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Thesis Plan

1. Abstract

• Brief overview of LSM trees and their importance in modern database systems.
• Significance of dynamic parameter optimization for LSM-based databases.
• Problem statement
• Submit thesis proposal

2. Literature Review

• Review existing literature on LSM-based databases, RocksDB, and parameter optimization techniques like MLOS.

3. Data Generation and Preprocessing (2 week)

• Develop a Python program to generate a representative database.
• Populate RocksDB
• Run workload
• Collect performance metrics

4. Parameter Identification (2 week)

• go through with options.h/advanced_options.h file to identify dynamically configurable parameters
• Implement a profiling mechanism to identify critical parameters that impact performance.
• Analyze the collected data to identify key parameters.

5. Interface design (2 weeks)

• the interface should run rocksdb in the background and collect performance metrics
• run another process parallely to dynamically tune parameters based on the performance metrics

5. Optimization Strategy Design (4 weeks)

• Define the optimization problem - cost model
• Develop an optimization strategy for dynamically adjusting critical parameters.
• Consider MLOS based approaches for adaptive parameter tuning.
• Create an objective function that takes parameters to be optimzed - size ratio, bloom filter settings

6. Parameter Optimization Implementation (3 weeks)

• Implement the designed optimization strategy into RocksDB.
• Develop an interface for real-time parameter adjustments.
• Ensure the system can self-optimize based on performance metrics.
• Plot graphs for performace - latency, throughput, disk space usage

7. Database Benchmarking Framework (3 weeks)

• Develop a comprehensive benchmarking framework - we need to focus on latency and throughput.
• Include various workloads, scalability tests, and performance metrics.

8. Experimental Evaluation (3 weeks)

• Conduct extensive experiments using the generated database.
• Compare the performance of the optimized database against default settings.