Energy Aware Opportunistic Routing for Energy Harvesting Wireless Sensor Networks

Li, Yuanyang; He, Xuhua; Yin, Changchuan

doi:10.1109/pimrc48278.2020.9217148

Cited by 6 publications

(8 citation statements)

References 10 publications

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“…With the growing demand for network quality in some applications, enhancing the overall performance of WSNs has become a topical issue. Several attempts have been made to explore solutions for improving energy efficiency and alleviating congestion to provide a high-quality services (QoS) [8,9,10,11]. Xu et al proposed a multi-hop routing protocol [12].…”

Section: Related Workmentioning

confidence: 99%

A Biodynamics Inspired Routing Algorithm for Energy Harvesting-aided 3-D Wireless Sensor Networks

Hao,

Chen,

Hong

et al. 2024

Preprint

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Energy Harvesting (EH) has emerged as a signiffcant technology capable of constructing future wireless sensor networks (WSNs). Although a signiffcant body of studies has focused on designing routing algorithms for EH-aided WSN so that the harvested energy can be efffciently used, most of them do not adequately consider energy overffow and waste caused by the limited battery capacity and data buffer. In addition, these works only concentrated on twodimensional (2-D) plane scenario. In practical environment, sensor nodes are generally deployed in three-dimensional (3-D) space. In light of the above limitations, a brand-new biodynamics inspired energy-efffcient routing algorithm used for EH-aided 3-D WSN is proposed (BDRATD for short). Firstly, through fully considering the spatial distribution of nodes (including planar and vertical dimensionality), we design a classiffed channel model adapted to 3-D spatial communication conditions. On this basis, an energy assessment model is is built to determine the energy state of nodes. Next, we establish a buffer queuing model to detect the blocking level of nodes. Combining the above models, we further consider the inffuence of IEEE 802.11b medium access control (MAC) protocol, and design an idle energy prediction mechanism to improve power utilization. With the help of hemodynamics, we provide the path selection strategy of BDRA-TD for EH-aided 3-D WSN. Moreover, we analyze the complexity of our algorithm and demonstrate it has convergent property. Extensive simulation results show that our algorithm performs superior in terms of average end-to-end delay, average energy dissipation, packet success ratio, average residual energy and acceptable performance in average energy variance compared to other algorithms.

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Section: Related Workmentioning

confidence: 99%

A Biodynamics Inspired Routing Algorithm for Energy Harvesting-aided 3-D Wireless Sensor Networks

Hao,

Chen,

Hong

et al. 2024

Preprint

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“…The outcomes defined the benefits and efficacy of the RE-BORN method compared to the other methods. Yuanyang et al 2020 [8] defined the JO (join optimization) of data transmission, and EUS(energy utilization) in EH-WSN (energy harvesting-WSN) was analyzed.aEH-WSN the imbalance of EH and consumption affects the communication and ability of the network. A new EA opportunistic RP with LSTM (along-shot-term-memory) method based on SE (solar energy)prediction was presented to resolve this issue.…”

Section: Prior Work João Junior Et Al 2021 [7]mentioning

confidence: 99%

Several Categories of Energy Harvested Routing Protocols, Challenges, and Characteristics in WSN: A Review

Bhanu Priyanka Valluri

2023

IJRITCC

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The routing protocol is a technique for determining the most efficient channel for data transmission. The route selection procedure, which relies on the kind of network, channel conditions, and measurement systems, presents several challenges. Routing is essential in Wireless Sensor Networks (WSNs) for environmental monitoring, traffic monitoring, and other applications. WSNs are small nodes that can sense, interpret data, and communicate wirelessly. Many routing, power control, and data dissemination techniques have been developed specifically for WSNs, where energy efficiency is a crucial design factor. On the other hand, the focus has been on energy harvesting and standard routing methods, which can vary depending on the design and network architecture. In a Wireless Sensor Network (WSN), the data collected by the sensor nodes is typically transferred to the base station, which connects the sensor network to other networks (such as the internet), where it is processed and necessary action is taken. WSN has recently been developed to allow various applications, including traffic enforcement building automation, smart warfare, environmental sensing, and many more.WSN integrates several sensors or nodes deployed around a specific node to perform computational processes.

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“…Yee et al further proposed the energy threshold, combined with the maximum and minimum communication range to select the relay node with higher residual energy at different distances [19]. Additionally, an energy-saving opportunity routing protocol based on area density, relative distance, and residual energy was studied to balance energy consumption [21][22][23]. The references [24] further introduce the transmission probability as one of the indicators for constructing candidate sets.…”

Section: Related Workmentioning

confidence: 99%

“…This paper compares and analyzes the network performance in four aspects: energy consumption, throughput, delay, and retransmission rate. Reference [19], reference [18], reference [23], and reference [36] are used as comparison algorithms. In this paper, they are represented by Algorithm 1, Algorithm 2, Algorithm 3, and Algorithm 4, respectively.…”

Section: Experimental Parameter Settingmentioning

confidence: 99%

An Efficient Opportunistic Routing Protocol with Low Latency for Farm Wireless Sensor Networks

Han

Zhu

et al. 2022

Electronics

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Wireless sensor networks (WSN) can accurately and timely obtain the production information of crops, and provide data basis for intelligent agriculture. The dynamic crop state and unstable climate environment make it difficult to predict the connectivity probability of wireless links. Therefore, this paper studies an energy-saving opportunity routing transmission strategy under the influence of dynamic link interaction. The protocol establishes an importance model based on algebraic connectivity to reduce the energy consumption of network key nodes. At the same time, based on the improved Bellman–Ford algorithm, a method of constructing candidate sets is studied. It converts the opportunistic routing transmission cost of farm WSN into anycast link cost and the remaining opportunistic path cost affected by energy consumption. The priority queue is used to determine the nodes participating in the iteration, thereby reducing the computational overhead. The protocol also designs a backoff strategy considering the current residual energy to select the only forwarding node and reduce the unnecessary packet copies in the transmission process. Simulation results show that the studied method is superior to the existing opportunistic routing schemes in terms of packet overhead, network lifetime, energy consumption, and packet delivery rate.

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Energy Aware Opportunistic Routing for Energy Harvesting Wireless Sensor Networks

Cited by 6 publications

References 10 publications

A Biodynamics Inspired Routing Algorithm for Energy Harvesting-aided 3-D Wireless Sensor Networks

A Biodynamics Inspired Routing Algorithm for Energy Harvesting-aided 3-D Wireless Sensor Networks

Several Categories of Energy Harvested Routing Protocols, Challenges, and Characteristics in WSN: A Review

An Efficient Opportunistic Routing Protocol with Low Latency for Farm Wireless Sensor Networks

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