Samsung Electronics Co., Ltd.

Ping Terence Wong

Zhengyu Yang

T David Evans

Clay Mayers

Nithya Ramakrishnan

Venkatraman Balasubramanian

Olufogorehan Adetayo Tunde-Onadele

Morteza Hoseinzadeh

Thomas Edward Rainey, Iii

John Artoux

Michael Kurt Gehlen

A method of adapting a first key-value store to a second key-value store may include determining a conversion strategy based on one or more characteristics of the first key-value store and one or more characteristics of the second key-value store, converting the second key-value store to a converted key-value store based on the conversion strategy, and mapping the first key-value store to the converted key-value store based on a mapping function. The converted key-value store may be accessed on-the-fly. A data storage system may include a key-value interface configured to provide access to a lower key-value store, and a key-value adapter coupled to the key-value interface and configured to adapt an upper key-value store to the lower key-value store, wherein the key-value adapter may be configured to adapt at least two different types of the upper key-value store to the lower key-value store.

Methods and systems for adapting multiple key-value stores

A load balancing system includes: a centralized queue; a pool of resource nodes connected to the centralized queue; one or more processors; and memory coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the one or more processors to: monitor a queue status of the centralized queue to identify a bursty traffic period; calculate an index value for a load associated with the bursty traffic period; select a load balancing strategy based on the index value; distribute the load to the pool of resource nodes based on the load balancing strategy; observe a state of the pool of resource nodes in response to the load balancing strategy; calculate a reward based on the observed state; and adjust the load balancing strategy based on the reward.

Systems and methods for spike detection and load balancing resource management

A non-volatile memory (NVM) express (NVMe) system includes at least one user application, an NVMe controller and a hypervisor. Each user application runs in a respective virtual machine environment and including a user input/output (I/O) queue. The NVMe controller is coupled to at least one NVM storage device, and the NVMe controller includes a driver that includes at least one device queue. The hypervisor is coupled to the user I/O queue of each user application and to the NVMe controller, and selectively forces each user I/O queue to empty to a corresponding device queue in the driver of the NVMe controller or enables a private I/O channel between the user I/O queue and a corresponding device queue in the driver of the NVMe controller.

Hybrid framework of NVMe-based storage system in cloud computing environment

Growing community of inventors

San Diego, CA, United States of America

Ping Terence Wong