Energy‑harvesting and energy aware routing algorithm for heterogeneous energy WSNs

Abstract

Wireless sensor networks are regarded as the most essential components of contemporary technologies since they are in charge of sensing and monitoring processes, which are the primary functions of these technologies. Because these nodes rely on an unchangeable battery and are randomly deployed in the environment, node energy management is the most essential issue to consider when designing algorithms to enhance the network's life. Clustering is a wireless sensor network (WSN) routing technique that has been implemented in order to extend network lifetime. Also, it is trendy to increase the energy levels of the node battery by utilizing various energy harvesting techniques in order to extend the network lifetime. In this paper, a new energy-aware clustering algorithm (EHEARA) has been proposed. The proposed algorithm is based on a dynamic clustering function and adopts a solar energy harvesting scheme in order to improve network lifetime. Furthermore, the active-sleep mechanism was used to distribute node activity and balance communication among nodes within clusters and cluster heads with the base station. The proposed algorithm is simulated using matrix laboratory (MATLAB), and the results show that it outperforms the low energy adaptive clustering hierarchy (LEACH), distributed energy efficient clustering (DEEC), and stable election protocol (SEP) algorithms in terms of network lifetime, energy consumption, and network throughput.

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

“…These technologies include lead-acid batteries, Ni-Cd batteries, Na-S, VRFB batteries, and Li-Ion batteries [66], [83], [27]- [29]. There are several types of electrochemical storage, such as lead-acid, lithiumion, nickel cadmium, nickel metal hydride, and flow batteries.…”

Proposed energy efficient clustering and routing for wireless sensor network

“…− During communication, the energy utilization of CH becomes high because it performs various tasks such as packet receiving, aggregation, and broadcasting over the network. Hence, the sensor with a large amount of energy is wanted as CH and the residual energy is expressed in (6).…”

“…The WSNs accomplish three essential tasks such as sensing, processing, and communicating. The communication task utilizes high energy than the remaining tasks [6]. WSN is subjected to various types of limits when compared to wired networks such as restricted communication distance, limited network communication bandwidth, and limited power resources [7].…”

A novel energy efficient routing scheme for wireless sensor networks

“…The interested node joins the cluster by sending back an acknowledgement to the cluster head. In the data transmission phase, the nodes send data to the cluster head in the allocated time-division multiple access (TDMA) slot [18]- [20].…”