Composable Edge Device Platforms Using Manifests
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Solution Overview
Problem
Conventional centralized cloud computing systems face challenges in managing workflows at geographically remote devices, particularly in scenarios with hundreds or thousands of IoT devices, disconnected regions, or locations with no Internet connectivity, due to latency issues in wide-area network connections.
Innovation Solution
The composition of cloud-infrastructure edge computing devices using a manifest that specifies the configuration for each device, allowing for the delivery of computing and storage at remote locations separate from the centralized data center, and enabling low-latency processing near the point of data generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If data is processed at centralized cloud locations, then processing power and storage capacity are sufficient, but network latency increases for remote IoT devices
Solution Approach 1:
The centralized cloud computing system is segmented into multiple distributed edge computing nodes deployed at remote locations. Each edge node independently processes data from nearby IoT devices, eliminating the need for all data to traverse wide-area network connections to centralized data centers. This segmentation directly reduces network latency while the modular architecture manages complexity through standardized interfaces and containerization technologies.
Solution Approach 2:
The system transitions from a single-dimensional centralized processing model to a multi-dimensional distributed architecture where computing resources are spread across geographic dimensions. Edge computing nodes are positioned at multiple locations simultaneously, creating a hierarchical structure that combines local edge processing with centralized cloud coordination, thereby reducing latency for remote devices while maintaining overall system management.
2Productivity
If edge computing devices are deployed at remote locations, then processing speed improves for local data, but device configuration and management complexity increases
Solution Approach 1:
Edge computing devices are pre-configured with containerized applications and necessary software components before deployment to remote locations. The manifest files and configuration data are prepared in advance, allowing devices to be rapidly deployed and immediately begin processing local data without requiring complex on-site configuration. This preliminary preparation significantly simplifies the deployment process while maintaining high processing speeds.
Solution Approach 2:
The system uses containerization technology to create standardized, replicable computing environments that can be copied and deployed across multiple edge devices. Configuration templates and application bundles are replicated to each edge node, ensuring consistent behavior across the distributed system while simplifying management. This copying approach allows rapid provisioning of edge devices with identical or customized configurations without manual setup at each location.
3Reliability
If centralized cloud infrastructure is used, then system management is simplified, but response time for time-sensitive data processing deteriorates
Solution Approach 1:
The monolithic centralized management system is segmented into distributed edge nodes that autonomously handle time-sensitive processing decisions locally. Each edge node can independently respond to urgent events without waiting for centralized approval, while still reporting to and receiving updates from the central management system. This segmentation enables immediate local response to time-sensitive events while maintaining centralized coordination for non-urgent management tasks.
Solution Approach 2:
The system implements dynamic decision-making where edge computing nodes can operate autonomously in real-time for time-sensitive operations, then synchronize with centralized management when connectivity is available. The architecture dynamically adjusts between fully connected centralized mode and disconnected autonomous mode, allowing rapid local response when needed while maintaining simplified centralized management during normal operations. This dynamic behavior resolves the contradiction between management simplicity and response speed.
Data Source
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AI summary
Techniques discussed herein relate to providing composable edge devices. In some embodiments, a user request specifying a set of services to be executed at a cloud-computing edge device may be received by a computing device operated by a cloud computing provider. A manifest may be generated in accordance with the user request. The manifest may specify a configuration for the cloud-computing edge device. Another request can be received specifying the same or a different set of services to be executed at another edge device. Another manifest which specifies the configuration for that edge device may be generated and subsequently used to provision the request set of services on that device. In this manner, manifests can be used to compose the platform to be utilized at any given edge device.