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Related Concept Videos

Frames01:30

Frames

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Frames are essential components of various mechanical and structural systems used daily. These structures are known for their stability and ability to bear heavy loads. A frame is constructed using two-force and multi-force members, interconnected using pin joints. In contrast, trusses are made entirely of two-force members.
Frames are versatile and widely used in various applications such as structural supports for beams and columns, automobile chassis construction, and in the construction...
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Frames: Problem Solving I01:24

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Consider a jib crane with an external load suspended from the pulley. The dimensions of the crane members are shown in the figure. A systematic analysis of the frame structure is required to determine the reaction forces at the pin joints, assuming that the pulleys are frictionless.
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Control Systems: Applications01:25

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Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
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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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Frames: Problem Solving II01:26

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Consider a hydraulic hoist supporting a load of 1 kN. Assuming a simplified schematic representation of this frame structure, the force acting on BD and BF members can be determined.
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Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
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Updated: Oct 26, 2025

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FogFrame: a framework for IoT application execution in the fog.

Olena Skarlat1, Stefan Schulte1

  • 1Distributed Systems Group, Technische Universität Wien, Vienna, Austria.

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Summary

FogFrame is a new framework for managing Internet of Things (IoT) applications in fog computing environments. It efficiently places services on edge and cloud resources, improving deployment times and resource utilization.

Keywords:
Fog computingInternet of ThingsResource provisioningService placement

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Area of Science:

  • Computer Science
  • Distributed Systems
  • Cloud Computing

Background:

  • Existing fog computing research lacks practical frameworks for real-world implementation.
  • Managing edge and cloud resources for Internet of Things (IoT) applications presents significant challenges.

Purpose of the Study:

  • To design and implement FogFrame, a concrete framework for managing and monitoring fog computing landscapes.
  • To enable decentralized service placement, deployment, and execution for IoT applications within fog environments.

Main Methods:

  • Formalized a system model for service placement with an objective function and constraints.
  • Implemented greedy and genetic algorithms for decentralized service placement.
  • Evaluated FogFrame using a real-world testbed, focusing on Quality of Service and resource utilization.

Main Results:

  • FogFrame adapts service placement to demand and available resources.
  • Greedy placement maximizes edge utilization; genetic algorithm balances cloud/edge to prevent overload.
  • Edge service deployment is 14% faster than cloud deployment.
  • Genetic algorithm accommodates new applications better, maintaining ~50% CPU utilization on edge devices.

Conclusions:

  • FogFrame effectively manages fog landscapes and executes IoT applications.
  • The genetic algorithm offers superior adaptability for new applications and load balancing.
  • The framework demonstrates robust reaction to runtime events like device failures and overloads through service migration.