# US 2007/0180085 A1 · Method for building enterprise scalability models from production data

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- Number: US 2007/0180085 A1
- Document ID: US20070180085A1
- Status: Published application
- Kind: A1
- Application number: 11/345,415
- Filed: 2006-02-01
- Published: 2007-08-02
- Earliest claimed: 2006-02-01
- Assignees: Hyperformix, Inc.
- Inventors: Paul Barnett; Timothy Wise; Allan Clarke; Richard Gimarc; James Reynolds; Amy Spellmann
- Web page: https://patentgrep.com/patent/US20070180085A1

## CPC

- G06Q 10/04: Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202)
- G06Q 10/06: Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR

## Abstract

The invention provides a method for preparing a discrete event simulation model of a production network including a client and a plurality of servers on a plurality of network tiers connected by a network comprising the steps of executing a business function from the client on the production network, gathering resource data from the plurality of servers, normalizing the resource data, calculating a consumption of resources used by the plurality of servers, estimating a transaction cost associated with the consumption of resources and building a discrete event simulation model from the transaction cost.

## Claims

### Claim 1

A method of preparing a discrete event simulation model of a production network including a client and a plurality of servers on a plurality of network tiers connected by a network comprising the steps of:
executing a business function from the client on the production network;
gathering resource data from the plurality of servers;
normalizing the resource data;
calculating a consumption of resources used by the plurality of servers;
estimating a transaction cost associated with the consumption of resources; and
building a discrete event simulation model from the transaction cost.

### Claim 2 (depends on 1)

The method of claim 1 wherein the step of gathering further comprises the steps of:
deploying one of a plurality of resource monitors on each server resident on the production network;
collecting the resource data from the plurality of resource monitors; and
merging the resource data into a single file for analysis.

### Claim 3 (depends on 2)

The method of claim 2 wherein the step of normalizing further comprises the steps of:
equalizing a reporting interval in the resource data;
aggregating servers on at least one tier of the production network; and
synchronizing at least 2 timestamps present in the resource data.

### Claim 4 (depends on 2)

The method of claim 2 wherein the step of building a discrete event simulation model further comprises the steps of:
assembling a table containing the transaction costs;
approximating a flow of a transaction associated with the business function;
calculating data throughput on a network interface of the production network; and
assembling the approximated flow of a transaction associated with the business function with the calculated data throughput on a network interface of the production network.

### Claim 5 (depends on 2)

The method of claim 2 wherein the step of calculating further comprises the step of:
multiplying the calculated consumption of resources by a measurement period.

### Claim 6 (depends on 5)

The method of claim 5 wherein the step of calculating data throughput further comprises the step of:
repeating the step of multiplying and accumulating a running total of consumption of resources.

### Claim 7 (depends on 1)

The method of claim 1 wherein the step of estimating a transaction cost further comprises the step of:
dividing the calculated consumption of resources by a number of transactions performed during a measurement period.

### Claim 8 (depends on 1)

The method of claim 1 comprising the further step of:
running the discrete event simulation model on a discrete event simulation modeler.

### Claim 9 (depends on 8)

The method of claim 8 wherein the number of transactions is derived from a transaction log.

### Claim 10 (depends on 8)

The method of claim 8 wherein the number of transactions is derived from a load test.

### Claim 11 (depends on 1)

The method of claim 1 wherein the production network is a non-linear production network and the step of building an instruction table further comprises the steps of:
assuming an iteration count between at least two alternate paths on the non-linear production network;
statistically accounting for each of the at least two alternate paths on the non-linear production network; and
allocating the calculated consumption of resources among the at least two alternate paths.

### Claim 12

A computer program product adaptable for storage on a computer readable medium and operable for creating a discrete event simulation model comprising the program steps of:
gathering resource data from a plurality of resource monitors operatively disposed on a plurality of servers resident on a multi-tiered system executing a business function;
wherein the resource data includes a reporting interval, a timestamp, a resource utilization, a received packet count and a sent packet count;
equalizing at least one reporting interval in the resource data;
synchronizing at least one time stamp in the resource data;
normalizing at least one set of units in the resource data;
calculating a resource consumption for the plurality of servers;
calculating a transaction cost from the resource data;
approximating a transaction flow for a plurality of transactions related to the business function;
calculating a network throughput between the plurality of servers; and
building a discrete event simulation model from the transaction cost, the transaction flow and the network throughput.

### Claim 13 (depends on 12)

The computer program product of claim 12 wherein the program step of calculating a resource consumption for the plurality of servers further comprises the program step of:
multiplying the resource utilization during a measurement period by the length of the measurement period to arrive at a resource consumption.

### Claim 14 (depends on 13)

The computer program product of claim 13 wherein the program step of calculating a transaction cost from the resource data further comprises the program step of:
dividing the resource consumption by a number of transactions performed during the measurement period to arrive at a transaction cost.

### Claim 15 (depends on 14)

The computer program product of claim 14 further comprising the further program step of:
deriving the transaction cost for each of the plurality of transactions related to the business function.

### Claim 16 (depends on 12)

The computer program product of claim 12 wherein the step of calculating a network throughput between the plurality of servers further comprises the program steps of:
eliminating duplicate data from the sent packet count; and
eliminating duplicate data from the received packet count.

### Claim 17 (depends on 12)

The computer program product of claim 12 wherein the program step of approximating a transaction flow comprises the further program steps of:
estimating the transaction flow of a linear multi-tiered system.

### Claim 18 (depends on 12)

The computer program product of claim 12 wherein the program step of approximating a transaction flow comprises the further program steps of:
estimating the transaction flow of a non-linear multi-tiered system.

### Claim 19 (depends on 18)

The computer program product of claim 18 wherein the program step of estimating the transaction flow of a non-linear multi-tiered system comprises the further program steps of:
statistically accounting for a set of alternate paths on the multi-tiered system.