Server Migration Planning via Resource Packing Algorithm

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Solution Overview

Problem

Existing server migration techniques face challenges in efficiently planning the allocation of source servers to destination servers while ensuring resource capacity constraints are met, leading to increased operational management costs and complexity.

Innovation Solution

A server migration planning system and method that allocates source servers to destination servers based on resource usage and capacity, using a processor to select servers in descending order of resource usage and comparing resource usage with remaining capacity, with the option to switch to another destination server if the comparison-object usage exceeds the remaining amount, thereby optimizing the number of destination servers required.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual server migration planning is performed, then flexibility and adaptability are improved, but time consumption and operational complexity increase

Engineering Contradiction:

ImproveflexibilityVSAvoidtime consumption

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system enables self-service automation where the migration planning system automatically performs allocation calculations and generates migration plans without requiring manual intervention. The processor automatically reads resource data, performs packing algorithms, and outputs migration plans, eliminating the time-consuming manual planning process while maintaining adaptability through configurable parameters.

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If the number of destination servers is increased, then resource capacity and flexibility are improved, but operational management costs increase

Engineering Contradiction:

Improveresource capacityVSAvoidnumber of servers

Core Design Contradiction:

Adaptability or versatilityVSQuantity of substance

Solution Approach 1:

The system optimizes the parameter of destination server quantity by using packing algorithms that calculate the minimum number of servers required to accommodate all source servers while meeting resource capacity constraints. This dynamically adjusts the server count parameter based on actual resource usage patterns rather than using fixed or excessive server allocations.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system applies different resource capacity allocations to different destination servers based on their specific roles and requirements. Each destination server is optimized with locally appropriate resource capacities rather than uniform allocations, allowing efficient packing of source servers while minimizing the total number of destination servers needed.

Inventive Principle:

Principle #3Local quality

3Quantity of substance

If resource allocation is optimized to minimize destination servers, then operational management costs are reduced, but the complexity of allocation calculations increases

Engineering Contradiction:

Improvenumber of serversVSAvoidallocation calculation complexity

Core Design Contradiction:

Quantity of substanceVSDevice complexity

Solution Approach 1:

The system replaces complex manual allocation calculations with automated computational algorithms executed by a processor. The packing algorithm automatically performs the complex mathematical optimization to minimize destination server count, substituting mechanical human calculation efforts with electronic computation that handles the complexity without increasing operational burden.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Loss of energy

If virtualization technology is used for server consolidation, then space and power consumption are reduced, but migration planning complexity increases

Engineering Contradiction:

Improvepower consumptionVSAvoidmigration planning complexity

Core Design Contradiction:

Loss of energyVSDevice complexity

Solution Approach 1:

The migration planning system performs self-service automation by automatically reading virtual server resource usage data, executing packing algorithms to determine optimal destination server allocations, and generating migration plans. This automated approach handles the increased complexity of virtualization-based migration planning without requiring additional manual intervention, thereby maintaining energy efficiency benefits while managing planning complexity.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS7743148B2Server migration planning system and server migration planning method

Publication Date: 2010.06.22 NEC CORP

AI summary

A server migration planning system for planning server migration from source servers to destination servers is provided. A processor allocates the respective source servers to any ones of the destination servers, based on the resource usage of the respective source servers and resource capacity of the respective destination servers. The processor selects the source servers one-by-one in descending order of the resource usage, selects any one of the destination servers, and makes a comparison between a comparison-object usage as the resource usage of the selected source server and a remaining amount of the resource capacity of the selected destination server. If the comparison-object usage is more than the remaining amount, the processor selects another destination server and then makes the comparison again. If the comparison-object usage is not more than the remaining amount, the processor allocates the selected source server to the selected destination server.