Oracle International Corporation

Greg Edvenson

Tyler Ogren Vrooman

Graham Schwinn

Matthew Charles King

Kumud Nepal

Example embodiments facilitate prioritizing the recycling of computing resources, e.g., server-side computing systems and accompanying resources (e.g., non-volatile memory, accompanying firmware, data, etc.) leased by customers in a cloud-based computing environment, whereby computing resources (e.g., non-volatile memory) to be forensically analyzed/inspected, sanitized, and/or updated are prioritized for recycling based on estimates of when the computing resources are most likely to require recycling, e.g., via background sanitizing and updating. Computing resources that are likely to be recycled first are given priority over computing resources that are more likely to be recycled later. By prioritizing the recycling of computing resources according to embodiments discussed herein, other cloud-based computing resources that are used to implement computing resource recycling can be efficiently allocated and preserved.

Predictive recycling of computer systems in a cloud environment

The present memory restoration system enables a collection of computing systems to prepare inactive rewritable memory for reserve and future replacement of other memory while the other memory is active and available for access by a user of the computing system. The preparation of the reserved memory part is performed off-line in a manner that is isolated from the current user of the active memory part. Preparation of memory includes erasure of data, reconfiguration, etc. The memory restoration system allows for simple exchange of the reserved memory part, once the active memory part is returned. The previously active memory may be concurrently recycled for future reuse in this same manner to become a reserved memory. This enables the computing collection infrastructure to 'swap' to what was previously the inactive memory part when a user vacates a server, speeding up the server wipe process.

Concurrent memory recycling for collection of servers

Example embodiments employ a selective memory swapping system for selectively placing non-volatile memory devices of a computer system offline, e.g., for background updating, and online, for use by a computer system, whereby the background updating process includes a mechanism for performing forensics analysis and updating of offline memory devices while an alternate memory device is usable by a user of the first computer system.

Memory device forensics and preparation

Example embodiments facilitate prioritizing the recycling of computing resources, e.g., server-side computing systems and accompanying resources (e.g., non-volatile memory, accompanying firmware, data, etc.) leased by customers in a cloud-based computing environment, whereby computing resources (e.g., non-volatile memory) to be forensically analyzed/inspected, sanitized ,and/or updated are prioritized for recycling based on estimates of when the computing resources are most likely to require recycling, e.g., via background sanitizing and updating. Computing resources that are likely to be recycled first are given priority over computing resources that are more likely to be recycled later. By prioritizing the recycling of computing resources according to embodiments discussed herein, other cloud-based computing resources that are used to implement computing resource recycling can be efficiently allocated and preserved.

Growing community of inventors

Seattle, WA, United States of America

Greg Edvenson