Image Processing Apparatus Server Load Reduction via Ranked Data Transmission
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Solution Overview
Problem
Conventional image processing apparatus systems experience increased server load due to simultaneous data transfer from multiple devices, which can lead to system downtime.
Innovation Solution
An image processing apparatus that acquires a failure prediction list from a server, detects when internal components reach a warning state, and strategically stops data transmission from other apparatuses with lower rankings to prevent simultaneous data transfer, thereby reducing server load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple image processing apparatuses transmit data simultaneously to the server, then the server receives comprehensive diagnostic information, but the server load increases excessively causing system downtime
Solution Approach 1:
The server performs preliminary failure prediction analysis on received diagnostic data and generates a ranked failure prediction list before the actual data transmission phase. This preliminary action allows the server to identify which apparatuses have the highest failure risk and should transmit data first, thereby preventing simultaneous transmissions that would overload the server. The ranked list is distributed to apparatuses in advance, enabling them to transmit sequentially according to their rank.
Solution Approach 2:
The system dynamically adjusts the data transmission timing of each image processing apparatus based on its rank in the failure prediction list. High-ranking apparatuses (with higher failure risk) are allowed to transmit data first, while lower-ranking apparatuses transmit later or skip transmission if their risk level is low. This dynamic scheduling adapts to the actual failure risk distribution across the network, optimizing server load while maintaining diagnostic effectiveness.
2Productivity
If each image processing apparatus independently decides data transfer timing based on its own failure prediction, then each apparatus optimizes its own data transmission, but simultaneous data transfers occur causing server overload
Solution Approach 1:
The server sends feedback in the form of a ranked failure prediction list to each image processing apparatus based on the diagnostic data it receives. This feedback mechanism allows the server to communicate the overall failure risk assessment and transmission scheduling decisions back to the individual apparatuses. Each apparatus then uses this feedback information to determine its optimal transmission timing, avoiding simultaneous transmissions while still maintaining high data transmission efficiency for critical devices.
Data Source
AI summary
There is provided an image processing apparatus that transmits data relating to an internal component to a server, and the image processing apparatus includes a hardware processor that: acquires from the server a failure prediction list in which a plurality of image processing apparatuses is ranked; detects that the internal component has reached a warning state; specifies a data transmission stop apparatus that is to be caused to stop data transmission to the server from among other image processing apparatuses by referring the failure prediction list in a case where it is detected that the internal component has reached the warning state; transmits a stop command for causing the data transmission to the server to be stopped to the data transmission stop apparatus specified; and transmits, to the server, data relating to the internal component detected as being in the warning state.