Joint Latency-Energy Minimization for Fog-Assisted Wireless IoT Networks

This work aims to present a joint resource allocation method for a fog-assisted network wherein IoT wireless devices simultaneously offload their tasks to a serving fog node. The main contribution is to formulate joint minimization of service latency and energy consumption objectives subject to both radio and computing constraints. Moreover, unlike previous works that set a fixed value to the circuit power dissipated to operate a wireless device, practical models are considered. To derive the Pareto boundary between two conflicting objectives we consider, Tchebyshev theorem is used for each wireless device. The interactions among IoT devices are represented through a cooperative Nash bargaining framework, with the unique Nash equilibrium (NE) being computed via a block coordinate descent method. Numerical results obtained using realistic models are presented to corroborate the effectiveness of the proposed algorithm.

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Publication Details

Journal
IEEE Open Journal of the Communications Society
Published
2024-12-25
DOI
https://doi.org/10.1109/ojcoms.2024.3522256
Citations
2
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
0.70
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article

Joint Latency-Energy Minimization for Fog-Assisted Wireless IoT Networks

Vincenzo Lottici, Farshad Shams, Zhi Tian
2 citations
IEEE Open Journal of the Communications Society
Energy Efficient Wireless Sensor Networks
0.70
article

Joint Latency-Energy Minimization for Fog-Assisted Wireless IoT Networks

Vincenzo Lottici, Farshad Shams, Zhi Tian
article en
2 citations

Abstract

This work aims to present a joint resource allocation method for a fog-assisted network wherein IoT wireless devices simultaneously offload their tasks to a serving fog node. The main contribution is to formulate joint minimization of service latency and energy consumption objectives subject to both radio and computing constraints. Moreover, unlike previous works that set a fixed value to the circuit power dissipated to operate a wireless device, practical models are considered. To derive the Pareto boundary between two conflicting objectives we consider, Tchebyshev theorem is used for each wireless device. The interactions among IoT devices are represented through a cooperative Nash bargaining framework, with the unique Nash equilibrium (NE) being computed via a block coordinate descent method. Numerical results obtained using realistic models are presented to corroborate the effectiveness of the proposed algorithm.

IEEE Open Journal of the Communications SocietyVol. 6
University of Pisa (IT), George Mason University (US)
Affordable and clean energy
Openalex Percentile: Top 26%
Energy Efficient Wireless Sensor Networks
0.70
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Joint Latency-Energy Minimization for Fog-Assisted Wireless IoT Networks — Vincenzo Lottici, Farshad Shams, et al. · IEEE Open Journal of the Communications Society (2024) | TGRS Research Map | TGRS