An Energy-Efficient Routing Algorithm Based on Greedy Strategy for Energy Harvesting Wireless Sensor Networks

Abstract

Energy harvesting wireless sensor network (EH-WSN) is considered to be one of the key enabling technologies for the internet of things (IoT) construction. Although the introduced EH technology can alleviate the energy limitation problem that occurs in the traditional wireless sensor network (WSN), most of the current studies on EH-WSN fail to adequately consider the relationship between energy state and data buffer constraint, and thereby they do not address well the issues of energy efficiency and long end-to-end delay. In view of the above problems, a brand new greedy strategy-based energy-efficient routing protocol is proposed in this paper. Firstly, in the system modeling process, we construct an energy evaluation model, which comprehensively considers the energy harvesting, energy consumption and energy classification factors, to identify the energy state of node. Then, we establish a channel feature-based communication range judgment model to determine the transmission area of nodes. Combining these two models, a reception state adjustment mechanism is designed. It takes the buffer occupancy and the MAC layer protocol into account to adjust the data reception state of nodes. On this basis, we propose a greedy strategy-based routing algorithm. In addition, we also analyze the correctness and computational complexity of the proposed algorithm. Finally, we conduct extensive simulation experiments to show that our algorithm achieves optimum performance in energy consumption, packet delivery ratio, average hop count and end-to-end delay and acceptable performance in energy variance.

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

“…Up to now, EH-aided WSN has achieved great commercial value and it is successfully utilized in diverse domains including, Smart Cities, B5G/6G, Orthogonal Frequency Division Multiplexing (OFDM), Non-orthogonal Multiple Access (NOMA), Terahertz, Simultaneous Wireless Information and Power Transfer (SWIPT), etc. [5,6]. These all demonstrate EHaided WSN is an effective and cost-optimized technology.…”

An Enhanced Cluster-Based Routing Model for Energy-Efficient Wireless Sensor Networks

“…The algorithmic paradigm is one other technique that has been proven to improve the network lifetime. Genetic Algorithm (GA) iterative reconstruction mechanism using the residual energy [22], spanning tree search technique in selecting the CH node using the residual energy [23], elitist Genetic Algorithm [24], optimization algorithms [25][26], greedy strategy [27][28], K-Means routing scheme [29], and a host of others. These algorithmic approaches provided relevant information on energy-balanced data gathering and routing protocols for the WSN.…”

ROTEE: Remora Optimization and Tunicate swarm algorithm‐based Energy‐Efficient cluster‐based routing for EH‐enabled heterogeneous WSNs

“…Hao et al 29 determined the energy status of a node, as authors create an energy evaluation model in the system modeling process that takes into account all energy harvesting, energy consumption, and energy classification parameters. Then, to determine the transmission area of nodes, the authors create a channel feature‐based communication range judgment model.…”

“…For EH-WSNs, the performance is compared to energy-aware distributed clustering (EADC) and the self-energized clustering routing method (CRAS). During high irradiance circumstances, Hao et al 29 determined the energy status of a node, as authors create an energy evaluation model in the system modeling process that takes into account all energy harvesting, energy consumption, and energy classification parameters. Then, to determine the transmission area of nodes, the authors create a channel feature-based communication range judgment model.…”