Geo-staged Sensor Data Staging via Distributed Edge Storage
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Solution Overview
Problem
Computer networks experience high latency due to delays in data transmission and processing, particularly in distributed architectures like cloud computing, which can hinder real-time data access and analysis for mobile devices.
Innovation Solution
A method and system for staging real-time data in proximity to mobile devices by determining their geographic location and identifying nearby storage devices with lower connection latency, allowing data to be stored and accessed efficiently, thereby reducing communication latency and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in centralized cloud storage, then data accessibility is improved, but network latency increases
Solution Approach 1:
The patent implements edge storage nodes distributed across different geographic locations, allowing data to be stored locally near end-users rather than in a single centralized cloud data center. This enables users to access data from the nearest edge node, reducing network latency while maintaining the accessibility benefits of cloud storage through a distributed architecture.
Solution Approach 2:
The centralized cloud storage system is segmented into multiple distributed edge storage nodes deployed across different geographic regions. Each edge node handles local data storage and access requests, dividing the monolithic cloud storage function into smaller, geographically-distributed units that reduce latency for local users while maintaining overall system accessibility.
2Speed
If data is cached geographically nearby, then access speed is improved, but data freshness deteriorates
Solution Approach 1:
The edge storage nodes implement periodic synchronization with the central cloud data center, where data is updated at scheduled intervals or triggered by specific events. This periodic action ensures that cached data at edge nodes remains relatively fresh while maintaining fast local access speeds, resolving the contradiction between speed and data freshness.
Solution Approach 2:
The system incorporates feedback mechanisms where edge nodes monitor data access patterns and staleness metrics, automatically triggering data synchronization with the central cloud when data becomes outdated. This feedback-driven approach ensures data freshness is maintained dynamically while preserving fast local access for commonly-used data.
3Loss of time
If data is staged at multiple locations, then access latency is reduced, but system complexity increases
Solution Approach 1:
The patent introduces a data staging service as an intermediary layer between the central cloud data center and edge storage nodes. This service automatically manages data replication, synchronization, and consistency across multiple locations, reducing access latency for users while abstracting away the complexity of multi-location data management from the overall system.
Solution Approach 2:
The edge storage nodes and data staging service implement automated self-management capabilities, including automatic data replication, conflict resolution, and synchronization protocols. This self-service approach enables the system to maintain data consistency across multiple locations without requiring complex centralized coordination, reducing both access latency and operational complexity.
Data Source
AI summary
There is disclosed a method of staging real-time data in proximity to a mobile device. The method includes determining a geographic location associated with the mobile, device and identifying a storage device located in proximity to the determined geographic location. The method also includes enabling real-time data published by the mobile device or provided to the mobile device to be stored on the identified storage device.