Transaction Throughput Maximization under Delay and Energy Constraints in Fog-IoT Networks

Abkenar, Forough Shirin; Alam, Zahangir; Jamalipour, Abbas

doi:10.1109/globecom42002.2020.9348186

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…b) Offloading energy model: The energy consumption for offloading a task to the corresponding UAV-FN depends on the transmit power, as well as the transmission rate of a TN, which is given as [35], [37]…”

Section: Energy Modelmentioning

confidence: 99%

ENERGENT: An energy-efficient UAV-assisted fog-IoT framework for disaster management

et al. 2022

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In this paper, we propose ENergy-efficient disastER manaGmENT (ENERGENT) as a novel framework for disaster management in the unmanned aerial vehicle (UAV)-assisted Fog-Internet of things (IoT) networks. ENERGENT optimizes the energy consumption of the terminal nodes (TNs), as well as the UAVs, using three proposed algorithms. The first algorithm optimally adjusts the 3D placement of the UAVs such that these nodes consume the minimum energy to reach the desired cluster of the TNs. Besides, the transmit power and the transmission rate of the TNs are set in a way that their energy consumption is minimized and the outage probability requirements are met in the network. In the second algorithm, we propose an optimal task offloading scheme where tasks are offloaded to the UAVs in order to meet the network delay constraints. Finally, the third algorithm takes advantage of wireless power transfer to transfer energy to the TNs when their remaining energy degrades a predefined threshold. This scheme guarantees a minimum throughput for all TNs within a cluster by which the total network throughput is maximized. Simulation results reveal that ENERGENT outperforms the existing methods in terms of optimized network energy consumption, delay, and throughput.

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Section: Energy Modelmentioning

confidence: 99%

ENERGENT: An energy-efficient UAV-assisted fog-IoT framework for disaster management

et al. 2022

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“…The efficiency of the Fog-IoT networks is not only limited to energy consumption and delay. Two different methods, one based on the optimization problem and the other based on reinforcement learning (RL) mechanism, are proposed in [9] to improve the throughput of Fog-IoT networks. Ramezani et al propose mechanisms to improve the network throughput in energy harvesting (EH) [10], and backscattering [11].…”

Section: Introductionmentioning

confidence: 99%

Efficient Task Allocation Protocol for a Hybrid-Hierarchical Spatial-Aerial-Terrestrial Edge-Centric IoT Architecture

Jamalipour

Abkenar

2022

IEICE Trans. Commun.

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In this paper, we propose a novel Hybrid-Hierarchical spatial-aerial-Terrestrial Edge-Centric (H 2 TEC) for the space-air integrated Internet of Things (IoT) networks. (H 2 TEC) comprises unmanned aerial vehicles (UAVs) that act as mobile fog nodes to provide the required services for terminal nodes (TNs) in cooperation with the satellites. TNs in (H 2 TEC) offload their generated tasks to the UAVs for further processing. Due to the limited energy budget of TNs, a novel task allocation protocol, named TOP, is proposed to minimize the energy consumption of TNs while guaranteeing the outage probability and network reliability for which the transmission rate of TNs is optimized. TOP also takes advantage of the energy harvesting by which the low earth orbit satellites transfer energy to the UAVs when the remaining energy of the UAVs is below a predefined threshold. To this end, the harvested power of the UAVs is optimized alongside the corresponding harvesting time so that the UAVs can improve the network throughput via processing more bits. Numerical results reveal that TOP outperforms the baseline method in critical situations that more power is required to process the task. It is also found that even in such situations, the energy harvesting mechanism provided in the TOP yields a more efficient network throughput.

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Joint Cache and Computation Resource Optimization in Fog Radio Access Networks

Yang

Yuan

et al. 2022

2022 International Symposium on Sensing and Instrumentation in 5G and IoT Era (ISSI)

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Transaction Throughput Maximization under Delay and Energy Constraints in Fog-IoT Networks

Cited by 4 publications

References 17 publications

ENERGENT: An energy-efficient UAV-assisted fog-IoT framework for disaster management

ENERGENT: An energy-efficient UAV-assisted fog-IoT framework for disaster management

Efficient Task Allocation Protocol for a Hybrid-Hierarchical Spatial-Aerial-Terrestrial Edge-Centric IoT Architecture

Joint Cache and Computation Resource Optimization in Fog Radio Access Networks

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