Dynamic Service Provisioning on Embedded Devices
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Solution Overview
Problem
Existing systems for deploying web services on embedded devices lack dynamic management and on-demand provisioning, especially in networks with changing device configurations, leading to inefficiencies in service discovery and deployment.
Innovation Solution
A service system that continuously monitors a network of devices, populates a service type repository, and uses a discovery module to identify and rank active service instances, with the ability to install missing services on devices, ensuring dynamic adaptation to changes in the network and user queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If services are deployed on embedded devices in a static manner, then deployment simplicity is maintained, but service availability and adaptability to dynamic network changes deteriorate
Solution Approach 1:
The patent implements dynamic service provisioning by continuously monitoring the network for active service instances and automatically installing missing services on embedded devices. The service system transitions from a static deployment model to a dynamic one where services are provisioned in real-time based on user queries and current network state, resolving the contradiction between service availability and system complexity.
Solution Approach 2:
The system enables self-service through automated service discovery and installation. When a user requests a service, the system automatically searches for active instances across the network and installs the service on appropriate devices without manual intervention. This self-provisioning mechanism improves service availability while avoiding the need for complex manual configuration processes.
2Measurement precision
If continuous monitoring of service landscape is implemented, then service discovery accuracy is improved, but system resource consumption increases
Solution Approach 1:
The patent implements periodic monitoring where the service system continuously scans the network for active service instances at scheduled intervals. This periodic action maintains accurate service discovery information while allowing the system to enter low-activity states between scans, thereby balancing measurement precision with resource consumption efficiency.
3Productivity
If on-demand service installation is performed, then service provisioning efficiency is improved, but device storage and processing load increase
Solution Approach 1:
The system performs preliminary actions by maintaining a repository of service descriptions and metadata before actual service installation. When a service is needed, the system can quickly provision it using pre-prepared information. This preliminary preparation improves provisioning efficiency while minimizing the actual storage and processing load on embedded devices at any given time.
Data Source
AI summary
A service type repository is populated with types of services exposed on a network that has a dynamic organization. The services are embedded on one or more devices included in the network and the services providing information about the one or more devices. A query is received that includes a request for a type of service, and the requested type of service is compared to the types of services in the service type repository to select a collection of matching service types that satisfy the request. Active instances of services that have a type included in the collection of matching service types are identified. The active instances are instances of services embedded on one or more devices included in the network. When no active instances are identified, active instances of services that have a type included in the collection of matching service types are discovered.