M.C.S. Brayan Luna Nuñez

I joined the Claro Música project as the technical lead on a 5 developers team with the aim on stabilizing and reengineering the application in order to reduce crashes, errors and development times for new requirements, my main activities and contributions were:

• Diagnose and solve/follow-up priority bugs.
• Estimate, assign, review and integrate new requierements.
• Carry out the technical interview for new Android developers.
• Use Android Profiler to search for I/O and memory bottlenecks.
• Reduce 15Mb from APK size by removing old/unused/redundant code and dependencies.
• Refactor to image and services modules to improve error handling and optimize APP performance (Startup time reduced by ~3s).
• Integrate react-native and redux so that they could couple more naturally with the components that the application already had.

I joined the Android development team working on the redesign and reengineering of the Claro Video application for STB (Set-Top Box), this was the first major update in about a year and within my main contributions were:

• Complete development of the music streaming section.
• Image loading optimization using cache and pre-loading mechanisms in the most critical sections.

After the STB release, our team was divided in order to attend both the STB and the mobile application where I contributed with:

• Implementation of the Electronic Program Guide (EPG) used in the Live TV section.
• Refactor and stabilization of Chromecast integration (both sender and receiver) complying with Google's acceptance criteria.
• I was lead for the 3 developers team (including me) who carried out the 2016 Olympic Games broadcasting inside the Claro Video application.

Thesis: An Ontology-Driven Framework for Resource-Efficient Collaborative Sensing The framework is composed by a set of distributed and local algorithms which use in-network processing to find the most suitable device in the network for performing a sensing task. The device is selected based on physical distance, communication distance (hops), and semantic similarity between the requested service and the services offered by each device. The proposed algorithms are proven to be correct and were implemented on the Network Simulator v3 for performance measurement and comparison against a centralized approach.