Dynamic Skyline Computation with BJR-Tree

A Data Structures project implementing BJR-Tree for dynamic skyline computation, processing multi-dimensional datasets with continuous point insertions and deletions to maintain optimal skyline results over time. The main program is compiled from main.cpp while the core BJR-Tree structure is implemented in modules.hpp.

📥 Dataset Download

The dataset is not included in this repository. Download it from:

🔗 https://s33.picofile.com/file/8484976226/dataset.rar.html

After downloading, extract the files into the project structure:

dataset/
├── small/
├── medium/
└── large/

Key Features

• Dynamic Processing: Handles real-time point injections and ejections

• BJR-Tree Implementation: Optimized tree structure for skyline maintenance

• Multiple Optimizations:

  • Lazy evaluation for tree balancing
  • ND-cache for fast dominance checks
  • Time-window caching

• Scalable: Supports up to 800,000 points across 40,000+ timesteps

• Multi-dimensional: Works with 4D-7D datasets

Quick Start

# Clone & setup
git clone https://github.com/your-username/skyline-computation-bjr-tree.git
cd skyline-computation-bjr-tree
mkdir -p dataset/small dataset/medium dataset/large

# Add downloaded dataset files to appropriate folders
# Then build and run
make
# Should configure then run main.cpp

Configuration Options

Setting	Values	Description
version	"small", "medium", "large"	Choose dataset size
use_lazy	true, false	Enable/disable lazy evaluation
use_nd_cache	true, false	Enable/disable ND-cache optimization

🎓 Academic Project Developed for Data Structures course (Spring 2025). Implements BJR-Tree algorithms for dynamic skyline computation.