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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
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Short-distance Transport of Resources02:12

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Updated: Oct 13, 2025

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Infrastructure as Software in Micro Clouds at the Edge.

Miloš Simić1, Goran Sladić1, Miroslav Zarić1

  • 1Faculty of Technical Sciences, University of Novi Sad, Trg D. Obradovića 6, 21000 Novi Sad, Serbia.

Sensors (Basel, Switzerland)
|November 13, 2021
PubMed
Summary
This summary is machine-generated.

Edge computing dynamically organizes geo-distributed nodes into micro clouds, enabling "infrastructure as software" for real-time applications. This model adapts cloud principles for efficient, location-aware resource management at the edge.

Keywords:
cloud computingdistributed systemsedge computinginfrastructure as codeinfrastructure as softwaremicro cloudsmicro data centers

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Area of Science:

  • Computer Science
  • Distributed Systems
  • Cloud Computing

Background:

  • Edge computing brings cloud services closer to users, enabling new applications but posing challenges in geo-distributed resource management.
  • Real-time applications necessitate multi-tier infrastructure for local data preprocessing and cloud-based heavy computation.

Purpose of the Study:

  • To present a model for dynamically organizing geo-distributed edge nodes into flexible micro clouds.
  • To enable resource reorganization for optimal service delivery based on population needs and location advantages.

Main Methods:

  • Adapting cloud organization principles for edge environments.
  • Developing a descriptive model for specifying desired infrastructure states.
  • Implementing dynamic resource reorganization for elasticity.

Main Results:

  • A model capable of organizing geo-distributed nodes into adaptive micro clouds.
  • Abstraction of edge infrastructure to a software level, enabling "infrastructure as software" at the edge.
  • Demonstration of elasticity through dynamic resource reorganization.

Conclusions:

  • The proposed model facilitates efficient management of geo-distributed edge resources.
  • Enabling "infrastructure as software" at the edge is crucial for future real-time applications.
  • The model can be integrated with existing tools, allowing cloud providers to offer micro clouds as a service.