Sun Microsystems, Inc.

Krishna Kumar

Declan J Murphy

Andrew L Hisgen

Siamak Nazari

Robert J Block

Ira Pramanick

Declan Murphy

Improved techniques for managing operations of clustered computing system are disclosed. The improved techniques provide protection against potential problems encountered in operation of clustered computing. More particularly, the improved techniques can be implemented as an integral solution that provide protection against undesired partitions in space and partitions in time. The improved techniques do not require any human intervention.

Method and apparatus for managing operations of clustered computer systems

Improved techniques for controlled take over of services for clustered computing systems are disclosed. The improved techniques can be implemented to allow one sub-cluster of the clustered computing system to safely take over services of one or more other sub-clusters in the clustered computing system. Accordingly, if the clustered computing system is fragmented into two or more disjointed sub-clusters, one sub-cluster can safely take over services of the one or more other sub-clusters after the one or more other sub-clusters have been shutdown. As a result, the clustered computing system can continue to safely provide services even when the clustered computing system has been fragmented into two or more disjointed sub-clusters due to an operational failure.

Controlled take over of services by remaining nodes of clustered computing system

Improved techniques for dynamically altering configurations of clustered computing systems are disclosed. The improved techniques can be implemented to allow alteration of an existing configuration of a clustered computing system without having to completely shutdown the clustered computing system. As a result, the clustered computing system can provide uninterrupted services while the configuration of the clustered computing system is being dynamically altered, yet also safeguard against unwanted partitions in time or space.

Method and apparatus for dynamically altering configurations of clustered computer systems

Improved techniques for resolving partial connectivity in clustered computing systems are disclosed. The improved techniques allow for detection of one or more disconnections that cause a loss of full connectivity and then resolution of the disconnections by shutting down one or more appropriate nodes of the clustered computing system to regain full connectivity. As a result, the clustered computing system can effectively maintain a full connectivity condition that is often needed by software running on the nodes of the clustered computing system.

Method and apparatus for resolving partial connectivity in a clustered computing system

Method for emulating persistent group reservations on non persistent group reservation-compliant devices, apparatus to perform the method, and computer-readable storage medium containing instructions to perform the method. The present invention enables the emulation of persistent group reservations on a non persistent group reservation-compliant device, including a shared disk, to enable the disk's implementation of persistent group reservation-reliant algorithms. This in turn enables the implementation of algorithms based on persistent group reservation features substantially without modification of those algorithms. One such algorithm is a quorum algorithm. One example of persistent group reservations is found in the SCSI-3 standard. The present invention accomplishes persistent group reservation emulation, or PGRE, by storing host- and reservation-specific information on a reserved portion of the disk and using this data to emulate the steps of certain persistent group reservation features. One persistent group reservation preempt feature executes a set of steps as a single atomic action, the mutual exclusion necessary for this feature being done internally by the persistent group reservations-compliant device. To emulate this feature, the present invention uses mutual exclusion algorithm, where the disk serves as the &ldquo;shared memory&rdquo; of the algorithm. The variables needed by the algorithm are also stored in the reserved portion of the disk.

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Cupertino, CA, United States of America

Krishna Kumar