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相关概念视频

Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

131
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
131
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

229
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
229
Energy and Power Signals01:17

Energy and Power Signals

322
In an electrical system with a resistor, voltage and current signals facilitate the measurement of power and energy across the resistor. For a continuous-time signal, the total energy over a time interval is defined as the integral of the square of the signal's magnitude over that interval. Mathematically, this is expressed as:
322
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

666
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
666
Maximum Power Transfer01:16

Maximum Power Transfer

278
Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...
278
Electrical Energy01:10

Electrical Energy

1.2K
Using electric appliances for a longer period of time consumes more electrical energy and results in a higher electric bill. The energy produced by the transfer of electrons from one point to another is known as electrical energy. If power is delivered at a constant rate, the electrical energy can be defined as the product of power used by the device for a period of time. The energy unit on electric bills is the kilowatt-hour, where one kilowatt-hour is equivalent to 3.6 × 106 joules.
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Updated: Jul 15, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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通过深度学习和软件定义网络来管理具有多连接性的设备的能源消耗.

Ramiza Shams1, Atef Abdrabou1, Mohammad Al Bataineh1,2

  • 1Department of Electrical and Communication Engineering, College of Engineering, United Arab Emirates University, Al-Ain P.O. Box 15551, Abu Dhabi, United Arab Emirates.

Sensors (Basel, Switzerland)
|September 28, 2023
PubMed
概括

本研究介绍了一种使用软件定义网络和深度神经网络来管理多连接设备的能源消耗的新方法. 这种方法有效地减少了电力消耗,同时提高了5G和超越无线网络的网络性能.

关键词:
拥堵控制 拥堵控制能源消耗 能源消耗是指能源的消耗.多重连接性多重连接性多个家庭的多个家庭.多路径的TCP是多路径的.神经网络的神经网络的神经网络软件定义网络是软件定义的网络.无线无线无线无线无线无线

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科学领域:

  • 计算机科学 计算机科学
  • 电气工程 电气工程
  • 电信 电信服务 电信服务 电信服务

背景情况:

  • 多连接性使同时连接到多个无线电接入技术 (5G,4G LTE,WiFi) 成为可能,这对于满足不断增长的移动数据需求至关重要.
  • 多路径TCP (MPTCP) 便于在这些多样化的链路上可靠的数据传输,但增加了电池驱动设备的能源消耗.
  • 在多家无线设备中管理能效是当前和未来移动网络面临的重大挑战.

研究的目的:

  • 开发和评估使用MPTCP的多连接设备的能源管理策略.
  • 利用软件定义网络 (SDN) 和深度神经网络 (DNN) 来优化能源消耗.
  • 为了提高网络吞吐量性能,并节省能源.

主要方法:

  • 在SDN控制器上实现两个轻量级算法,用于管理多连接.
  • 使用一个硬件测试台与双主机无线节点连接到WiFi和蜂网络.
  • 使用在各种网络场景中训练有素的DNN来改进网络连接决策.

主要成果:

  • 拟议的基于SDN和DNN的方法显著降低了设备的能耗.
  • 与单路TCP和标准MPTCP算法 (Cubic,BALIA) 相比,该方法实现了改进的网络吞吐量性能.
  • 实验验证证明了算法的有效性在现实世界双主机网络环境中.

结论:

  • SDN和DNN集成为管理多连接设备的能源消耗提供了有效的解决方案.
  • 开发的算法为优化5G和未来无线网络资源利用提供了实用方法.
  • 这种方法平衡了高性能需求与移动设备能源效率的关键要求.