Wireless Sensor Networks (WSNs) contain several small, autonomous sensor nodes (SNs) able to process, transfer, and wirelessly sense data. These networks find applications in various domains like environmental monitoring, industrial automation, healthcare, and surveillance. Node Localization (NL) is a major problem in WSNs, aiming to define the geographical positions of sensors correctly. Accurate localization is essential for distinct WSN applications comprising target tracking, environmental monitoring, and data routing. Therefore, this paper develops a Chaotic Mapping Lion Optimization Algorithm-based Node Localization Approach (CMLOA-NLA) for WSNs. The purpose of the CMLOA-NLA algorithm is to define the localization of unknown nodes based on the anchor nodes (ANs) as a reference point. In addition, the CMLOA is mainly derived from the combination of the tent chaotic mapping concept into the standard LOA, which tends to improve the convergence speed and precision of NL. With extensive simulations and comparison results with recent localization approaches, the effectual performance of the CMLOA-NLA technique is illustrated. The experimental outcomes demonstrate considerable improvement in terms of accuracy as well as efficiency. Furthermore, the CMLOA-NLA technique was demonstrated to be highly robust against localization error and transmission range with a minimum average localization error of 2.09%.
The Aedes aegypti (Linnaeus, 1762) mosquito is the main vector of dengue, chikungunya and Zika and is well established today all over the world. The species comprises two forms: the ancestral form found throughout Africa and a global domestic form that spread to the rest of the tropics and subtropics. In Saudi Arabia, A. aegypti has been known in the southwest since 1956, and previous genetic studies clustered A. aegypti from Saudi Arabia with the global domestic form. The purpose of this study was to assess the genetic structure of A. aegypti in Saudi Arabia and determine their geographic origin. Genetic data for 17 microsatellites were collected for A. aegypti ranging from the southwestern highlands of Saudi Arabia on the border of Yemen to the north-west in Madinah region as well as from Thailand and Uganda populations (as representatives of the ancestral African and global domestic forms, respectively). The low but significant level of genetic structuring in Saudi Arabia was consistent with long-distance dispersal capability possibly through road connectivity and human activities, that is, passive dispersal. There are two main genetic groupings in Saudi Arabia, one of which clusters with the Ugandan population and the other with the Thailand population with many Saudi Arabian individuals having mixed ancestry. The hypothesis of genetic admixture of the ancestral African and global domestic forms in Saudi Arabia was supported by approximate Bayesian computational analyses. The extent of admixture varied across Saudi Arabia. African ancestry was highest in the highland area of the Jazan region followed by the lowland Jazan and Sahil regions. Conversely, the western (Makkah, Jeddah and Madinah) and Najran populations corresponded to the global domesticated form. Given potential differences between the forms in transmission capability, ecology and behaviour, the findings here should be taken into account in vector control efforts in Saudi Arabia.