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Optimizing storage on fog computing edge servers: A recent algorithm design with minimal interference.

Xumin Zhao1,2,3, Guojie Xie2, Yi Luo1,2

  • 1Zhejiang Yuexiu University, Shaoxing, China.

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A new algorithm, Low Interference Recently Used (LIRU), optimizes edge server storage in fog computing. LIRU enhances data access efficiency and reduces latency, improving overall system performance.

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Area of Science:

  • Computer Science
  • Distributed Systems
  • Cloud Computing

Background:

  • Fog computing leverages edge servers for distributed data processing and storage.
  • Optimizing storage capacity on edge servers is critical for fog computing efficiency.
  • Existing algorithms like LRU and LFU have limitations in constrained storage environments.

Purpose of the Study:

  • To develop a novel storage optimization algorithm for fog computing edge servers.
  • To enhance storage utilization, data access efficiency, and reduce access latency.
  • To address the challenges posed by limited storage resources in fog infrastructures.

Main Methods:

  • Developed the Low Interference Recently Used (LIRU) algorithm, combining LIRS and LRU principles.
  • Analyzed edge server storage resources, focusing on utilization and access frequency.
  • Constructed an optimization model harmonizing data frequency with cache capacity.

Main Results:

  • LIRU demonstrated superior performance over conventional algorithms like LRU and LFU.
  • Achieved a 66% enhancement in hit ratio over LRU and a 5% increment over LFU.
  • Reduced average system response time by up to 16.5% compared to LRU and LFU.

Conclusions:

  • The LIRU algorithm significantly improves storage utilization and data access efficiency in fog computing.
  • This research offers a valuable framework for data management in fog computing architectures.
  • The findings contribute to advancing the performance and efficiency of the fog computing ecosystem.