Self-learning file delegation system and method
OwnerJianfei Yang, Chaojun Zhao +3inventors
InventorsJianfei Yang, Chaojun Zhao, Xiaoyu Ren, Changxu Jiang, Srinivasa R. Chamarthy
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Abstract
A method, computer program product, and computing system for receiving a request from a client device to access a file stored in a storage system configured to be communicatively coupled to a plurality of client devices. It may be determined whether to delegate the file to the requesting client device based upon, at least in part, a reinforcement learning model, thus defining a file delegation determination. An access pattern associated with the file may be monitored. The reinforcement learning model may be updated based upon, at least in part, the monitored access pattern associated with the file and the file delegation determination.
Claims17
A computer-implemented method, executed on a computing device, comprising:
- receiving, via the computing device, a request from a client device to access a file stored in a storage system configured to be communicatively coupled to a plurality of client devices;
- determining whether to delegate the file to the requesting client device based upon, at least in part, a reinforcement learning model, thus defining a file delegation determination, wherein the file delegation determination is based upon, at least in part, a probability of receiving additional requests to access to the file from other client devices during the delegation of the file to the requesting client device, wherein delegating the file to the requesting client device includes caching the file at the requesting client device and processing any changes made to the file locally at the requesting client device;
- monitoring an access pattern associated with the file;
- generating a reward for the reinforcement learning model based upon, at least in part, the monitored access pattern associated with the file and the file delegation determination;
- and
- updating the reinforcement learning model based upon, at least in part, the generated reward and in response to a user-defined threshold number of file delegation determinations.
A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising:
- receiving a request from a client device to access a file stored in a storage system configured to be communicatively coupled to a plurality of client devices;
- determining whether to delegate the file to the requesting client device based upon, at least in part, a reinforcement learning model, thus defining a file delegation determination, wherein the file delegation determination is based upon, at least in part, a probability of receiving additional requests to access to the file from other client devices during the delegation of the file to the requesting client device, wherein delegating the file to the requesting client device includes caching the file at the requesting client device and processing any changes made to the file locally at the requesting client device;
- monitoring an access pattern associated with the file;
- generating a reward for the reinforcement learning model based upon, at least in part, the monitored access pattern associated with the file and the file delegation determination;
- and
- updating the reinforcement learning model based upon, at least in part, the generated reward and in response to a user-defined threshold number of file delegation determinations.
A computing system including a processor and memory configured to perform operations comprising:
- receiving a request from a client device to access a file stored in a storage system configured to be communicatively coupled to a plurality of client devices;
- determining whether to delegate the file to the requesting client device based upon, at least in part, a reinforcement learning model, thus defining a file delegation determination, wherein the file delegation determination is based upon, at least in part, a probability of receiving additional requests to access to the file from other client devices during the delegation of the file to the requesting client device, wherein delegating the file to the requesting client device includes caching the file at the requesting client device and processing any changes made to the file locally at the requesting client device;
- monitoring an access pattern associated with the file;
- generating a reward for the reinforcement learning model based upon, at least in part, the monitored access pattern associated with the file and the file delegation determination;
- and
- updating the reinforcement learning model based upon, at least in part, the generated reward and in response to a user-defined threshold number of file delegation determinations.
Dependencies are inferred from the claim text.