An algorithm for the graphmatching is presented. The steps of finding compliance with the expectation ratio are described. The degree of difference of edges is calculated. The way to find the similarity of vertices u...
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ISBN:
(纸本)9789663354125
An algorithm for the graphmatching is presented. The steps of finding compliance with the expectation ratio are described. The degree of difference of edges is calculated. The way to find the similarity of vertices using the Euclidean distance is described. The algorithm is implemented and experimentally tested for performance.
In response to challenges such as data encryption, uneven distribution, and user privacy concerns in network traffic classification, this paper presents a clustering-based *** response to challenges such as data encry...
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In response to challenges such as data encryption, uneven distribution, and user privacy concerns in network traffic classification, this paper presents a clustering-based *** response to challenges such as data encryption, uneven distribution, and user privacy concerns in network traffic classification, this paper presents a clustering-based approach. The proposed method utilizes a graphmatching approach to effectively categorize data streams in real-time scenarios. This approach aims to enhance the accuracy and efficiency of network traffic classification, particularly in the face of evolving encryption techniques and privacy-preserving measures. The method relies solely on non-content features to characterize network flow characteristics and employs graph matching algorithms to reduce inter-class imbalances, enabling coarse-grained clustering and reliable graphmatching. Firstly, an unsupervised clustering framework is designed, which studies the diverse distributions and category similarities of traffic data based on a limited set of features. This unsupervised clustering helps mitigate network disparities by aggregating network sessions into a few clusters with extracted primary features. Next, the correlation between clusters from the same network is used to construct a similarity graph. Finally, a graph matching algorithm is proposed, which combines graph neural networks and graphmatching networks to reveal reliable correspondences between different network relationships. This allows for associating clusters in the test network with clusters in the initial network, enabling the labeling of test clusters based on associated clusters in the training set. Simulation results demonstrate that the proposed method achieves an accuracy rate of 96.8%, which is significantly superior to existing approaches.
Executing irregular, data-intensive workloads on multithreaded architectures can result in performance losses and scalability problems. Codesigning algorithms and architectures can realize high performance on irregula...
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Executing irregular, data-intensive workloads on multithreaded architectures can result in performance losses and scalability problems. Codesigning algorithms and architectures can realize high performance on irregular applications. A codesign study reveals four key lessons learned from implementing matchingalgorithms on various platforms.
CASA (computer aided systems architecting) is a methodology and tool to support the design of complex technical systems. It combines approaches from systems and requirement engineering and AI. System design in CASA is...
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ISBN:
(纸本)3540662375
CASA (computer aided systems architecting) is a methodology and tool to support the design of complex technical systems. It combines approaches from systems and requirement engineering and AI. System design in CASA is requirement-driven and works by a hierarchical stepwise top-down refinement of designs and a hierarchical decision making process. One important task in CASA deals with reusability of existing design artifacts and is supported by case-based reasoning techniques. Based on given structural specifications and format requirements, a search procedure finds the best inexact match in a design base and computes an estimated degree of fulfillment for requirements. The approach employs efficient graphmatching and indexing scheme for case retrieval and structural similarities and has adapted usual similarity measures to compute degree of fulfillment of requirements. It has been show by different example projects that the developed methods can be of great practical assistance for a designer.
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