5G Data Replication for Risk-Based Device Protection
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Solution Overview
Problem
Current data protection systems fail to actively detect risks to computing devices, leading to potential data loss, and they initiate backup processes only at predefined intervals or after hardware damage, resulting in data gaps.
Innovation Solution
A system that collects data from computing devices, detects risks using a 5G network by assessing surroundings, location, and conditions, and initiates data replication when risks reach a predetermined threshold, storing the replicated data in a cloud storage system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data backup is initiated only at predefined intervals or after hardware damage, then system complexity is reduced and energy consumption is lowered, but data loss risk increases and data availability decreases
Solution Approach 1:
The system performs preliminary risk assessment by continuously monitoring device conditions (location, surroundings, sensor data) before actual data loss events occur. When risk thresholds are exceeded, the system proactively initiates data replication to cloud storage, preventing data loss before it happens rather than reacting after hardware damage or at fixed intervals.
Solution Approach 2:
The system implements a feedback mechanism where device sensors continuously provide data about device conditions and location. This feedback loop enables the system to dynamically adjust backup timing based on real-time risk assessment, triggering data replication only when necessary conditions are met, thus balancing reliability improvement with system complexity management.
2Reliability
If continuous risk monitoring and real-time data replication is implemented, then data loss risk is reduced and data availability is improved, but energy consumption increases and system complexity increases
Solution Approach 1:
The system applies partial monitoring action by selectively triggering full data replication only when risk thresholds are exceeded. Instead of continuously replicating data regardless of conditions, the system monitors continuously but acts partially - initiating replication only when sensor data indicates elevated risk, thus reducing energy consumption while maintaining data protection.
Solution Approach 2:
The system performs preliminary risk assessment using sensor data before initiating energy-intensive data replication. By evaluating device conditions, location, and surroundings first, the system determines whether replication is necessary, avoiding unnecessary energy consumption while ensuring data protection when risks are present.
3Reliability
If data replication is initiated based on risk threshold detection, then data loss prevention is improved, but response time variability increases
Solution Approach 1:
The system transitions from static, fixed-interval backup scheduling to dynamic, condition-based backup timing. The backup timing adapts dynamically based on real-time risk assessment from sensor data, allowing the system to respond appropriately to changing conditions while maintaining data protection reliability.
4Speed
If 5G network is used for real-time data replication, then data transmission speed is improved and data availability is enhanced, but network dependency increases and system complexity increases
Solution Approach 1:
The system integrates 5G network capability as a universal communication interface for data replication, leveraging its high-speed transmission capabilities. The network interface serves multiple functions including risk data transmission, device identification, and cloud storage communication, reducing overall system complexity despite the advanced network technology employed.
Data Source
AI summary
Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises collecting data capable of being replicated from a computing device; detecting risks of the computing device, wherein detecting risks comprises detecting the computing device's surroundings, location, speed, and condition; initiating data replication on the computing device once the risks are determined to reach a predetermined threshold; and storing the replicated data within a cloud storage system using a 5G network.