In order to gather data more efficiently, a clustering hierarchy algorithm is used for data communication in wireless sensor networks (WSNs). This algorithm is one of the major techniques to improve the energy efficiency in WSNs and it provides an effective manner to maximize the lifetime of WSNs. Hierarchical protocols based on clustering hierarchy are proposed to save energy of WSNs in which the nodes with higher remaining energy could be used to collect data and transmit it to a base station. However, most of the previous approaches based on clustering hierarchy have not considered the redundant data collected by the adjacent nodes or nodes overlap each other. In this paper, an enhanced clustering hierarchy (ECH) approach has been proposed to achieve energy efficiency in WSNs by using sleeping-waking mechanism for overlapping and neighboring nodes. Thus, the data redundancy is minimized and then network lifetime is maximized. In contrast of previous hierarchical routing protocols where all nodes are required for collecting and transmitting data, the proposed approach only requires the waking nodes to do these tasks, which are keys of energy consumption in WSNs. We implement (ECH) approach in homogeneous and heterogeneous networks. Results of the simulation show its effectiveness.

WSNs are characterized by limited energy constraints. This characteristic poses considerable challenge on design of routing protocols. Therefore, many designers and researchers focus on architectures and algorithms that allow energy-efficient operation of WSNs. One of the popular algorithms in this regard is clustering algorithm. Thus, there are many routing protocols based on clustering algorithm has been proposed for WSNs, the functionality of these protocols is divided into cluster heads (CHs) selection and cluster formation. However, CHs selection is one of the very important problems in routing protocols applications and can drastically impact the network lifespan thereby energy conservation task for WSNs. In this paper, we propose a new routing approach called Energy-efficient fuzzy logic cluster head (EEFL-CH); it is an improvement of LEACH protocol. The goal of this approach is to decrease energy consumption in terms of network lifetime extension using three fuzzy parameters. These parameters are residual energy, expected efficiency, and closeness to base station. Simulation results show that EEFL-CH approach has the better result as compared with LEACH and LEACH-ERE routing protocols.

Energy efficiency is a major factor in designing wireless sensor networks (WSNs). Clustering design and grid‐based scheme are one of the techniques to save energy in WSNs. However, for a mobile sink in WSNs, packet loss rate that occurs due to the sink mobility is also a significant challenge. Here, an enhanced routing‐G _i protocol for a mobile sink in WSNs has been proposed to not only enhance energy efficiency but also minimise the packet loss rate. Simulation results show that the proposed protocol is more efficient than the previous protocols in terms of the network lifespan, energy efficiency, and packet delivery ratio. Thus, the proposed approach in this work could further be adapted to investigate highly mobility of sink in WSNs.

WSNs have many applications in modern life. Thus, optimization of the network operation is required to maximize its lifetime. The energy is a major issue in order to increase the lifetime of WSNs. The clustering algorithm is one of the proposed algorithms to enhance the lifetime of WSNs. The operation of the clustering algorithm is divided into cluster heads (CHs) selection and cluster formation. However, most of the previous works have focused on CHs selection, and have not considered the cluster formation process, which is the important issue in clustering algorithm based routing schemes, and it can drastically affect the lifetime of WSNs. In this paper, a Fuzzy Logic based Clustering Algorithm for WSN (CAFL) has been proposed to improve the lifetime of WSNs. This approach uses fuzzy logic for CHs selection and clusters formation processes by using residual energy and closeness to the sink as fuzzy inputs in terms of CH selection, and residual energy of CH and closeness to CHs as fuzzy inputs in terms of clusters formation. Simulation results justify its efficiency.

Energy efficiency and throughput are critical factors in the design routing protocols of WSNs. Many routing protocols based on clustering algorithm have been proposed. Current clustering algorithms often use cluster head selection and cluster formation to reduce energy consumption and maximize throughput in WSNs. In this chapter, the authors present a new routing protocol based on smart energy management and throughput maximization for clustered WSNs. The main objective of this protocol is to solve the constraint of closest sensors to the base station which consume relatively more energy in sensed information traffics, and also decrease workload on CHs. This approach divides network field into free area which contains the closest sensors to the base station that communicate directly with, and clustered area which contains the sensors that transmit data to the base station through cluster head. So due to the sensors that communicate directly to the base station, the load on cluster heads is decreased. Thus, the cluster heads consume less energy causing the increase of network lifetime.

In order to conserve energy in wireless sensor networks (WSNs), sensor nodes are partitioned into clusters. Clustering algorithm provides an effective way to extend the network lifetime of WSNs. The operation of clustering algorithm is divided into cluster heads (CHs) selection phase and cluster formation phase. However, most of the previous researches have focused on CHs selection, and have not considered the cluster formation phase, which is important problem in WSNs and can drastically affect the network lifetime in WSNs. In this paper, cluster formation using fuzzy logic (CFFL) approach has been proposed to prolong network lifetime and reduce energy consumption in WSNs. this approach uses fuzzy logic in the formation cluster phase, two fuzzy parameters are used. These parameters are residual energy which is energy level of each CH and closeness to base station (BS) which is the distance between the CH and the BS. Simulation results show that the proposed approach consumes less energy and prolongs the network lifetime compared with Low Energy Adaptive Clustering Hierarchy (LEACH) protocol.