Emc IP Holding Company LLC

Rachel L Traylor

Mark Chamness

Craig Struble

Richard Mark Stern

Embodiments are directed to a method and system for allocating common resources for a user in a cloud computer network, by: monitoring system reliability and resource charges; estimating a reliability based on the monitored system reliability and simulating resource provisioning choices to measure an impact of resource provisioning on the estimated reliability; estimating a cost based on the monitored resource charges; and allocating network resources based the estimated cost and simulated resource provisioning choices.

Hybrid reliability and cost-based method for resource allocations in software defined infrastructures

A method for predicting disk failures in a RAID environment is provided. A data collection center receives hard disk status information from one or more sets of hard disks in a storage system. For each of the sets of hard disks, the data collection center calculates a transitional probability that a hard disk will fail within a predetermined period of time based on the hard disk status information, and generates a first risk profile for the hard disk based on the calculated transitional probability. The data collection center then generates a second risk profile for a set of hard disks based on two or more of the first risk profiles, and compares the second risk profiles of the sets of hard disks to determine which of the sets of hard disks has a highest probability of failing within the predetermined period of time.

Method for dynamically modeling medium error evolution to predict disk failure

Systems and methods are disclosed for predicting failure of a hard disk in a storage system. Embodiments are disclosed that predict failure of at least one hard disk in a storage system having a plurality hard disks. A data center reports to a data collection center than a hard disk has reported an initial non-zero medium error count (NMEC). The data collection center stores historic data of initial NMEC for many hard disks, and subsequent failure of those hard disks. From the historic data, the data collection center can report to the data center a prediction of when a hard disk reporting an initial NMEC may fail. Different models of hard disks fail at different times relative to a reported initial NMEC. The data collection center can track historic hard disk data by manufacturer, model of hard disk, and by model of storage system and thus can predict, by hard disk model, a probability of failure of a hard disk.

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San Jose, CA, United States of America

Rachel L Traylor