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Found 13 papers, 0 papers with code
Unleashing the True Power of Age-of-Information: Service Aggregation in Connected and Autonomous Vehicles
With an increase in AoI, incremental service aggregation issues are observed with out-of-sequence information updates, which hampers the performance of low-latency applications in CAVs.
DeepEn2023: Energy Datasets for Edge Artificial Intelligence
We anticipate that DeepEn2023 will improve transparency in sustainability in on-device deep learning across a range of edge AI systems and applications.
Unveiling Energy Efficiency in Deep Learning: Measurement, Prediction, and Scoring across Edge Devices
In this paper, we conduct a threefold study, including energy measurement, prediction, and efficiency scoring, with an objective to foster transparency in power and energy consumption within deep learning across various edge devices.
Analysis and Detection against Network Attacks in the Overlapping Phenomenon of Behavior Attribute
Then, many attack detection methods based on these datasets are proposed.
Listen to Minority: Encrypted Traffic Classification for Class Imbalance with Contrastive Pre-Training
Despite some existing learning-based ETC methods showing promising results, three-fold limitations still remain in real-world network environments, 1) label bias caused by traffic class imbalance, 2) traffic homogeneity caused by component sharing, and 3) training with reliance on sufficient labeled traffic.
Research on Efficient Fuzzy Clustering Method Based on Local Fuzzy Granular balls
In recent years, the problem of fuzzy clustering has been widely concerned.
GBMST: An Efficient Minimum Spanning Tree Clustering Based on Granular-Ball Computing
We construct coarsegrained granular-balls, and then use granular-balls and MST to implement the clustering method based on "large-scale priority", which can greatly avoid the influence of outliers and accelerate the construction process of MST.
EPAM: A Predictive Energy Model for Mobile AI
Predicting the energy consumption of these models, along with their different applications, such as vision and non-vision, requires a thorough investigation of their behavior using various processing sources.
A novel cluster internal evaluation index based on hyper-balls
It is crucial to evaluate the quality and determine the optimal number of clusters in cluster analysis.
GBC: An Efficient and Adaptive Clustering Algorithm Based on Granular-Ball
Existing clustering methods are based on a single granularity of information, such as the distance and density of each data.
LEAF + AIO: Edge-Assisted Energy-Aware Object Detection for Mobile Augmented Reality
In this paper, we design an edge-based energy-aware MAR system that enables MAR devices to dynamically change their configurations, such as CPU frequency, computation model size, and image offloading frequency based on user preferences, camera sampling rates, and available radio resources.
Energy Drain of the Object Detection Processing Pipeline for Mobile Devices: Analysis and Implications
In order to accurately measure the energy consumption on the smartphone and obtain the breakdown of energy consumed by each phase of the object detection processing pipeline, we propose a new measurement strategy.
Architectural Design Alternatives based on Cloud/Edge/Fog Computing for Connected Vehicles
These requirements ask for a well-designed computing architecture to support the Quality-of-Service (QoS) of CV applications.
Networking and Internet Architecture
