A Data Collection Method for Mobile Wireless Sensor Networks Based on Improved Dragonfly Algorithm

Abstract

For the sensing layer of the Internet of Things, the mobile wireless sensor network has problems such as limited energy of the sensor nodes, unbalanced energy consumption, unreliability, and long transmission delay in the data collection process. It is proved by mathematical derivation and theory that this is a typical multiobjective optimization problem. In this paper, the optimization goal is to minimize the energy consumption and improve the reliability under time-delay constraints and propose a path optimization mechanism to optimize the mobile Sink of mobile wireless sensor networks based on the improved dragonfly optimization algorithm. The algorithm takes full advantage of the abundant storage space, sufficient energy, and strong computing power of the mobile Sink to ensure network connectivity and improve network communication efficiency. Through simulation comparison and analysis, compared with random movement method, artificial bee colony algorithm, and basic dragonfly optimization algorithm, the energy consumption of the network is reduced, the lifespan of the network is increased, and the connectivity and transmission delay of the network are improved. The proposed algorithm balances the energy consumption of the sensors nodes to meet the network service quality and improve the reliability of the network.

Application of Swarm Intelligence Optimization Algorithms in Image Processing: A Comprehensive Review of Analysis, Synthesis, and Optimization

“…Swarm intelligence algorithms can be roughly divided into three categories according to the source of inspiration: It is derived from the simple foraging behavior of animals. For example, the Shuffled Frog Leaping Algorithm (SFLA) [ 7 ] proposed by Eusuff et al in 2003 and the Whale Optimization Algorithm (WOA) [ 8 ] proposed by Mirjalili et al in 2016; It stems from the pure social behavior of biological populations, such as the artificial bee colony algorithm (ABC) proposed by Karaboga in 2005 [ 9 ] and the firefly algorithm (FA) proposed by Yang in 2008 [ 10 ]. The cuckoo search (CS) method proposed in 2009 [ 11 ] and the Mayfly Algorithm (MA) proposed by Konstantinos et al in 2020 [ 12 ]; Social behavior and foraging behavior derived from biological populations, such as the Bacterial Foraging Optimization (BFO) proposed by Passino in 2002 [ 13 ], the Bat Algorithm (BA) proposed by Yang in 2010 [ 14 ], and the Sparrow Search Algorithm (SSA) proposed by Xue et al in 2020 [ 15 ].…”

“…It stems from the pure social behavior of biological populations, such as the artificial bee colony algorithm (ABC) proposed by Karaboga in 2005 [ 9 ] and the firefly algorithm (FA) proposed by Yang in 2008 [ 10 ]. The cuckoo search (CS) method proposed in 2009 [ 11 ] and the Mayfly Algorithm (MA) proposed by Konstantinos et al in 2020 [ 12 ];…”

Implementation of Features Selection Based on Dragonfly Optimization Algorithm

“…By mimicking the hunting behaviour of dragonflies, the algorithm basically searches for the global optimal solution to the optimization issue The life routines of dragonflies, such as seeking food, avoiding enemies, and determining flying paths are taken into account throughout the modelling. [15] Dragonflies have two major goals: hunting and migration. The first is known as a feeding (static) swarm, whereas the second is known as a migrating (dynamic) swarm.…”

Analysis and Prospect of the Application of Wireless Sensor Networks in Ubiquitous Power Internet of Things

“…Therefore, it is a good choice to adopt a cheap and easy-to-install wireless monitoring and diagnosis system [ 3 ]. Wireless sensor network technology has the characteristics of low cost, self-organizing network, and application-related and is very suitable for wireless monitoring and diagnosis systems of power grids [ 4 – 8 ]. As an advanced information acquisition and processing technology, the wireless sensor network has been widely used in medical, industrial, agricultural, commercial, public management, and other fields, and it is an important means to promote future economic development and build a harmonious society [ 9 – 11 ].…”