Projects

Elastic Application Using Cloud Computing

An application that scales itself based on real-time request volume and CPU usage.

Problem
Applications need to handle variable load without manual intervention, and the scaling approach needed to work across more than one kind of cloud environment.
Role
Designed and built the application and its scaling logic.
Decision
Built auto-scaling targeting both a public cloud (AWS) and a hybrid cloud (OpenStack) rather than a single provider, so the scaling logic wasn’t tied to one platform’s specific APIs.
Outcome
The application scaled automatically based on request volume and CPU usage across both AWS and OpenStack.
Cloud ComputingAWSOpenStackAuto-scaling

Multimedia Storage, Retrieval, and Similarity Simulation

A simulated database comparing feature representation and indexing techniques for multimedia retrieval.

Problem
Different feature representation, indexing, and classification techniques trade off differently for multimedia storage, retrieval, and similarity search, and those trade-offs needed to be evaluated concretely rather than assumed.
Role
Built the simulation and ran the evaluation.
Decision
Compared multiple feature representation, indexing, and classification techniques against the same dataset rather than committing to a single approach upfront.
Outcome
Benchmarked similarity-search performance across techniques using a dataset of 4,000 images.
DatabasesInformation RetrievalData Indexing