Runtime Autonomous Component Management Systems

CMS Runtime Component Optimizer We have designed software APIs for CMS Runtime Optimizer Develop general-purpose and application specific Runtime Optimizer using these APIs Switching Supports for CMS Load balancing Mechanism Supports Stateful and Stateless invocation Work-flow model

Runtime Autonomous Component Management Systems SIP/Mobile RMI integration Protecting transmitted data when composing components dynamically in a distributed environment Supporting more types of mobility using Session Initiation Protocol (SIP) and Mobile RMI complementally Combine both mechanism to a single integrated mechanism to reduce overhead and redundancy Integrate SIP servers with Mobile RMI facilities

Mechanism Diagram Network Processor Linux Host Cluster2 Cluster1 Client1 Client2 CMS Client1 CMS Client2 CMS Cluster1 CMS Cluster2 CMS

.NET Remoting An emerging object-oriented remote-procedure-call protocol under Microsoft ’ s.NET framework, like RMI in JAVA Let programmer concentrate on business logic instead of socket operation in network application Three Service Activated Mode: Both Singleton and Client- Activated modes provide the stateful access Single Call C1 Client Side C2 S1 Server Side Singleton C1 Client Side C2 S1 Server Side Client-Activated C1 Client Side C2 S1 Server Side

Load Balancing Mechanisms We propose two methods: ETT (Estimated- Task-Time) Scheduling Method EFT (Earlier- Finished-Time) Scheduling Method : Consider the Workflow Graph Find a least load server Dispatch In TCP connection table Start Find service type Stateful? In Session table? Apply previous server yes no Find a least load server Insert session table no yes

ETT Scheduling Method We use the Estimated-Task-Time model to calculate the cluster states at run-time. Use given computation cost and communication cost to estimate the total execution time to be consumed. Calculating the ETT values of each cluster to find out the server for assignments.

EFT Scheduling Method --Handle Workflow Graph To cope with application when given a workflow graph, we propose a scheduling policy. We use a two-phase algorithm: Phase 1: Schedule the stateful tasks. Phase 2: Schedule the remained stateless tasks and dispatch the stateful tasks which have been scheduled at phase 1. Use a Time-Out policy to re-schedule stateful tasks when timeout constraints are met during phase 2.

Phase 1 of EFT algorithm We balance the total load of each stateful task groups to each server. Decide the target server for tasks to be assigned.

Phase 2 of EFT algorithm We use the rank function to find out the critical path to decide the execution order. Use Earlier-Finish-Time Function to find out the server to finish the task early. If the stateful group has met time-out constraint, the group of the tasks will be rescheduled. Stateful Assign task by the Rank order Time out Schedule task by EFT function Schedule task by phase 1 decision Restart Phase 1 Dispatch no yes no

Experimental Result We examine our implementation in IXP1200 which was compared with Microsoft NLB. We experiment with our workload algorithms EFT by simulations. We use 500 graph instances for evaluating each parameter settings. The performance results with ETT and EFT is normalize to the results of Round-robin (RR). ParameterValue V25, 50, 100, 200, 400 S1 O2, 3, 4 CCR0.3 Stateful groups2, 4, 8 Stateful task ratio 0.25, 0.5

Experiment result of 25% stateful task graph sets Experimental Result

Experiment result of 50% stateful task graph sets Experimental Result

Summary We proposed a load balancing methodology which supports stateful service access. We can see that the EFT algorithm has significant performance improvement compared to ETT and RR. While the stateful task ratio is 50%, the improvement of EFT is from 5% to 21% when compared to ETT and is from 8% to 34% when compared to RR.

本年度計畫產出物 – 論文 “ Efficient Switching Supports of Distributed.NET Remoting with Network Processors. ” C. K. Chen, Y. H. Chang, C. W. Chen, Y. T. Chen, C. C. Yang, and Jenq-Kuen Lee. ICPP “ Switching Supports for Stateful Object Remoting on Network Processors ”, C. K. Chen, Y. H. Chang, Y. T. Chen, C. C. Yang, and Jenq Kuen Lee, accepted, Journal of Supercomputing, (Special Issue for Selected Papers of CTHPC 2005). „ Mobile Java RMI Support over Heterogeneous Wireless Networks “, C. K. Chen, C. W. Chen, C. T. Ko, Jenq-Kuen Lee and Jyh-Cheng Chen, Submitted to IEEE Transcation on Mobile Computing. – 專利 1. Jenq-Kuen Lee, Jyh-Cheng Chen, Cheng-Wei Chen, Chung-Kai Chen, “ Method and System for Providing Roaming of Remote Object Procedure Call in Heterogeneous Wireless Network Environment, Pending Patent ( 已申請台灣專利, 美國專利申請中 ). 2. “ Mechanism for Supporting Stateful Object Remoting ”, 準備提出專利 申請 ( 台灣及美國 ).