Dynamic API Contract Generation for Edge Data Retrieval
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Solution Overview
Problem
In distributed computing environments, edge devices experience connectivity disruptions and data overload due to mobility, leading to latency and network congestion, making it difficult to identify relevant data and perform tasks efficiently.
Innovation Solution
A data management system that dynamically generates API contracts between edge devices and data services to control data retrieval, deploying deployable objects with these contracts to optimize data flow, detect new services, and deactivate out-of-range connections, ensuring efficient data collection and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If edge devices continuously connect to data services, then data availability is improved, but network congestion and latency increase due to mobility disruptions
Solution Approach 1:
The system dynamically adjusts data retrieval operations based on real-time connection status. When connectivity is disrupted, the system suspends data retrieval operations rather than continuously attempting to fetch data, thereby reducing latency and avoiding network congestion while maintaining data availability through resumption upon reconnection
Solution Approach 2:
The system implements periodic connection status monitoring and uses this information to control data retrieval operations. By periodically checking connectivity and adjusting operations accordingly, the system balances data availability with latency reduction, avoiding continuous data fetch attempts during disconnected states
2Loss of information
If edge devices retrieve data from multiple data services, then data completeness is improved, but network bandwidth consumption increases causing congestion
Solution Approach 1:
The system selectively retrieves data from multiple data services based on availability and relevance rather than attempting to retrieve all possible data. By using the available connection to fetch data from the most relevant services first, the system achieves sufficient data completeness while controlling bandwidth consumption and avoiding network congestion
3Reliability
If edge devices maintain continuous data retrieval operations, then data freshness is improved, but computational resources are wasted during connectivity disruptions
Solution Approach 1:
The system dynamically adjusts data retrieval operations based on real-time connection status. When connectivity is disrupted, the system suspends data retrieval operations rather than continuously attempting to fetch data, thereby reducing latency and avoiding network congestion while maintaining data availability through resumption upon reconnection
Solution Approach 2:
The system continuously monitors connection status and uses this feedback to control data retrieval operations. Based on the connection status feedback, the system decides whether to execute data retrieval operations or suspend them, thereby avoiding computational resource waste during disconnected states while maintaining data freshness when connected
Data Source
AI summary
Dynamic, client-specific retrieval of data can be performed for edge devices using data services. For example, a system can receive a data request from a client device. The data request can include a type of data and one or more parameters for the type of data. In response to receiving the data request, the system can further detect data services that include the type of data. Additionally, the system can generate application programming interface (API) contracts. Each of the API contracts can define a communication protocol between the client device and each of the data services. The system can also deploy a deployable object, which may include the API contracts, on the client device to cause the client device to receive data satisfying the data request from each of the data services.