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Enhancing Immune Plasma Algorithm for Coverage Optimization Problem in Wireless Sensor Networks

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2025年 1-22页

作者： Tasdemir, Adnan Demirci, Sercan Aslan, Selcuk Ondokuz Mayis Univ Dept Comp Engn TR-55139 Samsun Turkiye Erciyes Univ Dept Aeronaut Engn TR-38280 Kayseri Turkiye

Wireless sensor networks (WSNs) have gained paramount importance in diverse applications, resulting in extensive research efforts. Among the pivotal challenges facing WSNs is the strategic deployment of nodes, which are critical for efficient data processing and dissemination. Maximizing the coverage area of the sensor nodes emerges as a key determinant of optimal performance in various application domains. Leveraging advanced node deployment algorithms holds the promise of significantly enhancing sensor node coverage within monitoring regions, thereby yielding benefits such as reduced energy consumption, prolonged network lifespan, and streamlined sensor operations. This study endeavors to address the coverage area challenge by employing two variants of the immune plasma algorithm (IP), augmented by sophisticated modeling techniques and tools. Inspired by the biological transfer of plasma or antibodies between patients, the IP algorithm offers a robust framework to optimize WSN deployment. Rigorous experimentation showcases the efficacy of the proposed algorithm in effectively addressing the multifaceted challenges inherent in WSN deployment, thereby presenting compelling avenues for future research and implementation.

关键词： Wireless sensor networks Node deployment Coverage optimization Immune plasma algorithm Meta-heuristic algorithms Sensor coverage models binary detection model Probabilistic detection model Optimization techniques

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On the performance of quick artificial bee colony algorithm for dynamic deployment of wireless sensor networks

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2019年第6期27卷 4038-4054页

作者： Gorkemli, Beyza Al-Dulaimi, Zahraa Erciyes Univ Fac Engn Dept Comp Engn Kayseri Turkey

In recent years, the use of wireless sensor networks (WSNs) has increased and there have been significant improvements in this field. Especially with smarter, cheaper, and smaller sensor nodes, various kinds of information can be detected and collected in different environments and under different conditions. WSNs have thus been used in many applications such as military, surveillance, target tracking, home, medical, and environmental applications. As the popularity of WSNs increases, problems related to these networks are being realized. The dynamic deployment problem is one of the main challenges that have a direct effect on the performance of WSNs. In this study, a novel optimization technique named the quick artificial bee colony (qABC) algorithm was applied to the dynamic deployment problem of WSNs. qABC is a new version of the artificial bee colony algorithm (ABC) and it redefines the onlooker bee phase of ABC in a more detailed way. In order to see the performance of qABC on this problem, WSNs that include only mobile sensors or both stationary and mobile sensors were considered with binary and probabilistic detection models. Some experimental studies were conducted for tuning the colony size (CS) and neighborhood radius (r) parameters of the qABC algorithm, and the performance of the proposed method was compared with the standard ABC algorithm and some other recently introduced approaches including a parallel ABC, a cooperative parallel ABC, a version of ABC powered by a transition control mechanism (tlABC), and a parallel version of tlABC. Additionally, some CPU time analyses were provided for qABC and ABC considering different dimensions of the problem. Simulation results show that the qABC algorithm is an effective method that can be used for the dynamic deployment problem of WSNs, and it generally improves the convergence performance of the standard ABC on this problem when r >= 1.

关键词： Quick artificial bee colony algorithm wireless sensor networks dynamic deployment problem probabilistic detection model binary detection model

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A new metaheuristic approach based on orbit in the multi-objective optimization of wireless sensor networks

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WIRELESS NETWORKS 2021年第1期27卷 285-305页

作者： Ozdag, Recep Canayaz, Murat Van Yuzuncu Yil Univ Dept Comp Engn TR-65080 Van Turkey

Wireless sensor networks (WSNs) is a research area which has been used in various applications and has continuously developed up to now. WSNs are used in many applications, especially in military and civilian applications, with the aim of monitoring the environment and tracking objects. For this purpose, increasing the coverage rate of WSNs is one of the important criteria that determine the effective monitoring of the network. Since the sensors that make up the WSNs have a limited capacity in terms of energy, process and memory, various algorithmic solutions have been developed to optimize this criterion. The effective dynamic deployment of sensor nodes, which is the primary goal of these solutions, has a critical role in determining the performance of the network. A new orbit-based dynamic deployment approach based on metaheuristic Whale Optimization Algorithm has been proposed in this study. The goal is to optimize the convergence speed of the nodes, the coverage rate of the network, the total displacement (movement) distances of sensors and the degree ofk-coverage of each target (Grid) point in the area by effectively performing the dynamic deployments of sensors after their random distribution. This approach is compared with MADA-WOA and MADA-EM in the literature. Simulation results indicated that the approach developed in rapidly converging sensors to each other, increasing the network's coverage rate, and in minimizing the total movement distances of the sensors in the area and the degrees ofk-coverage of Grid points covered by the sensors could be proposed.

关键词： Wireless sensor networks Sensor deployment Area coverage problem Whale optimization algorithm binary detection model Degree ofk-coverage

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