scholarly journals Energy Optimization in a Multihop Sensor Network for a WBAN Application

2021 ◽  
Vol 25 (1) ◽  
pp. 3-10
Author(s):  
Vishakha Tyagi ◽  
◽  
Sindhu Hak Gupta ◽  
Monica Kaushik ◽  
◽  
...  

Movement and posture change of human body plays a crucial role in energy consumption while data transmission between strategically deployed nodes in wireless body area networks (WBANs). The majority of energy is used in transmission rather than processing of the data. Nodes within body are there for long time and need to be energy efficient so that the network lifetime is increased. In this paper, we propose an energy efficient data transmission for multi-hop network that uses particle swarm optimization (PSO) for optimizing the parameters on which energy consumption relies. An energy efficient data transmission and reception takes place by altering the parameters like node to node distance and packet size of data. The obtained results show a significant reduction of energy consumed by reducing the packet size and keeping the node-to-sink distance a constant value. The total energy consumed per hop per bit length of data packet Emh/L shows 75% optimization. The energy consumed in data transmission per bit length of data E tx /L and the energy consumed for data received per bit length of data packet E rx /L is optimized by approximately 70% and 50% respectively for hope count 2 to 5.

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 2024
Author(s):  
Seyed Ahmad Soleymani ◽  
Shidrokh Goudarzi ◽  
Nazri Kama ◽  
Saiful Adli Ismail ◽  
Mazlan Ali ◽  
...  

Energy consumption because of unnecessary data transmission is a significant problem over wireless sensor networks (WSNs). Dealing with this problem leads to increasing the lifetime of any network and improved network feasibility for real time applications. Building on this, energy-efficient data collection is becoming a necessary requirement for WSN applications comprising of low powered sensing devices. In these applications, data clustering and prediction methods that utilize symmetry correlations in the sensor data can be used for reducing the energy consumption of sensor nodes for persistent data collection. In this work, a hybrid model based on decision tree (DT), autoregressive integrated moving average (ARIMA), and Kalman filtering (KF) methods is proposed to predict the data sampling requirement of sensor nodes to reduce unnecessary data transmission. To perform data sampling predictions in the WSNs efficiently, clustering and data aggregation to each cluster head are utilized, mainly to reduce the processing overheads generating the prediction model. Simulation experiments, comparisons, and performance evaluations conducted in various cases show that the forecasting accuracy of our approach can outperform existing Gaussian and probabilistic based models to provide better energy efficiency due to reducing the number of packet transmissions.


2016 ◽  
Vol 6 (2) ◽  
pp. 931-936 ◽  
Author(s):  
Y. Emami ◽  
R. Javidan

Energy is a precious resource in underwater wireless sensor networks (UWSNs). In these networks, the number of data transmissions between sensor nodes dominates energy consumption. Complex signal processing techniques also increase energy consumption. In this paper an energy-efficient data transmission scheme based on bloom filters is proposed. Extensive simulation is carried out to demonstrate the effectiveness of the proposed method. Simulation results indicate that the proposed scheme outperforms the primary technique in terms of energy efficiency, lifetime, load and loss rate. The results of this research suggest that exploiting bloom filters is a viable solution for reducing the number of transmissions in UWSNs.


2020 ◽  
Author(s):  
Ademola Abidoye ◽  
Boniface Kabaso

Abstract Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the 21st century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize energy consumption of sensor nodes so as to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called Energy-Efficient Hierarchical routing protocol for wireless sensor networks based on Fog Computing (EEHFC). Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of Things applications. In addition, we propose an improved ant colony optimization (ACO) algorithm that can be used to construct optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses and extends the network lifetime


Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4238
Author(s):  
Yating Qu ◽  
Guoqiang Zheng ◽  
Honghai Wu ◽  
Baofeng Ji ◽  
Huahong Ma

Wireless body area networks will inevitably bring tremendous convenience to human society in future development, and also enable people to benefit from ubiquitous technological services. However, one of the reasons hindering development is the limited energy of the network nodes. Therefore, the energy consumption in the selection of the next hop must be minimized in multi-hop routing. To solve this problem, this paper proposes an energy efficient routing protocol for reliable data transmission in a wireless body area network. The protocol takes multiple parameters of the network node into account, such as residual energy, transmission efficiency, available bandwidth, and the number of hops to the sink. We construct the maximum benefit function to select the next hop node by normalizing the node parameters, and dynamically select the node with the largest function value as the next hop node. Based on the above work, the proposed method can achieve efficient multi-hop routing transmission of data and improve the reliability of network data transmission. Compared with the priority-based energy-efficient routing algorithm (PERA) and modified new-attempt routing protocol (NEW-ATTEMPT), the simulation results show that the proposed routing protocol uses the maximum benefit function to select the next hop node dynamically, which not only improves the reliability of data transmission, but also significantly improves the energy utilization efficiency of the node and prolongs the network lifetime.


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