CSci 8980 Mobile Cloud Computing. Outsourcing: Components

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1 CSci 8980 Mobile Cloud Computing Outsourcing: Components

2 Cloud as an Outsourcing Platform Cloud Mobile Users 2 Benefits: Scalability, elasticity: Can scale up to large number of users on-demand Sharing: Can share data and computation across multiple users/applications Problem: Network latency

3 Mobile Outsourcing to Cloud: Key Questions Question 1: Is cloud a feasible mobile outsourcing platform despite higher network latencies? Question 2: How can we detect and exploit sharing across applications for better performance and efficiency? Our Focus: Cloud-side optimizations for efficiency and performance of mobile outsourcing 3

4 Outline Motivation Mobile-to-Cloud Outsourcing Platform Feasibility of Cloud for Outsourcing Sharing-aware Application Placement Experimental Evaluation Conclusion

5 Mobile-to-Cloud Outsourcing Platform Code Repository Cloud (Amazon EC2) Component Manager Offloading Servers (VMs) Mobile Users (Android)

6 Feasibility of Cloud for Outsourcing Setup: Android HTC Hero phone, 1 small EC2 instance Network latency: WiFi: 82ms, 3G: 151ms, wired: 44ms Application: Image processing Blur Filter Performance Energy Consumption Cloud is desirable for compute-intensive applications

7 Data Sharing Between Applications Applications often share common data E.g.: Intermediate data between Image processing and Face detection Image Processing Face Detection Input Intermediate Output

8 Data Sharing with Outsourcing Data sharing method determined by application locations

9 Time(Sec) Time(sec) Impact of Application Location on Performance Image Size: 405x405 Image Size: 800x Comm. Time Comp. Time Local NS Strg Comm Intra Data Sharing Method Comm. Time Comp. Time Local NS Strg Comm Intra Data Sharing Method Desirable to co-place sharing applications together

10 Sharing-aware Application Placement Detects the application components that have potential to share data Association analysis: Sequence mining on temporal data access Co-locate such components on same server

11 Other Application Placement Strategies User-centric Mobile users are assigned dedicated servers No users share servers Good for cross-application data sharing Application-centric Components are assigned to dedicated servers Multiple users can share the same component on the same server Good for resource utilization

12 Dynamic Provisioning Scale the number of servers According to CPU utilization state High/Low thresholds for detecting overloaded/underloaded servers Create server: when all servers are overloaded Merge server: when a server is underloaded

13 Outline Motivation Mobile-to-Cloud Outsourcing Platforms Feasibility of Cloud for Outsourcing Sharing-aware Application Placement Experimental Evaluation Conclusion 13

14 Experimental Setup Amazon EC2 offloading platform Component manager, code repo: small instances Offloading servers: Micro instances Emulated mobile workload 100 users, 10 image processing components Some requests share data among components Metrics Server utilization: measures resource efficiency on the cloud Network traffic: measures user performance and outsourcing overhead

15 Number of offloading servers Server utilization User-centric App-centric Co-location Number of mobile users Sharing-aware Co-location is close to App-centric in efficiency

16 Total network traffic normalized to no-sharing Network traffic 100% 95% 90% 85% 80% 75% 70% 65% User-centric App-centric Co-location Optimal 60% 0% 11% 28% 40% 63% Percentage of sharing requests Sharing-aware Co-location is close to Usercentric (and optimal) in network overhead

17 Co-location rate(%) Co-location rate 100% 90% 80% 70% 60% 50% User-centric App-centric Co-location 40% 30% 11% 28% 40% 63% Percentage of sharing requests Sharing-aware placement achieves high colocation rate

18 Requests/second Number of servers Dynamic Provisioning Request rate Number of Server Time(min) Num servers varies according to workload

19 Conclusion Cloud is a desirable outsourcing platform for mobile computation Cloud provides cross-application sharing opportunities as well as dynamic scalability Sharing-based application placement can achieve high efficiency as well as performance