Overview
As part of my Master’s thesis research at the University of Oklahoma, I contributed to a study on “Time-, Energy-, and Monetary Cost-Aware Cache Design for a Mobile-Cloud Database System” presented at the DMAH 2015 workshop (Data Management and Analysis for Medicine and Healthcare), part of VLDB 2015 in Waikoloa, HI, USA.
Research Focus
The research addressed critical challenges in mobile-cloud database systems:
Key Problems
- Performance bottlenecks in mobile database queries
- Energy consumption optimization for battery-powered devices
- Monetary cost reduction for cloud-based data processing
- Query execution planning between mobile and cloud environments
Our Approach
We developed a cost-aware cache design that considers:
- Time efficiency: Minimizing query response time
- Energy efficiency: Reducing battery consumption on mobile devices
- Monetary efficiency: Optimizing cloud resource usage costs
- Adaptive query planning: Intelligent decision-making for query execution location
Technical Contributions
Cache Design
- Multi-dimensional cost model integrating time, energy, and monetary factors
- Adaptive caching strategies based on query patterns and resource availability
- Hybrid execution framework supporting both mobile and cloud processing
Query Optimization
- Cost-aware query planner that analyzes query complexity and resource requirements
- Dynamic decision engine for determining optimal execution location (mobile vs. cloud)
- Performance prediction models for estimating query execution outcomes
Publication Details
- Title: Time-, Energy-, and Monetary Cost-Aware Cache Design for a Mobile-Cloud Database System
- Authors: Mikael Perrin, et al.
- Conference: DMAH 2015 Workshop at VLDB 2015
- Location: Waikoloa, HI, USA
- Date: August 31 - September 4, 2015
- Publisher: Springer International Publishing
- Publication: Biomedical Data Management and Graph Online Querying: VLDB 2015 Workshops
Impact and Applications
This research has implications for:
Mobile Health Applications
- Patient data management with optimized resource usage
- Real-time health monitoring with reduced energy consumption
- Cost-effective cloud integration for healthcare providers
General Mobile Database Systems
- Improved battery life for mobile applications
- Reduced operational costs for cloud-based services
- Enhanced user experience through faster query responses
Skills and Methodologies
Through this research, I developed expertise in:
- Database system design and optimization
- Mobile computing constraints and opportunities
- Cloud computing cost models and architectures
- Performance analysis and benchmarking
- Academic research methodologies and publication
Challenges and Solutions
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Solution
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Master’s Thesis Connection
This publication represents the core research conducted for my Master’s thesis in Computer Science at the University of Oklahoma (2013-2015). The thesis focused on developing practical solutions for mobile-cloud database integration, with particular emphasis on healthcare applications where performance, energy efficiency, and cost are critical factors.
The work demonstrates my ability to:
- Conduct interdisciplinary research at the intersection of database systems, mobile computing, and healthcare
- Develop innovative solutions to complex technical challenges
- Apply rigorous scientific methodologies to real-world problems
- Communicate technical concepts effectively through academic publication
Related Technologies
- Mobile databases and data synchronization
- Cloud computing platforms and services
- Query optimization algorithms
- Performance modeling and prediction
- Energy-aware computing techniques
This research experience has been foundational to my career, providing deep insights into system optimization, resource management, and the practical challenges of mobile-cloud integration that continue to inform my work in software development today.