Distributed Transaction Server
Scalable fault-tolerant stock trading platform with Paxos consensus
Designed and implemented a scalable three-tier stock trading platform (Frontend, Backend — Catalog and Order services) capable of handling high user concurrency through a dynamic thread-pool scheduling model.
Some highlights of this project are:
- Achieved redundancy and fault tolerance via Bully Leader Election and Paxos-based consensus, ensuring consistent state synchronization across replicas under node failures.
- Enhanced frontend performance with an LRU caching layer that reduced latency for frequent stock lookup requests.
- Stress-tested the system under high concurrency to validate throughput and consistency guarantees.
Advisor: Prof. Prashant Shenoy, UMass Amherst.
Figure: Client-server model by Calimo (derived from work by David Vignoni), LGPL, via Wikimedia Commons.