Energy-Efficient Adaptive Sensing Scheduling in Wireless Sensor Networks Using Fibonacci Tree Optimization Algorithm

Wu, Liangshun; Cai, Hengjin

doi:10.3390/s21155002

Cited by 7 publications

(4 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Fibonacci method and its variations, such as Fibonacci multi-modal optimization [35] and Fibonacci tree optimization (MTO) [36], are efficient and accurate search algorithms based on Fibonacci sequences, and they conform to the following principle.…”

Section: Parameter Estimation Algorithm-multi-dimensional Fibonacci O...mentioning

confidence: 99%

Improved bond graph model for fault diagnosis under uncertain conditions

Chen

Fan

Zhong

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

The effectiveness of model-based diagnosis is strongly dependent on the authenticity of the model and is influenced by various uncertainties. Measurement uncertainty is governed by the probability method and parameter uncertainty can be handled by the linear fractional transformation (LFT) while structure uncertainty and errors are rarely considered. In this paper, an improved bond graph (BG) model is proposed, which adopts subsystems to substitute modelling errors, namely parameter uncertainty and structure uncertainty. Multi-dimensional Fibonacci optimization algorithm (MFO) is developed to identify parameters in subsystems to obtain subsystem-based diagnostic hybrid bond graph (SDHBG) model. Fault diagnosis is realized by comparing the residuals and thresholds derived from the SDHBG. Experiments are conducted to validate the key concepts of the proposed methods and the results suggest the effectiveness.

show abstract

Section: Parameter Estimation Algorithm-multi-dimensional Fibonacci O...mentioning

confidence: 99%

Improved bond graph model for fault diagnosis under uncertain conditions

Chen

Fan

Zhong

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…In [25], a new strategy named Fibonacci tree Optimization (FTOS) is proposed to cater the problem of task scheduling in wireless sensor based network. It outperforms in term of energy consumption as compared to differential evolution (DE), PSO and Artificial Bee Colony (ABC).…”

Section: Literature Reviewmentioning

confidence: 99%

A Performance Constrained Metaheuristic Algorithm for 2D Mesh Based NoC

Khurshid

Baig

2023

ICAENS

View full text Add to dashboard Cite

Integrating large number of Intellectual Property (IP) cores onto a single chip has been made possible with the technology scaling and shrinking in the size of transistors. This has led designers to create a scalable and flexible on-chip network infrastructure – Network on Chip (NoC). Mapping application graphs on multiple cores of NoC architecture is one of the challenging research problems. The all in all performance of NoC network depends primarily on an efficient and cost-effective mapping technique which optimizes several performance metrics. These metrics primarily consists of communication cost, energy, throughput, latency, power dissipation and simulation time. A metaheuristic state-of-the-art nature inspired mapping approach for NoC's called Hunger Games Search Algorithm (HGSA) has been introduced in this research work. The devised algorithm minimizes NoC energy and power consumption based on six standard available embedded application benchmarks. Experimental results demonstrate that the presented technique outperforms as compared to other existing nature-inspired meta-heuristic application mapping approaches.

show abstract

“…In [12], Wu and Cai presented a Fibonacci tree optimization strategy (FTOS) for the scheduling query of wireless sensor networks. The proposed algorithm provided less energy consumption and optimization of detection efficiency.…”

Section: Related Workmentioning

confidence: 99%

An Optimized Nature-Inspired Metaheuristic Algorithm for Application Mapping in 2D-NoC

Sikandar

Baloch

Hussain

et al. 2021

Sensors

View full text Add to dashboard Cite

Mapping application task graphs on intellectual property (IP) cores into network-on-chip (NoC) is a non-deterministic polynomial-time hard problem. The evolution of network performance mainly depends on an effective and efficient mapping technique and the optimization of performance and cost metrics. These metrics mainly include power, reliability, area, thermal distribution and delay. A state-of-the-art mapping technique for NoC is introduced with the name of sailfish optimization algorithm (SFOA). The proposed algorithm minimizes the power dissipation of NoC via an empirical base applying a shared k-nearest neighbor clustering approach, and it gives quicker mapping over six considered standard benchmarks. The experimental results indicate that the proposed techniques outperform other existing nature-inspired metaheuristic approaches, especially in large application task graphs.

show abstract

Energy-Efficient Adaptive Sensing Scheduling in Wireless Sensor Networks Using Fibonacci Tree Optimization Algorithm

Cited by 7 publications

References 40 publications

Improved bond graph model for fault diagnosis under uncertain conditions

Improved bond graph model for fault diagnosis under uncertain conditions

A Performance Constrained Metaheuristic Algorithm for 2D Mesh Based NoC

An Optimized Nature-Inspired Metaheuristic Algorithm for Application Mapping in 2D-NoC

Contact Info

Product

Resources

About