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Related Concept Videos

Storage01:23

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A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
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Elastic collision of a system demands conservation of both momentum and kinetic energy. To solve problems involving one-dimensional elastic collisions between two objects, the equations for conservation of momentum and conservation of internal kinetic energy can be used. For the two objects, the sum of momentum before the collision equals the total momentum after the collision. An elastic collision conserves internal kinetic energy, and so the sum of kinetic energies before the collision equals...
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An elastic collision is one that conserves both internal kinetic energy and momentum. Internal kinetic energy is the sum of the kinetic energies of the objects in a system. Truly elastic collisions can only be achieved with subatomic particles, such as electrons striking nuclei. Macroscopic collisions can be very nearly, but not quite, elastic, as some kinetic energy is always converted into other forms of energy such as heat transfer due to friction and sound. An example of a nearly...
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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.
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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:
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The structural behavior of beams under distributed loads is critical for engineering analysis, which focuses on predicting how beams bend and react under such conditions. Different types of beams (e.g., cantilever, supported, or overhanging) behave differently under distributed load conditions.
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Quasi-light Storage for Optical Data Packets
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Store Edge Networked Data (SEND): A Data and Performance Driven Edge Storage Framework.

Adrian-Cristian Nicolaescu1, Spyridon Mastorakis2, Ioannis Psaras1

  • 1University College London.

Proceedings. IEEE INFOCOM
|August 9, 2021
PubMed
Summary
This summary is machine-generated.

Managing edge data is crucial with growing device numbers. The Store Edge Networked Data (SEND) framework intelligently places data at the network edge for efficient processing and retrieval.

Keywords:
Data managementData storage at the edgeEdge computingInternet of Things (IoT)

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Area of Science:

  • Computer Science
  • Network Engineering
  • Data Management

Background:

  • The proliferation of Internet of Things (IoT) devices and edge computing generates massive data volumes.
  • Efficient management and processing of this data at the network edge are critical challenges.

Purpose of the Study:

  • To propose a novel framework, Store Edge Networked Data (SEND), for effective in-network storage management at the network edge.
  • To intelligently place raw and processed data at the edge using system-wide data context identifiers (labels).

Main Methods:

  • Implementation of a data repository prototype on the Google file system.
  • Evaluation using real-world datasets (images, IoT measurements) and network simulations with synthetic and real-world data.
  • Analysis of data placement criteria including data popularity and proximity to edge processing functions.

Main Results:

  • SEND achieves low data insertion times (0.06ms-0.9ms) and lookup times (0.5ms-5.3ms).
  • The framework successfully completes up to 92% of user requests for raw and processed data retrieval.
  • Performance and trade-offs of the SEND design were evaluated through extensive simulations.

Conclusions:

  • The SEND framework offers an efficient solution for managing and processing large volumes of data at the network edge.
  • Intelligent data placement based on labels significantly enhances edge data management capabilities.
  • SEND demonstrates practical viability and scalability for edge data storage and retrieval.