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An Intelligent Data Uploading Selection Mechanism for Offloading Uplink Traffic of Cellular Networks.

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  • 1College of Computer Science, Beijing University of Technology, Beijing 100124, China.

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Summary

This study introduces an Intelligent Data Uploading Selection Mechanism (IDUSM) for mobile crowd sensing. IDUSM effectively balances cellular offloading and user costs by predicting mobility and reducing data redundancy.

Keywords:
mobile crowd sensing applicationsmobility predictionopportunistic communicationsuplink traffic offloading

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Area of Science:

  • Computer Science
  • Wireless Communication
  • Mobile Computing

Background:

  • Mobile crowd sensing (MCS) generates significant cellular traffic.
  • Existing Wi-Fi offloading schemes optimize either traffic offload or cost, not both.
  • Need for efficient data uploading strategies in MCS.

Purpose of the Study:

  • To propose an Intelligent Data Uploading Selection Mechanism (IDUSM).
  • To achieve a trade-off between cellular traffic offloading and user uploading costs.
  • To optimize Wi-Fi offloading considering individual data plans and transmission types.

Main Methods:

  • Developed a probability prediction model for participant mobility using spatial and temporal data.
  • Implemented a mechanism to select optimal data uploading methods.
  • Reduced data redundancy during Wi-Fi offloading to conserve user resources.
  • Simulated and evaluated IDUSM performance against existing schemes.

Main Results:

  • IDUSM achieved the highest offloading efficiency (56.54×10⁻⁷).
  • Achieved an offloading ratio of 52.1% and an uploading cost of (6.79×10³).
  • Demonstrated a superior trade-off between offloading ratio and uploading cost compared to other mechanisms.

Conclusions:

  • IDUSM effectively balances cellular offloading and user costs in MCS.
  • The probability prediction model enhances mobility prediction for better offloading decisions.
  • IDUSM conserves user resources by minimizing data redundancy during Wi-Fi offloading.