Novel reliable and dynamic energy-aware routing protocol for large scale wireless sensor networks

Abstract

<p>Wireless sensor networks (WSN) are made up of an important number of sensors, called nodes, distributed in random way in a concerned monitoring area. All sensor nodes in the network are mounted with limited energy sources, which makes energy harvesting on top of the list of issues in WSN. A poor communication architecture can result in excessive consumption, reducing the network lifetime and throughput. Centralizing data collection and the introduction of gateways (GTs), to help cluster heads (CHs), improved WSN life time significantly. However, in vast regions, misplacement and poor distribution of GTs wastes a huge amount of energy and decreases network’s performances. In this work, we describe a reliable and dynamic with energy-awareness routing (RDEAR) protocol that provides a new GT’s election approach taking into consideration CHs density, transmission distance and energy. Applied on 20 different networks, RDEAR reduced the overall energy consumption, increased stability zone and network life time as well as other compared metrics. Our proposed approach increased network’s throughput up to 75.92% , 67.7% and 9.78% compared to the low energy adaptive clustering hierarchy (LEACH), distributed energy efficient clustering (DEEC) and static multihop routing (SMR), protocols, respectively.</p>

Power Efficiency Optimization and Enhanced Connectivity for Wireless Sensor Networks with the Fuzzy C-Means 3D Model

“…Furthermore, our model's adaptive nature, featuring an efficient one-hop communication protocol, and a systematic rotation mechanism for Cluster Heads based on residual power, promises sustained efficiency and adaptability. The results of this research not only set new benchmarks for Wireless Sensor Networks, but also offer a roadmap for future studies [11][12]. As technology continues to evolve, the strategies and methodologies presented in this paper will serve as a foundational guide, ensuring that Wireless Sensor Networks are not just efficient but also sustainable and adaptable to the ever-changing requirements of real-world applications.…”

“…From the solutions of the problem (11,12,14), we propose a better clustering algorithm named Fuzzy C-Means (FCM) [6] for 3D WUSN named FCM-3WUSN described in Algorithm 1. The purpose of extending the lifetime of the WUSN [9] is to optimize the energy consumption of the sensors in the local cluster and communicate with the CHs-BS.…”

“…Other authors [7][8][9] showed various machine learning techniques suitable for energy-efficient routing using WSN. Furthermore, other researchers [9][10][11][12] propose current SDN or IoT trending technology uses Wireless Sensor Network.…”

A review of the state of art and prospects in energy storage systems for energy harvesting applications

“…It covers a wide range of issues, including power quality maintenance, power system protection, and energy management, etc. [80], [44]- [46]. Table 2 summarizes the selected and promising EES options for various service applications with suitable characteristics.…”

“…The demand for energy has been increasing due to the rapid development of industry and modern technologies. Energy harvesting is a technique that captures, harvests, or scavenges various unused or ambient sources of energy e.g., sun, heat, vibration, and wind, into electrical energy [1]- [44]. Sources for energy harvesting are divided into large scales such as solar PV [6], [13], [15], [33], [39], [45], [46], wind [46]- [50], tidal [30], [51], and geothermal [35], [40], [52], [53], and then on a small scale such as electromagnetic [6], [9], [32], mechanical [19], [37], [54], [55], and heat [2], [15], [24], [56], [57].…”