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Related Concept Videos

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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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...
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Distribution Reliability and Automation01:25

Distribution Reliability and Automation

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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
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Machines: Problem Solving II01:30

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
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Machines: Problem Solving I01:22

Machines: Problem Solving I

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A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
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Multimachine Stability01:25

Multimachine Stability

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Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
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Parallel Processing01:20

Parallel Processing

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The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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A Joint Resource Allocation, Security with Efficient Task Scheduling in Cloud Computing Using Hybrid Machine Learning

Prasanta Kumar Bal1, Sudhir Kumar Mohapatra2, Tapan Kumar Das3

  • 1Department of Computer Science and Engineering, GITA Autonomous College, Bhubaneswar 751012, India.

Sensors (Basel, Switzerland)
|February 15, 2022
PubMed
Summary

This study introduces a hybrid machine learning technique (RATS-HM) for efficient cloud resource allocation and task scheduling. It improves performance by optimizing resource utilization and ensuring data security.

Keywords:
NSUPREMERATS-HMcloud computingcloud securitydata storagehybrid machine learningresource allocationtask scheduling

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Area of Science:

  • Cloud Computing
  • Artificial Intelligence
  • Data Security

Background:

  • Cloud environments face challenges in managing massive data and resources due to rapid client growth.
  • Inefficient resource management degrades cloud computing performance, impacting profitability and user satisfaction.
  • Balancing resource allocation for stakeholders is crucial without indefinite request withholding.

Purpose of the Study:

  • To propose a hybrid machine learning (RATS-HM) technique for combined resource allocation security and efficient task scheduling in cloud computing.
  • To enhance cloud performance by optimizing resource allocation and task scheduling.
  • To ensure data security in cloud storage.

Main Methods:

  • An improved cat swarm optimization algorithm-based short scheduler (ICS-TS) for task scheduling to minimize makespan and maximize throughput.
  • A group optimization-based deep neural network (GO-DNN) for efficient resource allocation considering bandwidth and resource load.
  • A lightweight authentication scheme (NSUPREME) for data encryption and storage security.

Main Results:

  • The RATS-HM technique demonstrated superior performance compared to state-of-the-art methods in simulations.
  • Evaluations showed improvements in resource utilization and energy consumption.
  • The proposed method achieved reduced response times.

Conclusions:

  • The RATS-HM technique effectively addresses challenges in cloud resource management and task scheduling.
  • The integration of ICS-TS, GO-DNN, and NSUPREME enhances overall cloud system efficiency and security.
  • The proposed approach offers a promising solution for optimizing cloud computing environments.