Dynamic data collection algorithm based on mobile edge computing in underwater internet of things

Abstract The Underwater Internet of Things (UIoT) has emerged as one the prominent technologies in development future ocean monitoring systems, where mobile edge elements (such autonomous underwater vehicles (AUVs)) provide a promising method for data collection from sensor nodes. However, an important part UIoT, wireless networks (UWSNs) are severely affected by dynamic environment. For instance, node locations change continuously, which significantly increases difficulty collection. To solve this problem, concept inevitable communication space (ICS) is proposed. ICS calculated analyzing variation position nodes and range. Furthermore, ICS-based algorithm (ICS-DDCA) UIoT proposed to collect data. This utilizes instead initial location further improve performance shorten time. simulation results demonstrate that compared with energy-efficient over AUV-assisted (EEDA) algorithms based on probabilistic neighborhood (PNCS-GHA), ICS-DDCA can effectively reduce time, while ensuring full completion