Improved LEACH Protocol based on Moth Flame Optimization Algorithm for Wireless Sensor Networks

Wireless sensor nodes are made up of small electronic devices designed for detecting, determining, and sending data under severe physical conditions. These sensor nodes rely heavily on batteries for energy, which drain at a quicker pace due to the extensive communication and processing tasks they must carry out. Managing this battery resource is the major challenge in wireless sensor networks (WSNs). This work aims at developing an improved performance and energy-efficient low-energy adaptive clustering hierarchy (IPE-LEACH) that can extend the lifespan of networks. This paper proposes a novel LEACH protocol that uses the moth flame optimization (MFO) algorithm for clustering and routing to increase the longevity of the sensor network. IPE-LEACH proved to have a better cluster-head (CH) selection technique by eliminating redundant data, thereby extending the network lifetime. IPE-LEACH was compared with four other existing algorithms, and it performed better than: original LEACH by 60%, EiP-LEACH by 45%, LEACH-GA by 58%, and LEACH-PSO by 13.8%. It can therefore be concluded that IPE-LEACH is a promising clustering algorithm that has the potential to realize high flexibility in WSNs in case the CH fails.     

MG-leach: an enhanced leach protocol for wireless sensor network

A wireless sensor network is made up of a large number of small sensor nodes with limited energy resources, which is a real problem for this network. In this article, we will study the ingestion of node energy in these networks at the routing level. In addition, we are modifying one of the most popular routing algorithms for data communication in the WSN: LEACH (Adaptive Hierarchy with Low Power Consumption). The modified version of the LEACH base version "MG_LEACH" uses an intermediate cluster header to transmit data, extend the network lifetime and send more data than the original protocol. Our proposed algorithm is simulated using MATLAB to verify the effectiveness of improving the lifetime of this network. The results of the simulation confirmed that the system was working better than the LEACH basic system and that the network life had been improved. 

Enhancing the Stability of the Improved-LEACH Routing Protocol for WSNs

Recently, increasing battery lifetime in wireless sensor networks has turned out to be one of the major challenges faced by researchers. The sensor nodes in wireless sensor networks use a battery as their power source, which is hard to replace during deployment. Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the most prominent wireless sensor network routing protocols that have been proposed to improve network lifetime by utilizing energy-efficient clustering. However, LEACH has some issues related to cluster-head selection, where the selection is done randomly. This leads to rapid loss of energy in the network. Improved LEACH is a LEACH alternative that has the ability to increase network lifetime by using the nodes' residual energy and their distance to the base station to select cluster-head nodes. However, Improved LEACH causes reduced stability, where the stability period is the duration before the death of the first node. The network stability period is important for applications that require reliable feedback from the network. Thus, we were motivated to investigate the Improved LEACH algorithm and to try to solve the stability problem. A new protocol is proposed in this paper: Stable Improved Low Energy Adaptive Clustering Hierarchy (SILEACH), which was developed to overcome the flaws of the Improved LEACH protocol. SILEACH balances the load between the nodes by utilizing an optimized method that considers the nodes' distance to the base station and their residual energy to select the cluster-head nodes and considers the nodes' distance to the cluster head and the base station to form clusters. The simulation results revealed that SILEACH is significantly more efficient than Improved LEACH in terms of stability period and network lifetime

An Efficient Routing Algorithm for Optimizing Energy Conservation and Improved Scalability in WSN

Wireless Sensor Network (WSN) is a familiar technique to develop various real-world applications through sensor nodes on wireless networks. Energy efficiency and scalability are the important challenges in WSN, along withsome other parameters such as reliability, availability, and security. The nodes’ path and communication network have been decided based on routing techniques among the network nodes. Classical routing algorithms have improved the efficiency and accuracy of WSN nodes, but it works only in the limited range. The number of nodes is increased in WSN, and security of data transmitted has a lot of limitations in routing. This problem has been considered for a long time, but the level of improvement is only within a short range, not for larger networks and high-volume nodes. This problem has been overcome by an efficient routing algorithm SEERA (Scalable Energy Efficient Routing Algorithm). Familiar routing protocol techniques such as LEACH (Low Energy Adaptive Clustering Hierarchy), Multi-LEACH, CELL-LEACH when compared with this algorithm shows that SEERA provides better security, energy efficiency and scalability. Also, the proposed algorithm uses hybrid MAC protocols along with the clusters communicated in Intra mode on the network. This research paper summarizes the results of SEERA withmore scalable nodes on WSN and also improved their energy efficiency among all nodes

From carbon nanotubes and silicate layers to graphene platelets for polymer nanocomposites

In spite of extensive studies conducted on carbon nanotubes and silicate layers for their polymer-based nanocomposites, the rise of graphene now provides a more promising candidate due to its exceptionally high mechanical performance and electrical and thermal conductivities. The present study developed a facile approach to fabricate epoxy–graphene nanocomposites by thermally expanding a commercial product followed by ultrasonication and solution-compounding with epoxy, and investigated their morphologies, mechanical properties, electrical conductivity and thermal mechanical behaviour. Graphene platelets (GnPs) of 3.5