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Related Experiment Video

Updated: Jul 4, 2025

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
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Enhancing service availability and resource deployment in IoT using a shared service replication method.

Khaled Kaaniche1, Salwa Othmen2, Ayman Alfahid3

  • 1Department of Electrical Engineering, College of Engineering, Jouf University, Sakakah, 72388, Saudi Arabia.

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|February 8, 2024
PubMed
Summary
This summary is machine-generated.

The Shared Replication Augmenting Method (SRAM) optimizes Internet of Things (IoT) resource usage and service availability. This novel approach enhances efficiency in Network Function Virtualization (NFV) environments.

Keywords:
Data availabilityIoTNFVRegression learningResource utilizationService availability

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Information Technology

Background:

  • Internet of Things (IoT) applications require accessible and replicable resources for agility.
  • Network Function Virtualization (NFV) is integrated into IoT to maximize resource utilization and leverage endpoint data.
  • Underutilized Network Functions (NFVs) and service availability are key challenges in IoT environments.

Purpose of the Study:

  • To propose the Shared Replication Augmenting Method (SRAM) for enhancing resource usage in underutilized NFVs.
  • To maintain simultaneous service availability while improving resource utilization within IoT systems.
  • To leverage regressive decision-making learning for detecting NFV data and application portability needs.

Main Methods:

  • The Shared Replication Augmentation Method (SRAM) utilizes regressive decision-making learning to identify NFV data and application portability requirements.
  • SRAM dynamically adjusts procedures, considering computation-less function allocations for interoperable applications.
  • The method distributes virtualization and availability based on historical usage and data replication patterns.

Main Results:

  • SRAM improves resource usage by 7.09% without increasing latency.
  • Service availability is enhanced by 10.4%, while latency is reduced by 11.89%.
  • Backlogs are eliminated by 11.1%, and data repetition is reduced by 8.97%.

Conclusions:

  • SRAM offers a viable solution to enhance resource consumption and productivity in IoT settings.
  • The proposed method effectively reduces data replication, delays, and queues.
  • SRAM significantly increases the overall availability of services in virtualized IoT environments.