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A Self-Manageable Infrastructure for Supporting Web-based Simulations Yingping Huang Xiaorong Xiang Gregory Madey Computer Science & Engineering University of Notre Dame Sponsored by NSF/ITR-DEB Outline Introduction Self-manageable infrastructure Autonomic Computing Web-based Simulations Self-Configuring Self-Healing Self-Optimizing Self-Protecting Conclusion and future work Autonomic Computing Motivation What’s next? – A dozen information technology research goals (J. Gray, Microsoft Research) Goal The SysAdmin sets system goals and high level polocies http://www.ibm.com/autonomic System takes care of itself Autonomic Computing (cont) Self-Configuring Self-Healing Completed simulations Self-Optimizing New simulations, new simulation servers Efficient usage of system resources Self-Protecting No unauthorized access Web-based Simulations Features of Web-based simulations Simulations run on the simulation servers Simulation data is downloadable for users Simulation reports are generated dynamically Simulation status is sent to users by email Collaboration among users Challenges Reliability Availability Efficiency Security Motivation: NOMSIM Simulate natural organic matter (NOM) evolution behavior Agent-based stochastic simulation method Multi-disciplinary project that involves chemists, biologists, environmental scientists, geologists and computer scientists Collaboration is essential Funded by NSF-ITR Outline Introduction Self-manageable infrastructure Autonomic Computing Web-based Simulations Self-Configuring Self-Healing Self-Optimizing Self-Protecting Conclusion and future work The Infrastructure Features of the Infrastructure Scalability Web server tier: new application servers can be added to the balanced application server cluster Simulation server tier: can be scaled almost linearly by installing new simulation servers running identical simulations Database server tier: real application cluster (RAC) enables all active instances executing transactions against a shared database Features of the Infrastructure (cont) Availability Web server tier: eliminates single point of failure by redundancy and failover, and session state is maintained in the database server tier Simulation server tier: simulation checkpointing and resuming Database server tier: eliminates single point of failure by redundancy and failover Simulation Metadata <simulation name="nomsim"> <db_url> <url>jdbc:oracle:thin:username/password@hostname:port:sid</url> <username>dbusername</username> <password>dbpassword</password> </db_url> <input_part> <input name="time" type="number" /> <input name="temperature" type="number" /> <input name="granted" type="char(1)" /> <input name="molecule_name" type="varchar2(50)" /> </input_part> </simulation> Simulation Manager and Intelligent Agents One intelligent agent runs on one simulation server Functionalities of intelligent agents Register new simulation servers to simulation manager Reports metrics of simulation servers to simulation manager Deploy new simulation models Check for simulation jobs Transport data from simulation servers to database servers Cancel simulation jobs as directed by the simulation manager Functionalities of simulation manager Dispatch and manage simulation jobs Notify users simulation job status Self-Configuring <simulation name="nomsim"> <db_url> <url>jdbc:oracle:thin:username/password@hostname:port:sid</url> <username>dbusername</username> <password>dbpassword</password> </db_url> <input_part> <input name="time" type="number" /> <input name="temperature" type="number" /> <input name="granted" type="char(1)" /> <input name="molecule_name" type="varchar2(50)" /> </input_part> </simulation> HTML form JSP Code JavaScript Form Validation Database Table Self-Configuring (cont) On simulation servers Intelligent agents must run Install simulation software (To simplify: the simulation software is installed on an NFS server and which is mounted on the simulation servers) On simulation manager Email masquerading Self-Healing Self-Healing Web servers Self-Healing simulation servers Clustered application server instances Automatic recovery of failed instance Simulation checkpointing Simulation resuming Self-Healing database servers Clustered database instances Automatic recovery of failed instance Raid 0+1 Self-Healing (cont) Checkpointing Simulation Simulation Server Tier Resuming RDBMS Database Server Tier Self-Protecting Role based access control Firewall Public Owner Grant Port scan IPTABLES Log messages scanning Network traffic monitoring, Intrusion Detection (Future work) Self-Optimizing Self-Optimizing web server tier Load balanced application server cluster Self-Optimizing database servers Database parameter self-tuning Online index rebuilding Summary and aggregation Self-Optimizing (cont) Time DBMS Migrate Checkpoint Simulation Server 1 Simulation Server 2 Implementation of self-* Tools IBM’s ABLE (agent building and learning environment) Oracle Data Mining Unix Crontab Languages Java SQL and PL/SQL Bourne shell scripts Outline Introduction Self-manageable infrastructure Autonomic Computing Web-based Simulations Self-Configuring Self-Healing Self-Optimizing Self-Protecting Conclusion and future work Conclusions and Future Work Conclusions Self-Manageable infrastructure Intelligent agents Simulation manager Future work Applying data mining “Intelligent agents” Proactive critical event prediction Job completion time prediction Questions? 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