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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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A software trigger based synchronization for multipurpose distributed acquisition systems

A software trigger based synchronization for multipurpose di...

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2020 international conference on Innovation and Intelligence for Informatics, computing and Technologies, 3ICT 2020

作者： Jetti, Harsha Vardana Salicone, Simona Politecnico di Milano Dipartimento di Energia Milano Italy Milano Italy

ISBN: (纸本)9781728196732

Synchronization is one of the key aspects and a requirement for modern day technologies. It's a requirement for almost every sector including power, health, retail, navigation, banking. Synchronization is also important when using distributed acquisition systems. Synchronous acquisition is strictly needed in applications like Phasor Measurement Units (PMU) and wide area sensor networks. Since the data from the sensors are all collectively processed by a central unit, it is important that the data from all sensors is synchronized. Therefore, the concept of synchronized sampling when using distributed acquisition systems forms an interesting research area. There have been numerous research papers discussing different methods to do this. But, in most of them, the available technology is specific to a particular application. This paper shows an initial attempt to present a solution with a PTP driven software trigger that could potentially be used for multiple applications. © 2020 ieee.

关键词： Synchronization

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Cooperative Air-Ground Instant Delivery by UAVs and Crowdsourced Taxis

Cooperative Air-Ground Instant Delivery by UAVs and Crowdsou...

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international conference on Data Engineering

作者： Junhui Gao Qianru Wang Xin Zhang Juan Shi Xiang Zhao Qingye Han Yan Pan School of Computer Science Northwestern Polytechnical University School of Computer Science and Technology Xidian University National Key Laboratory of Information Systems Engineering National University of Defense Technology Air Force Engineering University Laboratory for Big Data and Decision National University of Defense Technology School of Management Science and Real Estate Chongqing University National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

Instant delivery has become a fundamental service in people's daily lives. Different from the traditional express service, the instant delivery has a strict shipping time constraint after being ordered. However, the labor shortage makes it challenging to realize efficient instant delivery. To tackle the problem, researchers have studied to introduce vehicles (i.e., taxis) or Unmanned Aerial Vehicles (UAVs or drones) into instant delivery tasks. Unfortunately, the delivery detour of taxis and the limited battery of UAVs make it hard to meet the rapidly increasing instant delivery demands. Under this circumstance, this paper proposes an air-ground cooperative instant delivery paradigm to maximize the delivery performance and meanwhile minimize the negative effects on the taxi passengers. Specifically, a data-driven delivery potential-demands-aware cooperative strategy is designed to improve the overall delivery performance of both UAVs and taxis as well as the taxi passengers' experience. The experimental results show that the proposed method improves the delivery number by 30.1% and 114.5% compared to the taxi-based and UAV-based instant delivery respectively, and shortens the delivery time by 35.7% compared to the taxi-based instant delivery.

关键词： Autonomous aerial vehicles Data engineering Air to ground communication Trajectory Batteries Time factors Task analysis

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Performance and Energy-Tuning Methodology for Wireless sensor Networks Using TunableMAC

Performance and Energy-Tuning Methodology for Wireless Senso...

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2020 ieee international conference on Communications, computing, Cybersecurity, and Informatics, CCCI 2020

作者： Udoh, Ekereuke Getov, Vladimir Distributed and Intelligent Systems Research Group University of Westminster London United Kingdom

ISBN: (纸本)9781728120355

Energy-efficiency and performance are at the forefront with regards to wireless sensor networks due to the resource-constrained nature of the sensors on the network. Most of the energy in a sensor is consumed by the radio and this therefore creates the need for a more efficient use of the Media Access Control (MAC) layer which controls access to the radio. The Castalia framework which runs on the OMNET++ simulation platform provides a MAC layer protocol - TunableMAC - which is used in this paper for tuning of performance and consumed power. Our goal is to improve as much as possible the performance/energy balance in terms of resources used up by security features, while attempting to preserve the overall lifespan of the wireless sensors. This paper investigates performance parameters for TunableMAC such as energy consumed, latency, throughput and network lifetime based on simulated temperature sensors. A 5-step methodology is proposed that can be helpful for minimizing the impact of denial-of-sleep (DOS) attacks. Hence, the benefit of this research is that it feeds into the development of a novel MAC protocol that is energy-aware and can autonomously guard against energy drain attacks such as DOS attacks. © 2020 ieee.

关键词： Wireless sensor networks

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VMR-Tree: Efficient and Verifiable Location-based kNN Queries on Blockchain

VMR-Tree: Efficient and Verifiable Location-based kNN Querie...

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ieee international conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Yiping Teng Lei Liu Jiawei Qi Haochun Pan Chunlong Fan School of Computer Large-scale Distributed System Laboratory Shenyang Aerospace University Shenyang China

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

In recent years, blockchain technology has received extensive attention and applied in various fields including health-care, IoT and database systems. Utilizing the decentralization and anti-tampering properties, the blockchain provides potential solutions to achieve verification of data queries, without the assumption of the trusted third parties in traditional data verification studies. However, for kNN queries, a common query type in practical location-based scenarios, few existing solutions can directly support the location-based kNN query processing and result authentication based on blockchain. To address this problem, in this paper, we propose a blockchain-based verifiable kNN query processing method. In this method, we first design a novel authenticated data structure called VMR-Tree, which stores the data objects and their neighboring objects in leaf nodes and stores the hash values used for data verification in non-leaf nodes. To verify the results with the minimum size of verification objects (VOs), we design a query result verification method based on the blockchain, in which the client can verify the query results by processing the VOs generated based on the proposed VMR-Tree index and the blockchain. Besides, we further propose an optimization algorithm to reduce the size of VOs. We theoretically analyze the computational complexity and security guarantees of the proposed approaches. We also conducted extensive experiments on real and synthetic datasets to evaluate the efficiency of the proposed method on the result verification of location-based kNN queries.

关键词： Privacy Query processing Computational modeling Authentication Blockchains Security Computational complexity

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Wireless sensor Networks Life Time Optimization Based on the Improved Firefly Algorithm 16

Wireless Sensor Networks Life Time Optimization Based on the...

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16th ieee international Wireless Communications and Mobile computing conference (ieee IWCMC)

作者： Zivkovic, Miodrag Bacanin, Nebojsa Tuba, Eva Strumberger, Ivana Bezdan, Timea Tuba, Milan Singidunum Univ Fac Informat & Comp Belgrade Serbia

ISBN: (纸本)9781728131290

We have recently witnessed the rapid development of several emerging technologies, including the internet of things, which lead to a high interest in wireless sensor networks. Tiny sensor nodes are now important parts of a large number of complex systems, with numerous applications including military, environment monitoring, surveillance and body area sensor networks. One of the biggest challenges each wireless sensor network has to handle is the network lifetime maximization. To achieve this, numerous clustering algorithms have been created, with the goal to improve energy consumption throughout the network by balancing the energy consumption overall nodes. All clustering algorithms incorporate load balancing to achieve energy efficiency. One of the basic and most important algorithms in use is LEACH. Swarm intelligence metaheuristics have already been applied in solving numerous problems of wireless sensor networks, including lifetime optimization, localization and many other NP hard problems with promising results, as can be seen in the literature overview. In the research proposed in this paper, an improved version of the firefly algorithm has been applied to improve the network lifetime. The firefly algorithm was used to help in forming the clusters and selection of the cluster head. Additionally, we have evaluated the performance of the improved firefly algorithm by comparing it to the LEACH, basic firefly algorithm and particle swarm optimization, that were all tested on the same network infrastructure model. Conducted simulations have proven that our proposed metaheuristic achieves better and more consistent performance than other algorithms.

关键词： wireless sensor networks lifetime optimization metaheuristics optimization firefly algorithm LEACH

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Design of Power Data Encryption Speed Improvement Scheme Based on SM4

Design of Power Data Encryption Speed Improvement Scheme Bas...

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Power systems and Electrical Technology (PSET), ieee international conference on

作者： Yuqing Luo Jingxiang Feng Ruijue Feng School of advanced manufacturing Guangdong Polytechnic of Environmental Protection Engineering Foshan China School of Automotive Engineering Foshan Polytechnic Foshan China School of Electrical Engineering Guangzhou City University of Technology Guangzhou China

Electric power data contains rich private information, and encryption technology is often used to protect its information security. Due to its huge data volume, considering the lightweight and high-efficiency encryption algorithm, based on the encryption algorithm SM4 with independent intellectual property rights in my country, combined with the big data technology Hadoop, a parallel encryption speed-up scheme based on the national encryption algorithm SM4 is designed to realize the data encryption speed. Encryption and decryption protection and acceleration of computation. Finally, an experimental platform based on Hadoop is built, and the data is encrypted in blocks with the MapReduce computing framework, and the feasibility test of the scheme is carried out. The experimental results show that the algorithm scheme can improve the encryption speed of unstructured data files. The optimal number of Maps in the established cluster is 8, and the speedup ratio between serial encryption and parallel encryption is more than 2. Compared with serial encryption, it can save 50% of computing overhead time.

关键词： distributed databases Information security Clustering algorithms Intellectual property Network security Big Data Encryption

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distributed Decomposed Data Analytics of IoT, SAR and Social Network data 3

Distributed Decomposed Data Analytics of IoT, SAR and Social...

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3rd international conference on Communication systems, computing and IT Applications, CSCITA 2020

作者： Bharadi, Vinayak Ashok Tolye, Shashank Finolex Academy of Management and Technology IT Department Ratnagiri India

ISBN: (纸本)9781728123394

The weather nowadays has become so unpredictable that there is a need for a system that predicts correct weather patterns and allows them to take a precautionary plan of action to cope up with it. Three major sources of providing very crucial weather data are IoT sensors, SAR data and social media posts from a particular location. In this paper, we are proposing a system that takes IoT sensor data, SAR images and twitter feeds from a geographical location and creates a learning model that will provide a decision-making system for anomaly detection in order to minimize or nullify any casualties. A temperature, pressure and humidity dataset of BME 280 sensor is processed with K-NN Classifiers and the results are presented here. © 2020 ieee.

关键词： Graphics processing unit

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distributed Clique-Based Neural Networks for Data Fusion at the Edge

Distributed Clique-Based Neural Networks for Data Fusion at ...

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2nd ieee international conference on Artificial Intelligence Circuits and systems (AICAS)

作者： Larras, Benoit Frappe, Antoine Univ Lille CNRS Cent LilleIEMN Yncrea ISENUniv Polytech Hauts FranceUMR 8520 F-59000 Lille France

ISBN: (纸本)9781728149226

distributed smart sensors are more and more used in applications such as biomedical or domestic monitoring. However, each sensor broadcasts data wirelessly to the others or to an aggregator, which leads to energy-hungry sensors not ensuring data privacy. To tackle both challenges, this work proposes to distribute a part of a clique-based neural network in each sensor. This scheme allows standardizing data at the sensor level, ensuring privacy if the data is intercepted. Besides, a lower number of bits is transmitted, thus limiting the communication overhead. The circuit implementation is possible with the use of single-cluster iterative clique-based circuits. To this end, a hardware circuit has been fabricated and performs a classification using 115fJ per synaptic event per neuron in 83ns.

关键词： Data privacy

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Fractus: Orchestration of distributed Applications in the Drone-Edge-Cloud Continuum

Fractus: Orchestration of Distributed Applications in the Dr...

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ieee Annual international Computer Software and Applications conference (COMPSAC)

作者： Nasos Grigoropoulos Spyros Lalis University of Thessaly

ISBN: (数字)9781665488105

ISBN: (纸本)9781665488112

Next-generation drone applications will be distributed, including tasks that need to run at the edge or in the cloud and interact with the drone in a smooth way. In this paper, we propose Fractus, an orchestration framework for the automated deployment of such applications in the drone-edge-cloud continuum. Fractus provides users with abstractions for describing the application's placement and communication requirements, allocates resources in a mission-aware fashion by considering the drone operation area, establishes and maintains connectivity between components by transparently leveraging different networking capabilities, and tackles safety and privacy issues via policy-based access to mobility and sensor resources. We present the design of Fractus and discuss an implementation based on mature software deployment technology. Further, we evaluate the resource requirements of our implementation, showing that it introduces an acceptable overhead, and illustrate its functionality via real field tests and a simulation setup.

关键词： Privacy Cloud computing Codes conferences Computational modeling Software Safety

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Towards a One-Stop-Shop Solution for the Application of Data-Driven Value-Adding Services in Production

Towards a One-Stop-Shop Solution for the Application of Data...

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international conference on Emerging Technologies and Factory Automation (ETFA)

作者： Magnus Redeker Dennis Quirin Rafael Schroeder Tobias Klausmann Alexander Löwen Alexander Wollbrink Heiko Stichweh Simon Althoff Amelie Bender Walter Sextro Marc Hesse Fraunhofer IOSB IOSB-INA Lemgo Fraunhofer Institute of Optronics System Technologies and Image Exploitation Bielefeld University Cognitronics & Sensor Systems Friedrich Remmert GmbH R & D Systems Engineering - Lenze SE Faculty of Mechanical Engineering Chair of Dynamics and Mechatronics Paderborn University Paderborn Germany Weidmüller Group

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

The holistic application of data-driven value-adding services (DDSs) to shop-floor assets (SFAs; e.g. equipment, machines, components) is a major obstacle, particularly for small and medium-sized enterprises (SMEs): Due to the high complexity and required expertise in various disciplines. It is necessary to i) select suitable DDSs for a relevant component in production, ii) provide data for their training, iii) deploy the DDSs in the given IT/OT infrastructure, and iv) setup data-streams between SFAs, DDSs, and dashboards. Currently, many companies are implementing flagship projects that go through the necessary steps for individual components, but these isolated solutions are not scalable due to the need for manual intervention. This paper describes how to completely automatize the four steps and their consolidation in a scalable Industry 4.0 one-stop-shop solution. To achieve this goal, each asset is equipped with an Asset Administration Shell (AAS) that specifies, in particular, the represented asset's capabilities, the data required to apply such a capability and the data generated by a capability. Based on the AASs of SFAs, DDSs, and computing resources (CRs), a matching service suggests automatically which DDSs would add value to which SFAs and, for each SFA-DDS match, in which CR to deploy the DDS. A trade fair demonstration provides strong support for the statements made: The one-stop-shop solution including the automatic matching greatly simplifies the application of data-driven services and, in some cases, even makes it possible at all.

关键词： Training Space vehicles Production systems Remotely guided vehicles Semantics sensors Laser beam cutting Streams Space stations Monitoring

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