As deep learning grows rapidly, model training heavily relies on parallel methods and there exist numerous cluster configurations. However, current preferences for parallel training focus on data centers, overlooking ...
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Over the course of the last several decades, a significant amount of research effort has been carried out to construct wireless sensor networks (WSN) for a broad range of applications. These applications include monit...
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Two major issues concerning handling Internet of Things (IoT) networks are energy efficiency and efficient data transfer, especially in large-scale deployments. A popular technique to increase network efficiency is cl...
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Underwater Optical Wireless sensor Networks (UOWSNs) are gaining an increasing demand in industrial and commercial applications as they can achieve high-speed communication. However, prior arts concentrate on promotin...
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ISBN:
(纸本)9798350339864
Underwater Optical Wireless sensor Networks (UOWSNs) are gaining an increasing demand in industrial and commercial applications as they can achieve high-speed communication. However, prior arts concentrate on promoting the performance of UOWSNs, while the reliability issue has not been fully addressed. In this paper, we propose a novel reliable data delivery scheme based on a cluster structure. First, we determine the orientation of each sensor for directional optical communication, which aims to establish reliable next-hop links among sensors. We formalize such an orientation problem into a submodular function maximization problem and propose a greedy method with an approximation ratio guarantee to solve it. Then, a cluster head designation scheme is developed to improve the data delivery success rate while minimizing the number of cluster heads. Finally, extensive simulations are conducted to demonstrate the effectiveness of the proposed scheme. The results reveal that compared with other algorithms, the proposed scheme can ensure a data delivery success rate of over 98.5% while only keeping 45.3% fewer cluster heads. Furthermore, test-bed experiments are carried out to verify the applicability of the proposed scheme in practical applications.
This paper proposes a visualization function for developers in volunteer computing. In recent years, information systems such as e-Learning systems and groupware have been introduced in companies and educational insti...
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The increasing load demands in distribution systems are giving rise to several issues, including higher line losses due to increased current flow and deterioration of the system voltage profile. To address these chall...
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Cloud computing is a 21st-century buzzword. Most organizations adopt this automation in today's world. However! there are different types of data processing, such as Time-sharing computing environment, client-serv...
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Wireless sensor Networks are a type of device that converts any of the physical quantity to an understandable, and observable quantity. sensors are lightweight and distributed in large numbers to monitor the type of s...
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Wirelessly streaming high quality 360 degree videos is still a challenging problem. When there are many users watching different 360 degree videos and competing for the computing and communication resources, the strea...
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ISBN:
(纸本)9798350363999;9798350364002
Wirelessly streaming high quality 360 degree videos is still a challenging problem. When there are many users watching different 360 degree videos and competing for the computing and communication resources, the streaming algorithm at hand should maximize the average quality of experience (QoE) while guaranteeing a minimum rate for each user. In this paper, we propose a cross layer optimization approach that maximizes the available rate to each user and efficiently uses it to maximize users' QoE. Particularly, we consider a tile based 360 degree video streaming, and we optimize a QoE metric that balances the tradeoff between maximizing each user's QoE and ensuring fairness among users. We show that the problem can be decoupled into two interrelated subproblems: (i) a physical layer subproblem whose objective is to find the download rate for each user, and (ii) an application layer subproblem whose objective is to use that rate to find a quality decision per tile such that the user's QoE is maximized. We prove that the physical layer subproblem can be solved optimally with low complexity and an actor-critic deep reinforcement learning (DRL) is proposed to leverage the parallel training of multiple independent agents and solve the application layer subproblem. Extensive experiments reveal the robustness of our scheme and demonstrate its significant performance improvement compared to several baseline algorithms.
This paper explores intelligent traffic light management advancements, focusing on controlling intersection traffic opening times. The decision-making process is influenced by factors such as traffic density. The info...
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ISBN:
(纸本)9783031820724;9783031820731
This paper explores intelligent traffic light management advancements, focusing on controlling intersection traffic opening times. The decision-making process is influenced by factors such as traffic density. The information for these decisions is gathered from sensors placed on the streets, whose accuracy can vary. Data collected are processed to aid control agents in decision-making. The paper proposes an intersection control algorithm that operates under the assumption of lacking sensorisation. To balance raw sensor data, control nodes implement a reinforced learning algorithm to select the most suitable combination of sensors to improve traffic parameters. The paper also introduces a method for calculating traffic density by combining sensors with imprecise data. This research contributes to intelligent traffic management by providing a novel approach to intersection control and traffic density calculation.
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