Atomic IoT Information Model for Scalable M2M Service Communication
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Solution Overview
Problem
Current M2M and IoT systems face scalability and flexibility issues due to complex resource tree structures that are memory-intensive and cumbersome, particularly in network-to-network and device-to-device communications, limiting the ability to support a large number of devices and applications.
Innovation Solution
A lightweight information model based on atomic information objects, categorized into subjects, actions, and descriptions, which are addressable and flexible, allowing for efficient storage, sharing, and communication between entities, supporting multiple applications and complex deployment scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a complex resource tree structure is used for addressing entities in M2M systems, then service communication and management are enabled, but the system becomes memory-intensive and difficult to scale
Solution Approach 1:
The complex resource tree structure is segmented into atomic information objects (subjects, actions, descriptions) that can be independently addressed and manipulated. This segmentation reduces the memory overhead and complexity of the overall addressing structure while maintaining the ability to represent complex M2M services through combinations of atomic objects.
Solution Approach 2:
A universal set of atomic information object types is defined that can be combined to represent various M2M services and resources. This universal framework eliminates the need for separate complex tree structures for different service types, reducing overall system complexity while maintaining versatility in service communication.
2Adaptability or versatility
If a complex resource tree structure is used for M2M addressing, then entity communication is supported, but processing requirements and bandwidth consumption increase
Solution Approach 1:
Information is segmented into atomic objects (subjects, actions, descriptions) that can be processed and transmitted independently. This segmentation reduces the processing overhead compared to manipulating complex tree structures, as each atomic object can be handled separately with lower computational requirements and reduced bandwidth consumption.
Solution Approach 2:
The addressing paradigm is changed from hierarchical tree paths to flat atomic object references with standardized types. This parameter change in the addressing mechanism significantly reduces processing requirements and bandwidth usage while maintaining the ability to support diverse entity communications through the universal atomic object framework.
3Reliability
If traditional M2M information models are used, then service layer communication is enabled, but flexibility for evolving systems and vertical integration is limited
Solution Approach 1:
A universal set of atomic information object types is defined that can be combined in various ways to represent different services and resources. This universal framework provides the flexibility needed for evolving M2M systems and vertical integration, as new services can be created by combining existing atomic objects without requiring changes to the underlying information model structure.
Solution Approach 2:
The information model transitions from a static hierarchical structure to a dynamic composition of atomic objects that can be freely combined and recombined. This dynamic approach allows the system to adapt to evolving requirements and integrate vertical systems flexibly, as the atomic objects can be arranged in different configurations to support new services and use cases.
Data Source
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AI summary
A lightweight and extensible information model for machine to-machine systems is disclosed. A service layer information management architecture uses three categories of atomic objects, subjects, actions, and descriptions. Information for use within the model is built using the atomic information objects. Application programming interfaces are used to perform operations and information processing by different nodes. Common service functions are used in the model as instances of a generic common service information model.