Mobile ad hoc network (MANET) is a collection of autonomous mobile nodes forming an ad hoc network without fixed infrastructure. Dynamic topology property of MANET may degrade the performance of the network. However, multipath selection is a great challenging task to improve the network lifetime. We proposed an energy-aware multipath routing scheme based on particle swarm optimization (EMPSO) that uses continuous time recurrent neural network (CTRNN) to solve optimization problems. CTRNN finds the optimal loop-free paths to solve link disjoint paths in a MANET. The CTRNN is used as an optimum path selection technique that produces a set of optimal paths between source and destination. In CTRNN, particle swarm optimization (PSO) method is primly used for training the RNN. The proposed scheme uses the reliability measures such as transmission cost, energy factor, and the optimal traffic ratio between source and destination to increase routing performance. In this scheme, optimal loop-free paths can be found using PSO to seek better link quality nodes in route discovery phase. PSO optimizes a problem by iteratively trying to get a better solution with regard to a measure of quality. The proposed scheme discovers multiple loop-free paths by using PSO technique.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4707019PMC
http://dx.doi.org/10.1155/2015/284276DOI Listing

Publication Analysis

Top Keywords

particle swarm
12
swarm optimization
12
loop-free paths
12
energy-aware multipath
8
multipath routing
8
routing scheme
8
scheme based
8
based particle
8
mobile hoc
8
hoc network
8

Similar Publications

This study first proposes an innovative method for optimizing the maximum power extraction from photovoltaic (PV) systems during dynamic and static environmental conditions (DSEC) by applying the horse herd optimization algorithm (HHOA). The HHOA is a bio-inspired technique that mimics the motion cycles of an entire herd of horses. Next, the linear active disturbance rejection control (LADRC) was applied to monitor the HHOA's reference voltage output.

View Article and Find Full Text PDF

Rapid heating cycle molding technology has recently emerged as a novel injection molding technique, with the uniformity of temperature distribution on the mold cavity surface being a critical factor influencing product quality. A numerical simulation method is employed to investigate the rapid heating process of molds and optimize heating power, with the positions of heating rods as variables. The temperature uniformity coefficient is an indicator used to assess the uniformity of temperature distribution within a system or process, while the thermal response rate plays a crucial role in evaluating the heating efficiency of a heating system.

View Article and Find Full Text PDF

Research on Fire Detection of Cotton Picker Based on Improved Algorithm.

Sensors (Basel)

January 2025

College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China.

According to the physical characteristics of cotton and the work characteristics of cotton pickers in the field, during the picking process, there is a risk of cotton combustion. The cotton picker working environment is complex, cotton ignition can be hidden, and fire is difficult to detect. Therefore, in this study, we designed an improved algorithm for multi-sensor data fusion; built a cotton picker fire detection system by using infrared temperature sensors, CO sensors, and the upper computer; and proposed a BP neural network model based on improved mutation operator hybrid gray wolf optimizer and particle swarm optimization (MGWO-PSO) algorithm based on the BP neural network model.

View Article and Find Full Text PDF

Research on Sensitivity Improvement Methods for RTD Fluxgates Based on Feedback-Driven Stochastic Resonance with PSO.

Sensors (Basel)

January 2025

College of Computer Science and Technology, Beihua University, No. 3999 East Binjiang Road, Jilin 132013, China.

With the wide application of Residence Time Difference (RTD) fluxgate sensors in Unmanned Aerial Vehicle (UAV) aeromagnetic measurements, the requirements for their measurement accuracy are increasing. The core characteristics of the RTD fluxgate sensor limit its sensitivity; the high-permeability soft magnetic core is especially easily interfered with by the input noise. In this paper, based on the study of the excitation signal and input noise characteristics, the stochastic resonance is proposed to be realized by adding feedback by taking advantage of the high hysteresis loop rectangular ratio, low coercivity and bistability characteristics of the soft magnetic material core.

View Article and Find Full Text PDF

Research on RTD Fluxgate Induction Signal Denoising Method Based on Particle Swarm Optimization Wavelet Neural Network.

Sensors (Basel)

January 2025

College of Computer Science and Technology, Beihua University, No. 3999 East Binjiang Road, Jilin 132013, China.

Aeromagnetic surveying technology detects minute variations in Earth's magnetic field and is essential for geological studies, environmental monitoring, and resource exploration. Compared to conventional methods, residence time difference (RTD) fluxgate sensors deployed on unmanned aerial vehicles (UAVs) offer increased flexibility in complex terrains. However, measurement accuracy and reliability are adversely affected by environmental and sensor noise, including Barkhausen noise.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!