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...

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Published inIEEE open journal of the Communications Society Vol. 6; pp. 516 - 530
Main Authors Shams, Farshad, Lottici, Vincenzo, Tian, Zhi
Format Journal Article
LanguageEnglish
Published New York IEEE 2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Bi-objective optimization
Computational modeling
Energy consumption
fog-assisted networks
Integrated circuit modeling
Internet of Things
IoT
joint resource allocation
Linear programming
NBS
Network latency
Optimization
Pareto boundary
Power demand
Resource allocation
Resource management
Tchebyshev method
Wireless communication
Wireless networks
Wireless sensor networks
Online AccessGet full text
ISSN2644-125X
2644-125X
DOI10.1109/OJCOMS.2024.3522256

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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.
AbstractList 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.
Author Tian, Zhi
Lottici, Vincenzo
Shams, Farshad
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  surname: Tian
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  organization: Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA
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Snippet 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...
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SubjectTerms Algorithms
Bi-objective optimization
Computational modeling
Energy consumption
fog-assisted networks
Integrated circuit modeling
Internet of Things
IoT
joint resource allocation
Linear programming
NBS
Network latency
Optimization
Pareto boundary
Power demand
Resource allocation
Resource management
Tchebyshev method
Wireless communication
Wireless networks
Wireless sensor networks
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Title Joint Latency-Energy Minimization for Fog-Assisted Wireless IoT Networks
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