Withthe emergence of a large number of energy prosumer units, the edge side of the regulation system has become an intelligent computing unit, which has transformed the energy internet control mode from centralized t...
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ISBN:
(纸本)9798350306194;9798350306187
Withthe emergence of a large number of energy prosumer units, the edge side of the regulation system has become an intelligent computing unit, which has transformed the energy internet control mode from centralized to decentralized centralized collaborative operation. Combined withthe theory of cloud-edge collaborative computing, this paper analyzes the data transmission characteristics of the energy internet regulation system, and designs the regulation architecture of cloud-edge collaboration, including information collection, edge computing, core computing, management control, business applications and security auxiliary layers. According to the real-time requirements of the regulation and control business, the energy internet regulation business processing process is designed, and the typical business scenarios of the energy internet are sorted out and analyzed. the simulation results show that the real-time data transmission of the energy internet regulation system based on cloud-edge collaboration has been greatly improved, which can ensure the operation reliability of the new energy internet service scenario.
internet of things is a popular source to collect data. It is also a rich source to various types of information. Withthe rapid popularity of IoT, things getting connected to it and the number are increasing continuo...
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the term 'cloud computing' describes a way of using the internet to access resources, software, and databases without being constrained by local hardware. Businesses adopting this technology can grow their ope...
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In the realm of the internet of Vehicles (IoV), this study addresses a fundamental question that causes the emerging trends within the IoV landscape, Previous research in IoV has laid the groundwork but is limited by ...
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To detect the DDoS (distributed Denial of Service) attack that initiates a flooding attack over a targeted server or service meanwhile causing network traffic and disrupting legitimate users from accessing the network...
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Blockchain is the technology on which cryptocurrencies operate within the 6G internet of things. Due to its flexibility, it has received significant adoption in numerous applications as a possible distributed data man...
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Marine internet of things (Marine IoT) has garnered increasing interest in monitoring oceanic environments. But establishing a Marine IoT system for observing and processing marine environmental data presents various ...
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Many problems have been solved using the internet of things (IoT). Waste management, resource management, traffic management, financial services (e.g. stock rate prediction), logistics services, agriculture, etc. are ...
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Withthe increasingly fierce competition in the marketing and after-market of commercial vehicle enterprises in China, enterprises are facing the important issue of lack of objective and efficient digital means to tap...
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Earth Observation (EO) has traditionally involved the transmission of a large volume of raw data to map the Earth surface. this results in congestion to the satellite network and delays in the availability of the resu...
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ISBN:
(纸本)9798350384826;9798350384819
Earth Observation (EO) has traditionally involved the transmission of a large volume of raw data to map the Earth surface. this results in congestion to the satellite network and delays in the availability of the results, invalidating the approach for timing-sensitive applications. Instead, the computation resources at the satellites can be used as an edge layer for compressing the data and/or doing inferences. In this paper, we investigate satellite edge computing for vessel detection with a LEO satellite constellation. First, we distribute the computation and inference load among the neighbouring satellites of the one taking the images, based on the VHRShips data set and YOLOv8. this semantic and fragmented information is then routed to a remote ground monitor through the whole constellation. the average and peak Age of Information (AoI) are reformulated to measure the freshness of the aggregated information at the receiver in this image-capture scenario. We then dimension the network number of orbital planes and satellites per orbital plane - for a given target age and covered area that quantify the level of achievement of the task. the results show that 20 orbital planes with 20 satellites are necessary to keep the peak AoI below 60 s with a compression ratio > 23000, i.e., a size reduction of 99.996%, and for a similar to 100% probability of coverage.
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