Dynamic capacity management of multiple parallel-connected computing resources
AssigneesCarnegie Mellon University, Intel Corporation
InventorsMor Harchol-Balter, Anshul Gandhi, Varun Gupta, Michael Kozuch
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AssigneesCarnegie Mellon University, Intel Corporation
InventorsMor Harchol-Balter, Anshul Gandhi, Varun Gupta, Michael Kozuch
Estimating the term…
A dynamic capacity management policy for multi-paralleled computing resources (e.g., application servers, virtual application servers, etc.) that includes one or more of a state-change component, a load-balancing component, and a robustness-control component. The state-change component delays the release (e.g., powering down of a physical server, removal from a virtual-server lease, etc.) of each computing resource for a set amount of time. The load-balancing component can work in conjunction with the state-change component to reduce the number of idle computing resources by distributing incoming requests in a manner that keeps the already-processing computing resources as full of requests as possible. The robustness-control component scales capacity as a function of the current number of requests within the system of computing resources to account for variations other than request rate, such as request size, reduced processor frequency, network slowdowns, etc., that affect processing capacity.
A method of controlling a plurality of computing resources each having a lower-setup-cost state and a higher-setup-cost state, comprising:
A processing system for processing an incoming request stream, comprising:
A machine readable storage medium containing machine-executable instructions for controlling a plurality of computing resources in processing an incoming request stream, wherein each of the plurality of computing resources has a lower-setup-cost state and a higher-setup-cost state, said machine-executable instructions comprising:
Dependencies are inferred from the claim text.