System and method for modeling and provisioning information system capacity

• US 20020019873A1
• Filed: 01/26/2001
• Published: 02/14/2002
• Est. Priority Date: 07/14/2000
• Status: Abandoned Application

• Current Assignee: Cotagesoft Incorporated
• Original Assignee: Cotagesoft Incorporated
• Inventors: Goldszmidt, Moises, Sabata, Bikash, Palma, Derek, Raha, Amitava
• Application Number:
  US09/770,828
• Publication Number:
  US 20020019873A1
• Time in Patent Office: Days
• US Class Current: 709/228
• CPC Class Codes: G06F 2209/504 Resource capping
• CPC Class Codes: G06F 2209/508 Monitor
• CPC Class Codes: G06F 9/4881 Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
• CPC Class Codes: G06F 9/5027 the resource being a machine, e.g. CPUs, Servers, Terminals
• CPC Class Codes: H04L 67/01 Protocols
• CPC Class Codes: Y02D 10/00 Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

Models of capacity of an information system are described. The models may be queried when a new session arrives at the information system, to determine whether to accept the session as is, demand new capacity from an alternate server in order to fulfill the session, or reject the session. The models employ feature vectors to represents states of the information system. Parameters in the feature vectors may include load measurements on CPUs in the information system; load measurements on memory in servers employed in the information system; transactions per second conducted in databases in the information system; rate at which requests arrive from referral URLs to the information system; number of sessions in the information system; CPU utilization in the information system; database utilization in the information system.

Claims

1. A method of accepting a session in a network server, the method comprising:

generating a feature vector for the session, the feature vector comprising a first plurality of parameters, the first plurality of parameters defining a proposed additional load of the session on the network server;

etermining a current state vector of the network server, the current state of the network defined by a second plurality of parameters, the current state vector defining a current load on the network server at a time instant;

determining a headroom vector for the current state of the network, the headroom vector defined by a distance between a model surface, the model surface indicating a capacity of the network server;

comparing a magnitude of the headroom vector to a magnitude of the feature vector.

2. The method of claim 1, further comprising:

if the magnitude of the headroom vector is greater than the magnitude of the feature vector, accepting the session in the network server.

3. The method of claim 1, further comprising:

if the magnitude of the headroom vector is less than the magnitude of the feature vector, rejecting the session from the network server.

4. The method of claim 1, further comprising:

if the magnitude of the headroom vector is greater than the magnitude of the feature vector, demanding an extra capacity from a second network server, the second network server in communication with the first network server.

5. The method of claim 4, further comprising:

after demanding the extra capacity, accepting the session at the network server.

6. The method of claim 1, wherein the each of the first and second plurality of parameters includes a metric for CPU loads on the network server.

7. The method of claim 1, wherein the each of the first and second plurality of parameters includes a metric for memory utilization on the network server.

8. The method of claim 1, wherein the each of the first and second plurality of parameters includes a metric for transactions per second conducted in databases on the network server.

9. The method of claim 1, wherein the each of the first and second plurality of parameters includes a number of network sessions conducted on the network server.

10. The method of claim 1, wherein the each of the first and second plurality of parameters includes a metric for database utilization on the network server.