Predictive User Data Migration to Edge Nodes for Lower Access Latency
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Solution Overview
Problem
Current remote data access solutions for traveling users experience significant delays, increased network resource usage, and security risks, leading to reduced productivity and higher costs.
Innovation Solution
Integrate predictive scheduling and location systems with data center orchestration to anticipate user movement, pre-loading data onto nearby fog nodes or cloud servers, ensuring seamless and localized access to data and resources during travel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If user data is accessed from remote data centers, then data availability is maintained, but access latency increases significantly
Solution Approach 1:
The system performs preliminary actions by predicting user travel schedules and pre-migrating data to edge locations before the user actually needs access. The orchestration system uses scheduling information to proactively move data from central data centers to edge servers in advance, so that when the user arrives at a remote location, the data is already locally available, eliminating access latency while maintaining data availability.
Solution Approach 2:
The patent introduces edge locations and fog nodes as intermediary computing resources between central data centers and remote users. These intermediaries cache and serve user data locally at edge locations close to where users travel, acting as mediators that provide fast local access while the central data center remains the ultimate source of truth for data availability and consistency.
2Loss of time
If data is migrated to edge locations for faster access, then latency is reduced, but network resource usage increases
Solution Approach 1:
The system applies local quality by selectively migrating only the specific data sets that individual users need based on their predicted schedules and access patterns, rather than broadly replicating entire data centers to edge locations. This targeted approach reduces unnecessary network resource consumption while still providing fast local access for the specific data that matters to each user.
Solution Approach 2:
The orchestration system performs partial migration by moving only a subset of data - specifically the data that is predicted to be accessed by users at edge locations - rather than migrating all data. This partial action approach optimizes network resource usage by avoiding redundant transfers of data that won't be used, while still achieving the latency reduction benefit for the relevant data sets.
3Productivity
If predictive scheduling systems are integrated with data center orchestration, then data access efficiency is improved, but system complexity increases
Solution Approach 1:
The orchestration system is designed with multi-functionality to handle multiple tasks: it performs traditional data center provisioning, monitors user schedules, predicts data access needs, and manages data migration across hybrid cloud-edge environments. By consolidating these diverse functions into a single orchestration platform, the system improves data access efficiency without proportionally increasing complexity, as the same infrastructure serves multiple purposes.
Data Source
AI summary
Systems, methods, and computer-readable media for orchestrating data center resources and user access to data. In some examples, a system can determine, at a first time, that a user will need, at a second time, access to data stored at a first location, from a second location. The system can identify a node which is capable of storing the data and accessible by a device from the second location. The system can also determine a first service parameter associated with a network connection between the device and the first location and a second service parameter associated with a network connection between the device and the node. When the second service parameter has a higher quality than the first service parameter, the system can migrate the data from the first location to the node so the device has access to the data from the second location through the node.