Revolutionary ensemble-learning method for dynamic memory configuration of serverless computing functions. Reduce resource wastage by up to 82% and save costs by up to 87% through input-aware optimization.
Transform serverless function configuration from speculation to science with AI-powered input-aware memory optimization.
🧠
AI-Powered Optimization
Multi-output Random Forest Regression model that learns input-aware resource relationships for optimal memory configuration.
💰
Massive Cost Savings
Reduce resource wastage by up to 82% and save run-time costs by up to 87% compared to traditional approaches.
⚡
Input-Aware Intelligence
Automatically detects correlations between function payload, execution time, and memory requirements for precise optimization.
🏗️
MAPE Control Loop
Monitor, Analyze, Plan, and Execute framework for continuous optimization and performance improvement.
☁️
AWS Native
Built on AWS Serverless Suite with Lambda, DynamoDB, Step Functions, and S3 for seamless integration.
📊
Proven Results
Evaluated against COSE, Parrotfish, and AWS Power Tuning with superior performance across multiple benchmarks.
🏗️ MAPE Control Loop Architecture
MemFigLess implements a sophisticated MAPE (Monitor, Analyze, Plan, Execute) control loop for continuous optimization.
System Components
📊
Offline Training Module
Function profiling, data collection, and Random Forest model training
🔮
Online Prediction Module
Real-time memory estimation and constraint optimization
⚙️
Dynamic Resource Manager
Resource allocation, monitoring, and feedback loop management
🔄
Continuous Learning
Periodic model retraining and performance improvement
🏗️
MAPE Architecture
📊 Monitor
🔍 Analyze
📋 Plan
⚡ Execute
📊 Proven Performance Results
MemFigLess delivers exceptional results across diverse serverless functions and workloads.
🧮
Mathematical Functions
Matrix multiplication, linear algebra, and cryptographic operations with up to 73% resource savings.
matmullinpackpyaes
🌐
Graph Algorithms
Graph processing functions achieving up to 87% cost efficiency and 75% resource optimization.
graph-mstgraph-bfspagerank
🌐
Web Generation
Dynamic website generation and HTML processing with significant performance improvements.
chameleondynamic-html
🛠️ Technical Implementation
Built on AWS Serverless Suite with advanced machine learning and optimization algorithms.
Core Technologies
🤖Random Forest Regression (Scikit-Learn)
☁️AWS Lambda & Step Functions
🗄️AWS DynamoDB & S3
📊AWS CloudWatch Monitoring
🐍Python 3.12 Implementation
Advanced Features
🎯Input-aware resource estimation
⚖️Constraint optimization
🔄Continuous model retraining
📈Performance monitoring
💾Automated workflow execution
🔬 Research Impact & Recognition
MemFigLess represents cutting-edge research in serverless computing optimization and resource management.
📚
Published Research
Presented at UCC '24 - The Seventeenth International Conference on Utility and Cloud Computing in Sharjah, UAE.
Conference: UCC '24
Location: Sharjah, UAE
Pages: 346-355
Publisher: IEEE CS Press
🏆
Key Contributions
Novel approach to input-aware serverless function configuration with proven cost and performance benefits.
✓Input-aware resource optimization
✓Multi-objective constraint solving
✓Real-world AWS deployment
✓Comprehensive benchmarking
Ready to Optimize Your Serverless Functions?
Join the future of intelligent serverless optimization with MemFigLess. Experience unprecedented cost savings and performance improvements through AI-powered memory configuration.