As edge computing becomes an increasingly important computing model, trust management and security issues are becoming more severe. Problems such as malicious node attacks and trust isolation pose threats to the secur...
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The enhancement of signal-to-noise ratio (SNR) represents a significant challenge for distributed optical fiber acoustic sensing systems. This paper presents a distributed optical fiber acoustic sensing system based o...
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With the rapid advancement of aerospace electronics, the traditional single-satellite application paradigm is transitioning towards collaborative networking involving multiple satellites. Furthermore, the continuous i...
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The internet’s evolution has highlighted cloud computing’s limitations, such as latency and bandwidth issues, prompting interest in edge computing to address these. Effective load balancing is essential to fully lev...
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This paper proposes a face authentication and facial expression recognition system based on blockchain and trusted computingtechnology. With the continuous development of digital technology, people's demand for i...
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Image steganography is a technology that embed secret information within a cover image to obtain a stego-image for covert communication. The transmission of undetectable stego-images via social media can facilitate se...
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College of Computer Science Beijing University of technology, Beijing 100124, China, 1374622525@*** This paper proposes a trust collaboration technology for edge computing, addressing trust isolation and security issu...
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The swift expansion of the informationtechnology (IT) industry has led to a surge in compute-intensive and latency-sensitive applications. While cloud computing can satiate the demands of such applications, its centr...
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ISBN:
(纸本)9783031751691;9783031751707
The swift expansion of the informationtechnology (IT) industry has led to a surge in compute-intensive and latency-sensitive applications. While cloud computing can satiate the demands of such applications, its centralized architecture may cause delays in the execution of tasks. To address such issues, edge computing brings computation closer to data sources. However, limited resources on Internet of things (IoT) devices make local execution quite challenging. Therefore, a pliable approach is to consider task offloading for moving heavy tasks to resource-extensive systems like edge/cloud. Osmotic computing, leveraging edge and cloud resources, aims to enhance IoT services. However, the dynamic nature of IoT, edge, and cloud introduces challenges for task offloading. This paper proposes an offloading algorithm using fuzzy logic to manage uncertainty. Furthermore, we introduce an osmotic decision manager (ODM) that employs fuzzy logic for optimized offloading decisions, considering IoT/edge for latency-sensitive tasks and cloud for latency-tolerant tasks. This algorithm aims to improve overall system performance by efficiently offloading tasks based on their specific requirements and constraints. The proposed algorithm undergoes simulation and assessment with diverse synthetic test cases to demonstrate its efficacy.
Multimodal image segmentation utilizes a variety of modality images with RGB, infrared, polarization, etc. Unfortunately, the mainstream focus on digital modality fusion leads to the cost of computing abundant informa...
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Traditional multi-dimensional classification (MDC) methods often assume that optimizing a single objective can improve overall performance, thus meeting the requirements of various applications. However, achieving opt...
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