Fuzzy power‐optimised clustering routing algorithm for wireless sensor networks

Abstract

Transmission power control is an effective method to reduce energy consumption for wireless sensor networks. However, the current algorithms of power control have relatively low accuracy. At the same time, the parameters cannot be adjusted dynamically. In order to improve the energy utilisation as well as data transmission efficiency and balance the load, therefore, a fuzzy power-optimised clustering routing algorithm is proposed in this study. The algorithm optimises the iteration radius and classifies the sensor nodes into different categories according to their node degree. Then select the cluster head by multi-parameter iteration adaptively among the same category, and optimise the cluster structure with a comprehensive consideration of parameters such as degree of centralisation, distance between node and base station and so on. Finally, fuzzy control is used to adjust the transmission power of cluster nodes dynamically to minimise the energy consumption. Simulation results show that when the average cluster radius R L = 60, weight of election parameters α = 0.2, adjustment parameter of cluster radius η = 0.7, compared with other similar algorithms, the proposed algorithm prolongs the lifetime by at least 42.2% and increases the amount of data packets by at least 40.1%.

Load Balancing Routing Algorithm of Low‐Orbit Communication Satellite Network Traffic Based on Machine Learning

“…It is mainly concentrated in some important cities on the mainland but is quite small in the ocean. This leads to a situation in which the traffic is concentrated in a certain area at certain moments in the satellite network communication process, and the satellites in this area are often congested, but the surrounding satellites are not fully utilized [28]. The low-orbit satellite network load balancing algorithm can adjust the link cost of the link according to the congestion state of the satellite link and the load state of the previous time period when the satellite link is congested.…”

Energy-Saving Algorithm and Simulation of Wireless Sensor Networks Based on Clustering Routing Protocol

“…For any node, its n i -round serves as cluster head once, so the energy accumulation period is n i . According to formula (14), formula (15) and formula (16), ETh i is:…”

“…There are two main methods of implementation [12]- [15]: one is to establish a suitable data transmission link, and the other is to correctly transmit datagram along the established data link. In the traditional Ad hoc network, the primary purpose of routing protocol design is to utilize the limited bandwidth resources of the network [16]. Therefore, a path with a small communication delay is usually found between the two kinds nodes to balance network traffic, avoid channel congestion, and improve network utilization [17], [18].…”

Optimising the power using firework‐based evolutionary algorithms for emerging IoT applications

“…In the literature [25,32,33], various models of the power consumption are presented for radio communication between two communicating nodes. In this study, we consider the antenna gain as a factor of transmitting power between the radio links IoTs-CCNs and CCNs-BSs.…”