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1. US20050256971 - Runtime load balancing of work across a clustered computing system using current service performance levels

Office
United States of America
Application Number 11168967
Application Date 27.06.2005
Publication Number 20050256971
Publication Date 17.11.2005
Publication Kind A1
IPC
G06F 7/00
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
7Methods or arrangements for processing data by operating upon the order or content of the data handled
G06F 9/46
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
9Arrangements for program control, e.g. control units
06using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
46Multiprogramming arrangements
G06F 9/50
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
9Arrangements for program control, e.g. control units
06using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
46Multiprogramming arrangements
50Allocation of resources, e.g. of the central processing unit
G06F 17/30
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
17Digital computing or data processing equipment or methods, specially adapted for specific functions
30Information retrieval; Database structures therefor
Applicants ORACLE INTERNATIONAL CORPORATION
Inventors Colrain Carol
Simmons Charles
Semler Daniel
Pommerenk Stefan
Pruscino Angelo
Agents HICKMAN PALERMO TRUONG & BECKER/ORACLE
Priority Data 10917715 12.08.2004 US
11168967 27.06.2005 US
60495368 14.08.2003 US
60500096 03.09.2003 US
60652368 11.02.2005 US
Title
(EN) Runtime load balancing of work across a clustered computing system using current service performance levels
Abstract
(EN)

Runtime load balancing of work across a clustered computing system involves servers calculating, and clients utilizing, current service performance grades of each instance in the system. A performance grade for an instance is based on performance metrics for that instance, where the computation used may vary by policy. Examples of possible policies include: (a) using estimated bandwidth as a performance grade, (b) using spare capacity as a performance grade, or (c) using response time as a performance grade. Clients distribute work requests across servers in the system as the requests arrive. Work requests can be distributed according to performance grades, and/or flags associated with the performance grades. Automatically and intelligently directing work requests to the best server instances, based on real-time service performance metrics, minimizes the need to manually relocate work within the clustered system.


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