Distributed Cloud Backup Using Auxiliary Devices for Faster Uploads
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Solution Overview
Problem
Cloud backup methods for mobile electronic devices are inefficient due to the large volume of data being backed up, leading to frame freezing, high power consumption, and network congestion, resulting in prolonged backup times.
Innovation Solution
The method involves dividing the data to be backed up into multiple data sets and distributing these sets across the first device and one or more auxiliary devices, which then upload the data sets to a cloud platform simultaneously, utilizing high-speed transmission methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data backup is performed using a single mobile electronic device, then the backup process can be completed, but the backup time is prolonged and backup efficiency is low
Solution Approach 1:
The patent divides the backup task into multiple segments by splitting data into multiple data sets that are distributed across multiple devices (first device and auxiliary devices). Each device independently uploads its allocated data set to the cloud platform, enabling parallel processing and significantly reducing overall backup time.
2Reliability
If large volume data is backed up using a single device, then all data can be uploaded, but network congestion and power consumption increase
Solution Approach 1:
The patent segments the large volume of data into multiple smaller data sets that are distributed across multiple auxiliary devices. This division reduces the data transmission burden on each individual device and the network, thereby reducing power consumption and avoiding network congestion while ensuring complete data backup.
3Loss of energy
If data backup is performed during idle time of the electronic device, then power consumption and traffic consumption are reduced, but backup efficiency remains low
Solution Approach 1:
The patent merges the backup operations of multiple devices (first device and multiple auxiliary devices) into a coordinated parallel backup system. By distributing data sets across multiple devices that can operate simultaneously during their respective idle times, the system achieves both energy efficiency and high backup efficiency through parallel processing.
Data Source
AI summary
The method includes: A first device obtains an auxiliary device of the first device; the first device divides to-be-backed up data into N data sets, where N is a quantity of backup devices, and the backup devices include the first device and the auxiliary device of the first device; the first device sends backup information to the auxiliary device, where the backup information includes a data set allocated to the auxiliary device, and the backup information indicates the auxiliary device to send the received data set to a preset cloud platform; and the first device sends a data set allocated to the first device to the preset cloud platform.


