Dynamic Disaster Recovery for Computer Information Systems
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Solution Overview
Problem
Current computer information systems lack robustness, leading to system overload and unavailability when a certain number of faulty service nodes exceed the load-bearing capacity of operational nodes, resulting in disrupted service provision.
Innovation Solution
A dynamic disaster recovery method is implemented, where service clusters are classified by service category, and a disaster recovery node sets and adjusts dynamic policies to redistribute service requests among peer service nodes, ensuring continuous service delivery even if one cluster becomes overloaded or faulty.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If service requests are allocated to service nodes in a service cluster, then service processing capability is improved, but when faulty nodes exceed load-bearing capacity, system robustness deteriorates and the entire system becomes unavailable
Solution Approach 1:
The patent segments the service cluster into multiple independent service nodes, each capable of handling specific service requests. This segmentation allows the system to isolate failures to individual nodes rather than allowing a single point of failure to bring down the entire system, thereby maintaining robustness while preserving processing capability.
Solution Approach 2:
The patent implements dynamic service request allocation where the load balancing system can adaptively redirect traffic away from faulty nodes in real-time. This dynamic adjustment enables the system to respond to changing conditions and node failures, maintaining service availability and robustness even when some nodes become unavailable.
2Manufacturing precision
If multiple service clusters are established with fixed service categories, then service specialization is improved, but adaptability to handle cross-cluster service requests deteriorates
Solution Approach 1:
The patent makes service nodes universal by enabling them to process multiple types of service requests beyond their primary specialization. Service nodes can handle both their designated service category requests and cross-cluster requests from other categories, providing multi-functionality that enhances system adaptability while preserving specialized processing capabilities.
Solution Approach 2:
The patent introduces a load balancing system as an intermediary that manages and coordinates service requests across different service clusters. This mediator redirects cross-cluster requests to appropriate nodes, enabling specialized service clusters to handle diverse service types without losing their category-specific optimization.
3Adaptability or versatility
If service nodes are configured with all service processing logics, then service versatility is improved, but system complexity increases
Solution Approach 1:
The patent applies partial action by configuring service nodes with all service processing logics but enabling them to execute only the specific service category they are assigned to handle. This approach provides the versatility of having complete service logic available while avoiding the complexity of actively managing and coordinating multiple specialized nodes for each service type.
Data Source
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AI summary
The method is performed as a client device and includes receiving a first message that includes a first data usage value. The first message is formatted according to a respective format. After receiving the first message, the method further includes acquiring a data usage template corresponding to the respective format. The method further includes receiving a second message that includes a second data usage value. The second message is formatted according to the respective format. The method further includes parsing the second message according to the data usage template so as to obtain a second data usage value.