitations: 1) they are not privacy preserving in the sense that they receive destination addresses from users and may either store and use them for other commercial purposes or are at a risk of getting hacked and exposing these addresses to hackers;and 2) they require expensive infrastructure such as road side units (RSUs). To address these limitations, we propose a distributed and privacy preserving routing protocol, namely DPR, which the connected vehicles collaboratively and repeatedly execute to calculate fast routes to their destinations such that the overall congestion on the road network is significantly reduced and at the same time the privacy of the vehicles is preserved. The DPR protocol relies on direct vehicle to vehicle communication and does not need any new infrastructure such as RSUs. We have implemented and evaluated our DPR protocol through simulations on a real road network under several traffic conditions. Our results show that DPR reduces the average travel time of vehicles that travel a distance of 1000, 2500, and over 4000 meters by 15%, 32%, and 42%, respectively. This reduction in travel time is significant considering that this improvement results purely from software manipulations and without requiring any new infrastructure.

关键词： Roads and streets

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