A Systematic Literature Review on the Evolution of Skyline Query on Uncertain Database: Trends and Insights

Skyline Query, one of the profound tools that holds up tremendously when it comes to extracting valuable insights has witnessed multiple significant evolutions both in application domain and problem complexity over the years. In this SLR (Structural Literature Review), this study has tried to investigate the trends, evolutions of the application domain, and problem complexity from as early as 2008 until now. The authors divided the timespan into three major periods and analyzed 28 Scopus-indexed papers which this study chose using the PRISMA methodology. When looking at insights on application domain evolution, in the early years fundamental algorithmic research was taking place and it gradually shifted towards more specialized applications such as smart cities, IoT, and distributed computing. As the domains evolved, the complexity of the problems also spiked as a need to handle higher dimensionality in data, larger volume, and increased uncertainty became apparent. This paper provides impactful insights into how skyline query research domains have changed and tries to highlight future directions for addressing newer and more complex data management challenges.