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SWIPT-Aware Fog Information Processing: Local Computing vs. Fog Offloading.

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This summary is machine-generated.

This study explores simultaneous wireless information and power transfer (SWIPT) in fog computing. The optimal mode (local or fog offloading) depends on computational complexity, balancing energy harvesting and information rate.

Keywords:
deployment schemeenergy harvestingfog computingfog offloadinglocal computingsimultaneous wireless information and power transfer

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Area of Science:

  • Wireless communication
  • Energy harvesting
  • Fog computing

Background:

  • Simultaneous wireless information and power transfer (SWIPT) enables devices to harvest energy and receive data wirelessly.
  • Fog computing offers distributed computation closer to data sources, reducing latency.
  • Integrating SWIPT with fog computing presents challenges in resource allocation and mode selection.

Purpose of the Study:

  • To investigate SWIPT-aware fog computing systems with a power splitting (PS) receiver.
  • To analyze two information processing modes: local computing and fog offloading.
  • To minimize sensor power consumption while meeting information rate and energy harvesting constraints.

Main Methods:

  • Formulated two optimization problems for local computing and fog offloading modes.
  • Jointly optimized time assignment, transmit power, and power splitting (PS) ratio.
  • Derived closed-form and semi-closed-form solutions using convex optimization theory.

Main Results:

  • Neither local computing nor fog offloading is universally superior.
  • Local computing is preferred when computational complexity per bit is low.
  • Fog offloading is favored for higher computational complexity per bit.

Conclusions:

  • The optimal mode selection in SWIPT-aware fog computing is context-dependent.
  • Computational complexity per bit is a critical factor in mode selection.
  • User position relative to the hybrid access point (HAP) and fog server (FS) influences optimal mode choice.