الفهرس 
Chapter -1- IntroductionOnly 14 pages are availabe for public view
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Abstract
Wireless sensor networks (WSNs) have attracted significant attention because of their widespread use in healthcare, habitat tracking, disaster prevention, agriculture, monitoring areas, fire tracks, and other real-life applications. The lifetime of WSNs must be prolonged to increase their use for various applications. It can be computed using general metrics, such as the time when the last node died, how many bits were transferred to the base station (BS), and others for the used application. One of the most effective methods for improving the network’s lifetime is clustering with the optimal cluster head (CH). A CH is a special sensor node considered to be the lead. It is responsible for receiving data from normal sensor nodes within its cluster, aggregating it, and transferring the data to the BS. And as per the literature, the clustering protocols have a drawback. They are based on a probabilistic model that minimizes energy efficiency. This study proposes a fuzzy logic (FL) low-energy adaptive clustering hierarchy (LEACH) technique-based particle swarm optimization (PSO). It is used for enhancing the performance of WSN by prolonging the network lifetime and maximizing the network throughput. The proposed protocol is based on using gap-static clustering evaluation for determining the optimal number of clusters. After that, it is divided into two phases : setup and steady phases. The setup phase consists of cluster formation to reduce intra-cluster communication distances using hybrid PSO and a K-means clustering algorithm. The steady phase includes three main steps : primary CH selection using FL, secondary CH selection using FL, and intracluster data communication. CH has many tasks to be performed based on its energy level. Instead, two sensor nodes (primary CH and secondary CH) were used. The secondary CH collects sensed data from all cluster members (CMs) through its cluster and aggregates them. After aggregating, secondary CH transmits the data to primary CH through its cluster. The primary CH receives and transmits the data to the BS. Extensive simulations were conducted using a simulation program to validate the proposed protocol’s performance. Furthermore, the proposed protocol was compared with traditional algorithms, such as fuzzy c-means (FCM) clustering and fuzzy logic system FLS-based CH selection to enhance the sustainability of WSNs for environmental monitoring applications protocol, LEACH-Fuzzy clustering protocol, and LEACH based on energy consumption equilibrium algorithm. The obtained results were compared by applying standard evaluation metrics : the number of alive nodes related to rounds of the network, average remaining energy related to rounds of the network, and bits transferred to BS related to rounds of the network. The results confirmed that the proposed protocol efficiently balances energy consumption to improve WSN performance and maximize throughput. To draw conclusions about the scalability of the methodology of the proposed protocol, simulations were conducted in two different scenarios according to the number of deployed sensor nodes in experiments in the WSN area. In scenario 1, 100 sensor nodes were deployed in the WSN. In scenario 2, 1000 sensor nodes were deployed in the WSN area as the usage of nodes has increased exponentially lately. The simulated results indicated that network lifetime was improved compared with previous studies in this field by more than 46% as the last node died in the proposed protocol at more than 10,000 rounds (92 dead nodes). And the packet transmission was improved compared with previous studies in this field by 17.6% as 196 × 106 bits were transferred in the proposed protocol at 92% of the network lifespan.