Edge Data Synchronization Using Distributed Hash Mapping
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Solution Overview
Problem
Existing data synchronization methods in edge environments are hindered by delays due to latency, network congestion, and orchestrator unavailability, which negatively impact the quality and timeliness of computer-implemented services.
Innovation Solution
Implementing a distributed hash map to manage data synchronization between endpoint devices, allowing direct communication through an overlay network, replicating data copies on additional endpoint devices, and selecting data hosts based on latency for timely data retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is synchronized through a central orchestrator in edge environments, then data security and centralized control are improved, but latency and service timeliness worsen due to transmission delays and orchestrator unavailability
Solution Approach 1:
The patent segments the centralized data synchronization architecture into distributed peer-to-peer connections between endpoint devices. Instead of all devices communicating through a single orchestrator, devices directly exchange data copies with each other, creating multiple independent communication paths. This segmentation eliminates the single point of delay (the orchestrator) while maintaining security through encrypted direct connections.
Solution Approach 2:
The patent introduces an overlay network as an intermediary layer that enables direct peer-to-peer communication between endpoint devices without requiring data to traverse the physical network through the orchestrator. The overlay network provides virtual channels that allow devices to establish direct logical connections, reducing transmission latency while the underlying physical network infrastructure remains unchanged.
2Productivity
If data is replicated across multiple endpoint devices for fast access, then service availability and timeliness are improved, but network congestion and data consistency challenges worsen
Solution Approach 1:
The patent implements selective data replication where not all endpoint devices receive copies of all data. Instead, data is replicated to specific devices based on their capabilities, proximity, and relevance to local services. This local quality approach ensures that each device has the data it needs for fast local access without unnecessarily consuming network bandwidth for devices that don't require that data.
Solution Approach 2:
The patent applies partial replication strategies where data is copied to a subset of endpoint devices rather than all devices. This partial action reduces the total volume of data transmitted across the network while still providing sufficient redundancy for service availability. The system determines the optimal number of replicas based on service requirements and network conditions.
3Loss of time
If direct peer-to-peer data sharing is implemented between endpoint devices, then latency is reduced and service timeliness is improved, but system complexity and coordination overhead increase
Solution Approach 1:
The patent implements a universal data structure format that all endpoint devices use for data exchange and synchronization. This universal format includes standardized metadata, versioning information, and validation fields that work across different device types and applications. By establishing a single universal protocol, the system reduces the complexity that would otherwise arise from device-specific synchronization mechanisms.
Solution Approach 2:
The patent incorporates feedback mechanisms where endpoint devices exchange synchronization status information, version data, and conflict resolution outcomes with their peers. This feedback allows devices to automatically detect and resolve data consistency issues without centralized coordination. The feedback loop enables autonomous conflict resolution through version comparison and selective overwriting based on timestamps or device priority.
Data Source
AI summary
Methods and systems for data synchronization between endpoint devices in an edge network are disclosed. The method may include distributing data generated by an endpoint device to any number of additional endpoint devices based on a replication policy, and maintaining a distributed storage system (e.g., a distributed hash table) for data hosted by the endpoint devices. When a data access event for a portion of the data hosted by the endpoint devices occurs, one endpoint device may be selected, based on the distributed hash table and/or latency considerations, from which at least a copy of the portion of the data may be retrieved and used in providing computer-implemented services.