Data Sync Policies for Multi-Device Resource Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data synchronization techniques do not consider the attributes of the sync environment or the types of data being synced, leading to inefficient and resource-intensive data synchronization operations across multiple devices.
Innovation Solution
Implementing data synchronization policies that specify parameters for sync operations, such as frequency and data types, based on the number of participating devices, device attributes, and network conditions, to optimize data synchronization in a sync environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data synchronization is performed frequently across multiple devices, then data consistency is improved, but resource consumption and operational costs increase
Solution Approach 1:
The patent implements dynamic synchronization policies that automatically adjust sync frequency and data selection based on real-time device attributes (storage capacity, processing power, battery level) and environmental conditions (network quality, time of day). This dynamic adaptation maintains data consistency across devices while optimizing resource consumption by performing fewer sync operations on resource-constrained devices.
Solution Approach 2:
The system applies different synchronization strategies to different devices based on their specific attributes. Each device receives a customized sync policy tailored to its capabilities and context, rather than applying a uniform sync frequency to all devices. This allows the system to maintain data consistency while minimizing resource consumption on each individual device.
2Adaptability or versatility
If data synchronization is performed across all device types, then data availability is improved, but system complexity increases
Solution Approach 1:
The patent changes key parameters of the synchronization process based on device attributes and data types. Sync frequency, data selection criteria, and priority levels are adjusted as parameters according to device characteristics (mobile vs. desktop, storage capacity, battery status) and network conditions. This parameter-based approach enables broad device compatibility while maintaining manageable system complexity through rule-based differentiation.
Solution Approach 2:
The system segments the synchronization process into distinct components: device attribute assessment, data type classification, policy generation, and execution. By dividing the complex task of multi-device synchronization into these manageable segments, the system can handle diverse device types effectively while keeping overall system complexity controllable through modular processing.
3Loss of time
If synchronization frequency is increased for all data types, then data freshness is improved, but network bandwidth consumption increases
Solution Approach 1:
The patent applies partial synchronization actions by selectively syncing only the most critical or frequently accessed data types at high frequency, while less critical data types are synced at lower frequencies. This partial action approach ensures data freshness for important information while significantly reducing overall network bandwidth consumption compared to syncing all data types at maximum frequency.
Solution Approach 2:
The system implements periodic synchronization with varying frequencies based on data type priority and device attributes. Critical data types are synced more frequently, while less critical data types are synced periodically at lower frequencies. This periodic approach with differentiated intervals maintains data freshness where needed while optimizing network bandwidth utilization across the system.
Data Source
AI summary
Techniques for data synchronization policies are described. In one or more implementations, techniques may be employed to set data synchronization (“sync”) policies for devices in a data sync environment. The sync policies specify parameters for sync operations in the sync environment, such as how frequently data sync operations are performed, what types of data are synced to particular devices, how frequently particular types of data are synced, and so on. In implementations, the sync policies consider the number of devices that are participating in a sync environment and attributes of the devices in specifying parameters for sync operations. Data can be synchronized among devices in the sync environment based on the sync policies.