With the advent of softwarization of digital telephone switches, many dynamic call routing schemes were explored in the 1980s to provide better network performance. In particular, we highlight two learning algorithms ...
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With the rapid development of the Internet, network traffic has shown explosive growth, which puts forward higher requirements for the network routing system. Traditional static routing methods are no longer able to m...
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Capsule networks offer a useful approach for modeling part-whole hierarchies in visual data, yet they remain limited in effectively handling uncertainty in part-object relationships. This work introduces an entropy-ad...
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In this paper, we introduce a novel dynamic expert selection framework for Mixture of Experts (MoE) models, aiming to enhance computational efficiency and model performance by adjusting the number of activated experts...
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A dynamicrouting algorithm based on satellite reliability evaluation model is proposed to reduce the impact of satellite failure in satellite optical networks. Simulations show that our algorithm can achieve lower tr...
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We propose a multi-constraint routing algorithm with dynamic label restrictions based on the contraction hierarchies, considering spectrum, OSNR, and delay. Simulation shows the algorithm finds a path within 0.2ms at ...
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In modern advanced packaging, redistribution layers (RDLs) are often used for signal transmission among chips, and vias are used for communication among different layers. Most existing RDL routers perform via planning...
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The report proposes a dynamicrouting method for Self-healing Networks (ShN). The method takes into account the specific features of ShN. During routing, the flow of service information is reduced. The search for the ...
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Capsule networks(CapsNet) are recently proposed neural network models with new processing layers, specifically for entity representation and discovery of images. It is well known that CapsNet have some advantages over...
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This paper proposes an energy-efficient smart architecture for a Fog-based Wireless Sensor Network to facilitate safe evacuation in smart buildings during emergencies. The architecture comprises two layers: the sensin...
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This paper proposes an energy-efficient smart architecture for a Fog-based Wireless Sensor Network to facilitate safe evacuation in smart buildings during emergencies. The architecture comprises two layers: the sensing layer and the fog layer. Throughout the building, strategically distributed sensors continuously monitor potential emergencies and communicate with a central fog computing server, facilitating efficient emergency response management. To optimize evacuation routes, sensor nodes independently determine quick and safe paths using local intelligence, effectively addressing potential fog computing delays. The implementation of dynamic routing algorithms helps prevent congestion and evenly distribute evacuees across multiple routes. To achieve these objectives, the paper proposes an Improved Layer-wise Clustering Protocol (ILC) to establish an equal number of cluster heads at each floor of the smart building. Furthermore, Non-dominated Sorting Genetic Algorithm III (NSGA-III) is utilized to further enhance the system's performance. The combination of fog computing and smart sensing in this architecture presents a promising solution for ensuring the safety and effectiveness of building evacuations during critical situations. The extensive experimental analysis demonstrates that the ILC with NSGA-III (ILC-NSGA-III) surpasses the performance of competitive protocols in various key metrics such as stable period, network lifetime, energy conservation, and end-to-end delay.
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