1. Architectures and Systems for Mobile-Cloud Computing: A Workload-Driven Perspective Prashant Nair Adviser: Moin Qureshi ECE Georgia Tech Xin Zhang Adviser: Mayur Naik CS Georgia Tech S2014-6613 3/26/2014 Silicon Valley

2. Motivation  Mobile devices have become the primary computing device years performance 3/26/2014 Silicon Valley 2G 3G 4G … … 2

3. Hello Siri, What is Mobile Cloud Computing? “Call John.” Call John “Dialing 123-456-7890” 33/26/2014 Silicon Valley

4. Mobile-Cloud: Enabling New Applications Idea: Offload Computation to Cloud 43/26/2014 Silicon Valley

5. Key Challenges 0101010 1010101 1111010 1110001 1. Interleaved I/O and computation 2. Network latency 0101010101 1010100101 1100000101 1010101101 3. Diverse and dynamic execution environment 53/26/2014 Silicon Valley

6. Our Solution: Flexible Offloading Schemes Bi-directional offloading 1101000 1000101 11000 0101010 1010101 01010 63/26/2014 Silicon Valley Challenge 1: Interleaved I/O and computation

7. Our Solution: Lower Bandwidth via Persistence Persistent cloud 0101010 1010101 1101010 1000101 01010 0001110 0010101 ∆ Challenge 2: Network latency 73/26/2014 Silicon Valley

8. Our Solution: Analytical Models for Tradeoffs Software features Network features Hardware features Analytical model Runtime decision! Challenge 3: Diverse and dynamic execution environment 83/26/2014 Silicon Valley

9. Offloading System Analytical model How to offload Offloading schemes What to offload 93/26/2014 Silicon Valley

10. Roadmap  Mobile workload tracing  Trace mobile workloads of top 150 Google Play apps  Workload characterization  Identify features common and unique to mobile workloads  Analytical models of performance and energy usage  Produce tolerable error bounds compared to hardware measurement  Mobile-cloud computing system  Show speedup and energy savings (Infrastructure implemented) (~3 months) (~6 months) 103/26/2014 Silicon Valley

11. Result of Tracing “Chess” For 10 Rounds UI AI 24 threads 3 million function calls 17 million memory reads 13 million memory writes 113/26/2014 Silicon Valley

12. Summary  Mobile devices have become the new “PC”  Big performance gap between mobile and desktop Our Proposal:  Enable desktop-class performance for mobile apps by:  Offloading computation to the cloud  Using robust analytical modeling  Enable new applications and usage models 123/26/2014 Silicon Valley