Abstract: A diagnostic system monitors the status of other processes over a computer network by collecting status and configuration data, analyzing the data and providing diagnostic recommendations when necessary. The diagnostic system includes a collector module, an analyzer module and an administration client module. The collector module collects statistical data and configuration data from each monitored process and populates a plurality of source data tables or worksheets. The values of the source data are processed by the analyzer module, including component algorithms, which generate a plurality of individual component indexes each associated with a specific aspect of the processes performance. The component indexes are then processed using a weighting algorithm to form a composite index reflecting the overall health of the monitored process.

Abstract: The present invention allows complex messaging configurations (e.g., server clusters) and messaging activities to be simulated in a single test. A server cluster having two or more mail servers is provided. Each server in the cluster is assigned one or more mail databases that are also replicated to the other servers in the cluster. Thus, each server has a copy of every mail database. Mail clients are then assigned to specific mail servers (e.g., 50% of the mail clients are assigned to mail server “1,” 50% of the mail clients are assigned to mail server “2”). The present invention will drive a messaging workload against the servers (in a single test) that will simulate the type of messaging activity that is typically experienced when the servers are in actual use within an organization or business.

Abstract: A diagnostic system monitors the status of other processes over a computer network by collecting status and configuration data, analyzing the data and providing diagnostic recommendations when necessary. The diagnostic system includes a collector module, an analyzer module and an administration client module. The collector module collects statistical data and configuration data from each monitored process and populates a plurality of source data tables or worksheets. The values of the source data are processed by the analyzer module, including component algorithms, which generate a plurality of individual component indexes each associated with a specific aspect of the processes performance. The component indexes are then processed using a weighting algorithm to form a composite index reflecting the overall health of the monitored process.

Abstract: A diagnostic system monitors the status of other processes over a computer network by collecting status and configuration data, analyzing the data and providing diagnostic recommendations when necessary. The diagnostic system includes a collector module, an analyzer module and an administration client module. The collector module collects statistical data and configuration data from each monitored process and populates a plurality of source data tables or worksheets. The values of the source data are processed by the analyzer module, including component algorithms, which generate a plurality of individual component indexes each associated with a specific aspect of the processes performance. The component indexes are then processed using a weighting algorithm to form a composite index reflecting the overall health of the monitored process.

Abstract: A diagnostic system monitors the status of other processes over a computer network by collecting status and configuration data, analyzing the data and providing diagnostic recommendations when necessary. The diagnostic system includes a collector module, an analyzer module and an administration client module. The collector module collects statistical data and configuration data from each monitored process and populates a plurality of source data tables or worksheets. The values of the source data are processed by the analyzer module, including component algorithms, which generate a plurality of individual component indexes each associated with a specific aspect of the processes performance. The component indexes are then processed using a weighting algorithm to form a composite index reflecting the overall health of the monitored process.

Abstract: A meeting management device of a computer system determines the optimal meeting date and time for a specified group of invitees within a set of specified time parameters. A subset of the invitees are designated as critical along with any specified pieces of equipment and desired meeting sites. Remote from personal calendars of the invitees, the device compares available dates and times of each critical invitee with each other and that of any critical pieces of equipment and meeting sites. The comparison determines common available dates and times in which to schedule the meeting. Available or unavailable dates and times of each invitee are defined in part by the invitee and in part by other scheduled meetings to which the invitee has been invited. The invitee may define available or unavailable dates and times automatically through his personal calendar or manually to mirror as much of his calendar as desired.