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Randomized Experiments01:13

Randomized Experiments

8.5K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
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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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Random Sampling Method01:09

Random Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
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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:
274
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

886
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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Distributed Loads01:19

Distributed Loads

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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...
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Related Experiment Video

Updated: Nov 10, 2025

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
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Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

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Randomized routing of virtual machines in IaaS data centers.

Hadi Khani1, Hamed Khanmirza2

  • 1Department of Engineering, Islamic Azad University Garmsar Branch, Garmsar, Semnan, Iran.

Peerj. Computer Science
|April 5, 2021
PubMed
Summary

Randomly assigning virtual machines (VMs) to physical machines (PMs) in cloud data centers minimizes power consumption. This approach balances energy use and quality of service for dynamic workloads.

Keywords:
Cloud computingEnergy consumptionOptimizationPlacementService level agreementVirtualization

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Operations Research

Background:

  • Cloud computing offers cost-effective, on-demand resources via virtual machines (VMs) on physical machines (PMs).
  • Large-scale data centers experience dynamic, unpredictable workloads requiring efficient resource management.
  • Balancing power consumption and quality of service is critical for VM placement.

Purpose of the Study:

  • To develop an analytical model for VM assignment in large-scale cloud data centers.
  • To determine the optimal VM assignment strategy for minimizing power consumption while maintaining quality of service.

Main Methods:

  • Developed an analytical model for VM assignment in large cloud data centers.
  • Calculated mean power consumption for exponential VM arrivals and general sojourn times.
  • Analyzed VM assignment strategies focusing on load-independent placement.

Main Results:

  • An analytical model was developed for large-scale cloud data centers.
  • Randomized VM assignment was shown to minimize power consumption under quality of service constraints.
  • Extensive simulations validated the analytical model's findings.

Conclusions:

  • Randomized VM assignment is an effective strategy for optimizing energy efficiency in cloud data centers.
  • The proposed analytical model provides a framework for managing resources in large-scale cloud environments.
  • Balancing power consumption and quality of service can be achieved through intelligent VM placement.