508 research outputs found
ANCAEE: A novel clustering algorithm for energy efficiency in wireless sensor networks
One of the major constraints of wireless sensor networks is limited energy available to sensor nodes because of the small size of the batteries they use as source of power. Clustering is one of the routing techniques that have been using to minimize sensor nodes’ energy consumption during operation. In this paper, A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks (ANCAEE) has been proposed. The algorithm achieves good performance in terms of minimizing energy consumption during data transmis-sion and energy consumptions are distributed uniformly among all nodes. ANCAEE uses a new method of clusters formation and election of cluster heads. The algorithm ensures that a node transmits its data to the cluster head with a single hop transmission and cluster heads forward their data to the base station with multi-hop transmissions. Simulation results show that our approach consumes less energy and effectively extends network utilization
An Innovative Multiple Attribute Based Distributed Clustering with Sleep/Wake Scheduling Mechanism for WSN
Wireless sensor network is a dynamic field of networking and communication because of its increasing demand in critical Industrial and Robotics applications. Clustering is the technique mainly used in the WSN to deal with large load density for efficient energy conservation. Formation of number of duplicate clusters in the clustering algorithm decreases the throughput and network lifetime of WSN. To deal with this problem, advance distributive energy-efficient adaptive clustering protocol with sleep/wake scheduling algorithm (DEACP-S/W) for the selection of optimal cluster head is presented in this paper. The presented sleep/wake cluster head scheduling along with distributive adaptive clustering protocol helps in reducing the transmission delay by properly balancing of load among nodes. The performance of algorithm is evaluated on the basis of network lifetime, throughput, average residual energy, packet delivered to the base station (BS) and CH of nodes. The results are compared with standard LEACH and DEACP protocols and it is observed that the proposed protocol performs better than existing algorithms. Throughput is improved by 8.1% over LEACH and by 2.7% over DEACP. Average residual energy is increased by 6.4% over LEACH and by 4% over DEACP. Also, the network is operable for nearly 33% more rounds compared to these reference algorithms which ultimately results in increasing lifetime of the Wireless Sensor Network
ANCAEE: A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks
One of the major constraints of wireless sensor networks is limited energy available to sensor nodes because
of the small size of the batteries they use as source of power. Clustering is one of the routing techniques that
have been using to minimize sensor nodes’ energy consumption during operation. In this paper, A Novel
Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks (ANCAEE) has been proposed.
The algorithm achieves good performance in terms of minimizing energy consumption during data transmission and energy consumptions are distributed uniformly among all nodes. ANCAEE uses a new method of
clusters formation and election of cluster heads. The algorithm ensures that a node transmits its data to the
cluster head with a single hop transmission and cluster heads forward their data to the base station with
multi-hop transmissions. Simulation results show that our approach consumes less energy and effectively
extends network utilization
Energy-Efficient Hybrid K-Means Algorithm for Clustered Wireless Sensor Networks
Energy efficiency is the most critical challenge in wireless sensor network. The transmission energy is the most consuming task in sensor nodes, specifically in large distances. Clustered routing techniques are efficient approaches used to lower the transmission energy and maximize the network’s lifetime. In this paper, a hybrid clustered routing approach is proposed for energy optimization in WSN. This approach is based on K-Means clustering algorithm and LEACH protocol. The simulation results using MATLAB tool have shown that the proposed hybrid approach outperforms LEACH protocol and optimizes the nodes energy and the network lifetime
Residual Energy Based Cluster-head Selection in WSNs for IoT Application
Wireless sensor networks (WSN) groups specialized transducers that provide
sensing services to Internet of Things (IoT) devices with limited energy and
storage resources. Since replacement or recharging of batteries in sensor nodes
is almost impossible, power consumption becomes one of the crucial design
issues in WSN. Clustering algorithm plays an important role in power
conservation for the energy constrained network. Choosing a cluster head can
appropriately balance the load in the network thereby reducing energy
consumption and enhancing lifetime. The paper focuses on an efficient cluster
head election scheme that rotates the cluster head position among the nodes
with higher energy level as compared to other. The algorithm considers initial
energy, residual energy and an optimum value of cluster heads to elect the next
group of cluster heads for the network that suits for IoT applications such as
environmental monitoring, smart cities, and systems. Simulation analysis shows
the modified version performs better than the LEACH protocol by enhancing the
throughput by 60%, lifetime by 66%, and residual energy by 64%
- …