Persistent Remote Connection for Local Data Cloud Access
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Solution Overview
Problem
Current technologies face challenges in securely, stably, and efficiently accessing local data from devices in a real-time, on-demand manner for cloud-based applications, due to integration issues and the need for cumbersome connection methods like long polling, especially when dealing with accounting software.
Innovation Solution
Establishing a persistent remote connection, such as a WebSocket, between a client device and a network-accessible server, allowing the server to request and authenticate data from the client and send it to external devices as if it were cloud-hosted, using services like connection, token, and socket services for secure and efficient data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If local data is kept on a local machine for security and privacy reasons, then data security is improved, but data accessibility to cloud-based applications deteriorates
Solution Approach 1:
A server acts as an intermediary between the local machine and cloud-based applications. The server receives requests from external devices, forwards them to the local machine, and returns responses to the external devices. This mediator approach allows cloud applications to access local data without directly connecting to the local machine, thereby maintaining security while enabling accessibility.
2Ease of operation
If long polling or parallel data sets are used to access local data, then data accessibility is improved, but system complexity and resource consumption deteriorate
Solution Approach 1:
The server serves as a centralized intermediary that manages all data access requests. Instead of implementing complex long polling mechanisms or maintaining parallel data sets at multiple locations, the server consolidates data access through a single point of control, significantly reducing system complexity and resource consumption.
3Ease of operation
If long polling is used to communicate with clients hosting local data, then data accessibility is improved, but resource efficiency and performance deteriorate
Solution Approach 1:
Instead of continuous long polling that constantly checks for data changes, the system uses event-driven periodic action where the server is notified only when data changes occur. This approach maintains data accessibility while dramatically improving resource efficiency by eliminating unnecessary repeated requests.
Solution Approach 2:
The local machine provides feedback to the server when data changes occur. This feedback mechanism allows the server to efficiently determine when to request updated data, avoiding continuous polling and improving overall resource efficiency while maintaining real-time data accessibility.
Data Source
AI summary
Local data can be made available in a cloud computing environment. A persistent remote connection may be established between a processor and a server. The server may receive a request for data from an external device through a network. The request for data may be sent through the persistent remote connection from the server to a first executable process of the processor. The processor may obtain the data from an application being executed by the processor separately from the first executable process. The data may be sent through the persistent remote connection from the processor to the server. The server may send the data to the external device through the network in response to the request. The persistent remote connection may be maintained in an open state regardless of a status of the request for data.