A Differential Evolution-Based Routing Algorithm for Environmental Monitoring Wireless Sensor Networks

The traditional Low Energy Adaptive Cluster Hierarchy (LEACH) routing protocol is a clustering-based protocol. The uneven selection of cluster heads results in premature death of cluster heads and premature blind nodes inside the clusters, thus reducing the overall lifetime of the network. With a full consideration of information on energy and distance distribution of neighboring nodes inside the clusters, this paper proposes a new routing algorithm based on differential evolution (DE) to improve the LEACH routing protocol. To meet the requirements of monitoring applications in outdoor environments such as the meteorological, hydrological and wetland ecological environments, the proposed algorithm uses the simple and fast search features of DE to optimize the multi-objective selection of cluster heads and prevent blind nodes for improved energy efficiency and system stability. Simulation results show that the proposed new LEACH routing algorithm has better performance, effectively extends the working lifetime of the system, and improves the quality of the wireless sensor networks

Research on data transmission and energy consumption optimization in steel plant terminal networks based on improved sep protocol

In steel plants with harsh conditions, numerous devices equipped with wireless sensors generate vast data and high energy consumption. Our study introduces the optimized PK-SEP algorithm, enhancing the Stable Election Protocol (SEP) and traditional K-means clustering with the elbow method and particle swarm optimization. This approach, tailored for large-scale WSNs in steel plants, effectively extends network lifespan, conserves energy, and improves data throughput, offering a viable solution for energy issues in WSNs and potentially boosting steel production efficiency and sustainability

NM-LEACH: A Novel Modified LEACH Protocol to Improve Performance in WSN

Saving energy and improving the lifetime of wireless sensor networks (WSNs) has remained as a key research challenge for some time. Low-energy adaptive clustering hierarchy (LEACH), a classical protocol is designed originally for the purpose of reducing and balancing the network’s energy consumption. However, as the distances between the cluster head (CH) and the member nodes are not taken into consideration, it results in the uneven distribution of the clusters and uneven consumption of the energy in the network. Choosing the CHs with no distinction is an issue as well. Based on the original algorithm, a novel modified LEACH (NM-LEACH) has been proposed, considering critical problems that exist in the network. NM-LEACH protocol is capable of reasonably solving the number of the CHs in each round and takes the energy as a factor of weight under consideration in selecting the CH. The proposed protocol enhances performance by extending the WSN lifecycle, which results in increasing the balance of the energy consumption in the network, and improving the efficiency of the network

A modified energy efficient multi-hop routing protocol in wireless sensor networks

Energy efficient routing protocols in Wireless Sensor Networks (WSNs) is an important area of research due to energy limitations. It is therefore important to maximize the limited energy so as to increase the network lifetime of the WSN. In this paper, a modified energy efficient multi-hop routing protocol (mEEMRP) in a 200 m2 field is presented. This protocol is based on a technique that involves balancing load between communication management (CM) nodes during the multi-hop routing of aggregated data to the base station (BS), where the residual energy (RE) levels of CM nodes are considered as well as the distance between neighboring CM nodes. Simulation results showed that mEEMRP yielded a 1.77% improvement over energy efficient multi-hop routing protocol (EEMRP) in terms of network lifetime. More so, the proposed mEEMRP also improved the energy consumption and the number of packets received at the BS by 4.83% and 7.41%, respectively.Keywords: Routing protocol, Multi-hop routing, Network lifetime, mEEMRP, EEMR

UHEED - an unequal clustering algorithm for wireless sensor networks

Prolonging the lifetime of wireless sensor networks has always been a determining factor when designing and deploying such networks. Clustering is one technique that can be used to extend the lifetime of sensor networks by grouping sensors together. However, there exists the hot spot problem which causes an unbalanced energy consumption in equally formed clusters. In this paper, we propose UHEED, an unequal clustering algorithm which mitigates this problem and which leads to a more uniform residual energy in the network and improves the network lifetime. Furthermore, from the simulation results presented, we were able to deduce the most appropriate unequal cluster size to be used

A Decentralized Fuzzy C-Means-Based Energy-Efficient Routing Protocol for Wireless Sensor Networks

Energy conservation in wireless sensor networks (WSNs) is a vital consideration when designing wireless networking protocols. In this paper, we propose a Decentralized Fuzzy Clustering Protocol, named DCFP, which minimizes total network energy dissipation to promote maximum network lifetime. The process of constructing the infrastructure for a given WSN is performed only once at the beginning of the protocol at a base station, which remains unchanged throughout the network’s lifetime. In this initial construction step, a fuzzy C-means algorithm is adopted to allocate sensor nodes into their most appropriate clusters. Subsequently, the protocol runs its rounds where each round is divided into a CH-Election phase and a Data Transmission phase. In the CH-Election phase, the election of new cluster heads is done locally in each cluster where a new multicriteria objective function is proposed to enhance the quality of elected cluster heads. In the Data Transmission phase, the sensing and data transmission from each sensor node to their respective cluster head is performed and cluster heads in turn aggregate and send the sensed data to the base station. Simulation results demonstrate that the proposed protocol improves network lifetime, data delivery, and energy consumption compared to other well-known energy-efficient protocols