Live Breaking News & Updates on Low Energy Adaptive Clustering Hierarchy

Stay updated with breaking news from Low energy adaptive clustering hierarchy. Get real-time updates on events, politics, business, and more. Visit us for reliable news and exclusive interviews.

"Energy-efficient adaptive clustering (EEAC) with rendezvous nodes and " by Pushpendra Kumar Gupta, Akshay Verma et al.

Wireless sensor networks are an indispensable part of the present industrial and environmental scenario, with the everlasting challenges to increase network lifetime and reduce energy consumption. This paper presents an energy-efficient adaptive clustering (EEAC) model, which is built upon the existing Low Energy Adaptive Clustering Hierarchy (LEACH) protocol with mobile sink and rendezvous nodes. The nodes are energy aware and participate in cluster head selection only if their current energy is higher than the average energy for the round. The idle nodes in the rendezvous region, which do not act as rendezvous nodes undergo clustering within themselves for the efficient routing of data. The EEAC inspires local clustering successfully conserves the energy of continuous long-range transmission and enhances network lifetime. The proposed scheme proves to be remarkably better than the previous schemes, especially in large network cross-sections. It improves alive nodes' performance ....

Energy Adaptive Clustering Hierarchy , Low Energy Adaptive Clustering Hierarchy , Cluster Head , Ocal Clustering , Obile Sink , Endezvous Node , Wireless Sensor Network ,

"Energy-balanced neuro-fuzzy dynamic clustering scheme for green & sust" by Premkumar Chithaluru, Fadi Al-Turjman et al.

The Internet of Things (IoT) is a pervasive computing technology that provides solutions to critical sustainable smart city applications. Each sustainable application has its own set of requirements, including energy efficiency, Quality of Service (QoS), hardware, and software resources. Even though green IoT devices operate in a resource-constrained environment. Monitoring, recognizing, and responding to activities that entail continuous access to timely information in a partially or fully distributed ecosystem is a difficult task. To overcome the challenges of resource management in the IoT, we proposed an energy-efficient Dynamic Clustering Routing (DCR) protocol using a neuro-fuzzy technique for restricting the resources of IoT devices. The proposed protocol uses a dynamic self-organizing neural network to create dynamic clusters in a network. The test-bed analysis is for computing the real-time event detection and clustering sensor nodes using TinyOS. The simulation result shows t ....

Quality Of Service Qo , Dynamic Clustering Routing , Low Energy Adaptive Clustering Hierarchy , First Node Dies , Last Node Dies , Dynamic Clustering , Reen Communication Protocols , Neuro Fuzzy , Smart City ,