Đang chuẩn bị liên kết để tải về tài liệu:
Integrated Research in GRID Computing- P10

Integrated Research in GRID Computing- P10:The deployment process for adaptive Grid applications does not finish when the application is started. Several activities have to be performed while the application is active, and actually the deployment system must rely on at least one permanent process or daemon. | New Grid Monitoring Infrastructures 169 system and in fact needs knowledge about the semantics of the monitored data we have proposed an external module to Mercury called Event Monitor EM . In a nutshell EM implements more sophisticated push mechanisms as it is highlighted in Fig. 4. Event Monitors allow clients dynamic management and control of event-like metrics as very useful information providers for clients or management systems. We see many real scenarios in which an external client wants to have access to metrics described in the previous section regardless of their type and additionally often due to performance reasons does not want to constantly monitor their values. Figure 4. Event Monitors as external Mercury modules for event-like monitoring of resources and applications Nowadays policy-driven change and configuration management that can dynamically adjust the size configuration and allocation of resources are becoming extremely important issues. In many real use cases a resource management system may want to take an action according to predefined management rules or conditions. For example when application progress reaches a certain level the process memory usage becomes too high or dedicated disc quota is exceeded. Event Monitor was developed to facilitate such scenarios. Its main functionality is to allow an external client to register a metric in Event Monitor for receiving appropriate notifications when certain conditions are met. Strictly speaking clients can setup an appropriate frequency a default one has been set to 5 seconds of Event Monitor requests to LM. They can also use a predefined standard relational operator greater than less than etc. and different values of metrics to define various rules and conditions. Example EM rules for fine-grained enforcement of resource usage or application control are presented below Example application oriented rules in Event Monitor app.priv.jobid.LOAD tid 0.8 170 INTEGRATED RESEARCH IN GRID COMPUTING .