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Related Concept Videos

Distributed Loads01:19

Distributed Loads

576
Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
576
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

157
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.
157
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

692
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...
692
Relation Between the Distributed Load and Shear01:23

Relation Between the Distributed Load and Shear

737
Understanding the relationship between the distributed load and shear force in structural analysis is crucial for analyzing beams subjected to various loading conditions. Consider the case of a beam experiencing a distributed load, two concentrated loads, and a couple moment.
737
Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

306
The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
306
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

87
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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A sustainable and secure load management model for green cloud data centres.

Deepika Saxena1,2, Ashutosh Kumar Singh3, Chung-Nan Lee4

  • 1Department of Computer Applications, National Institute of Technology, Kurukshetra, Haryana, 136119, India. 13deepikasaxena@gmail.com.

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This study introduces a Sustainable and Secure Load Management (SaS-LM) model for Cloud Data Centres (CDCs). The SaS-LM model significantly reduces carbon emissions and energy consumption while improving resource utilization.

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Area of Science:

  • Cloud Computing
  • Data Centre Sustainability
  • Network Security

Background:

  • Cloud Data Centres (CDCs) face challenges with increasing resource demand, leading to high energy consumption, carbon emissions, and security risks.
  • Inefficient load management in CDCs compromises sustainability and operational efficiency.

Purpose of the Study:

  • To propose a novel Sustainable and Secure Load Management (SaS-LM) model for enhancing CDC security and sustainability.
  • To dynamically manage and reserve compute, network, and storage resources for optimal performance and reduced environmental impact.

Main Methods:

  • Developed a Sustainable and Secure Load Management (SaS-LM) model.
  • Proposed the Dual-Phase Black Hole Optimization (DPBHO) algorithm to optimize neural networks for resource estimation and congestion detection.
  • Extended DPBHO to a Multi-objective DPBHO for secure and sustainable Virtual Machine (VM) allocation and management.

Main Results:

  • The SaS-LM model demonstrated significant reductions in carbon emission (up to 46.9%) and energy consumption (up to 43.9%).
  • Achieved improved resource utilization by up to 16.5%.
  • Effectively minimized active server machines, carbon emissions, and resource wastage.

Conclusions:

  • The proposed SaS-LM model, utilizing the DPBHO algorithm, offers an effective solution for greener and more secure Cloud Data Centres.
  • The model successfully balances security and sustainability requirements in dynamic cloud environments.