An Enhanced Clustering Method for Extending Sensing Lifetime of Wireless Sensor Network

Extending the lifetime of a wireless sensor network is vital in ensuring continuous monitoring functions in a target environment. Many techniques have appeared that seek to achieve such prolonged sensing gains. Clustering and improved selection of cluster heads play essential roles in the performance of sensor network functions. Cluster head in a hierarchical arrangement is responsible for transmitting aggregated data from member nodes to a base station for further user-specific data processing and analysis. Minimising the quick dissipation of cluster heads energy requires a careful choice of network factors when selecting a cluster head to prolong the lifetime of a wireless sensor network. In this work, we propose a multi-criteria cluster head selection technique to extend the sensing lifetime of a heterogeneous wireless sensor network. The proposed protocol incorporates residual energy, distance, and node density in selecting a cluster head. Each factor is assigned a weight using the Rank Order Centroid based on its relative importance. Several simulation tests using MATLAB 7.5.0 (R2007b) reveal improved network lifetime and other network performance indicators, including stability and throughput, compared with popular protocols such as LEACH and the SEP. The proposed scheme will be beneficial in applications requiring reliable and stable data sensing and transmission functions.

Optimized Energy Conservation Procedure for Heterogeneous Wireless Sensor Network

A WSN is composed of device with dissimilar energy levels. For saving energy, a grouping algorithm is obligatory and it also intensification the epoch time of the network and the firmness epoch of the network. For securing the energy conservation of the network, energy-efficient grouping etiquettes are designed for the HWSN. We projected the protocol for the energy-efficient grouping scheme which is an enhanced version of the protocols such as EDEEC, SEP, DEEC, and DDEEC. Simulation outcomes demonstrate that the proposed mechanism is well recovering than the SEP (A Stable Election Protocol), DEEC (Distributed Energy Efficient Grouping Protocol), EDEEC (Enhanced Distributed Energy-Efficient Protocol), DDEEC (Developed DEEC) in standings of the network duration, number of packets delivered to the BS, amount of CH selected and number of nodes alive per smoothed. The CH will be selected founded on the original energy and the left-over energy of the device.

Sector Tree-Based Clustering for Energy Efficient Routing Protocol in Heterogeneous Wireless Sensor Network

One of the main challenges for researchers to build routing protocols is how to use energy efficiently to extend the lifespan of the whole wireless sensor networks (WSN) because sensor nodes have limited battery power resources. In this work, we propose a Sector Tree-Based clustering routing protocol (STB-EE) for Energy Efficiency to cope with this problem, where the entire network area is partitioned into dynamic sectors (clusters), which balance the number of alive nodes. The nodes in each sector only communicate with their nearest neighbour by constructing a minimum tree based on the Kruskal algorithm and using mixed distance from candidate node to base station (BS) and remaining energy of candidate nodes to determine which node will become the cluster head (CH) in each cluster? By calculating the duration of time in each round for suitability, STB-EE increases the number of data packets sent to the BS. Our simulation results show that the network lifespan using STB-EE can be improved by about 16% and 10% in comparison to power-efficient gathering in sensor information system (PEGASIS) and energy-efficient PEGASIS-based protocol (IEEPB), respectively.

Energy Efficient Heterogeneous WNS Clustering Using Machine Learning

Heterogeneous wireless sensor network (HWSN) fulfills the requirements of researchers in the design of real-life application to resolve the issues of unattended problem. Wireless sensor networks are used in diverse areas such as battlefields, security, hospitals, universities, etc. It has been used in our everyday lives. Its development is rising day by day. Wireless sensor network includes hundreds to thousands of sensor nodes which aid in gathering various information like temperature, sound, location, etc. Recharging or modifying sensor nodes which might have limited battery power is usually difficult. Therefore, energy conservation is a crucial concern in sustaining the network. Clustering the networks is definitely one of the most common solutions for rendering WSNs energy. In this paper, review and compare different energy-efficient clustering protocols for WSNs