Autonomous MFP Job Allocation via Distributed Storage
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Solution Overview
Problem
Conventional image processing systems require a costly server to select and manage image processing devices, leading to high operational costs and potential delays due to increased network load and job processing inefficiencies.
Innovation Solution
An image processing system where each device autonomously determines whether it can process a job and communicates with a storage unit to compare processing conditions with other devices, eliminating the need for a server by using a common standard to decide on job allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a server is used to select and manage image processing devices, then job allocation and device management can be centralized, but system cost increases and network load increases
Solution Approach 1:
Each image processing device autonomously determines whether it can process a job by comparing its own processing conditions with the job requirements and with other devices' conditions stored in the storage unit. This self-service mechanism eliminates the need for a centralized server to make allocation decisions, reducing system cost and complexity while maintaining reliable job processing management
Solution Approach 2:
The job allocation decision-making function is extracted from the centralized server and distributed to individual image processing devices. Each device obtains processing condition information from the storage unit and independently judges whether to accept a job, removing the dependency on a costly server infrastructure while preserving centralized information management through the storage unit
2Reliability
If a server is used to manage image processing devices, then centralized control is achieved, but network load increases and processing efficiency decreases
Solution Approach 1:
The centralized server's job allocation function is segmented and distributed to individual image processing devices. Each device independently performs judgment processing by comparing its own conditions with stored information from other devices, enabling parallel decision-making that reduces network load and improves overall job processing efficiency while maintaining reliable device management through the shared storage unit
3Reliability
If a server is used for job allocation, then centralized decision-making is possible, but system cost increases
Solution Approach 1:
Image processing devices perform self-service by autonomously determining job acceptance based on their own processing conditions and information obtained from the storage unit. This eliminates the need for a costly centralized server while maintaining reliable job allocation through distributed autonomous decision-making
Solution Approach 2:
The expensive centralized server is replaced with a distributed architecture using existing, less costly image processing devices. Each device uses the storage unit for information sharing and makes independent allocation decisions, achieving reliable job allocation without the high cost of dedicated server hardware
Data Source
AI summary
Each of a plurality of image processing devices (MFPs) included in an image processing system which includes a storage as well. (1) When the user requests processing a job, (2) the job data is stored in the storage. (3) Each MFP confirms that there is an unprocessed job to be executed, and (4) judges whether the own device can process the job. (5) MFPs that have judged that the own device can process the job stores information of the own device into the storage, and (6) check information stored by other MFPs. (7) One of the MFPs judges that the own device is the most suitable MFP, (11) obtains the job data, and (12) processes the job.