Abstract
Wireless sensor networks have attracted worldwide attention in recent years. The failure of the nodes is caused by unequal energy dissipation. The reasons that cause unequal energy dissipation are, first and foremost, the distance between the nodes and the base station, and secondly, the distance between the nodes themselves. In wireless sensor networks, the location of the base station has a substantial impact on the network’s lifetime effectiveness. An improved genetic algorithm based on the crossover elitist conservation genetic algorithm (CECGA) is proposed to optimize the base station location, while for clustering, the K-medoids clustering (KMC) algorithm is used to determine optimal medoids among sensor nodes for choosing the appropriate cluster head. The idea is to decrease the communication distance between nodes and the cluster heads as well as the distance among nodes. For data routing, a multi-hop technique is used to transmit data from the nodes to the cluster head. Implementing an evolutionary algorithm for this optimization problem simplifies the problem with improved computational efficiency. The simulation results prove that the proposed algorithm performed better than compared algorithms by reducing the energy use of the network, which results in increasing the lifetime of the nodes, thereby improving the whole network.
Highlights
The advancement of digital technology during the third industrial revolution combined with power-efficient electronic devices has brought about wireless sensor network (WSN) technology
WSN refers to a network of several low-cost, efficient, and multifunctional sensor nodes working together to monitor or investigate an area of interest (AoI)
Our goal is to figure out which base station position is the best position to collect data in a WSN so that the network lifetime (T) can be extended
Summary
The advancement of digital technology during the third industrial revolution combined with power-efficient electronic devices has brought about wireless sensor network (WSN) technology. WSN refers to a network of several low-cost, efficient, and multifunctional sensor nodes working together to monitor or investigate an area of interest (AoI). These sensors generate data from the area of interest and send them to a base station (BS) to be processed into useable information. Despite the popularization of WSN, the challenges encountered when implementing sensor nodes can be broadly categorized into three main issues: node deployment, data handling (includes acquisition and transfer), and power efficiency. If the nodes are sparsely deployed, the sensing accuracy would be compromised, while a dense deployment would result in a high power requirement and cost of the system
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