Modular Computing Network Configuration Determination
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Solution Overview
Problem
Modular electronic devices face challenges in determining optimal network configurations to implement desired functionalities due to varying capacities and resources of candidate network devices, leading to inefficiencies in resource allocation and task performance.
Innovation Solution
A computer-implemented method that identifies desired functionalities and determines network combinations by analyzing capacity data from candidate devices, selecting subsets to form an ad hoc network that efficiently implements the desired functions, and negotiates resource allocation among devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If modular electronic devices combine multiple different modules to achieve desired functionality, then the versatility and adaptability of the system is improved, but the complexity of determining optimal network configurations increases
Solution Approach 1:
The system segments the network configuration determination process into distinct phases: identifying desired functionality, receiving capacity data from candidate devices, and determining optimal network combinations. This segmentation allows complex configuration problems to be broken down into manageable steps, reducing the overall complexity of system management while maintaining high versatility.
Solution Approach 2:
The patent introduces an intermediary system that receives capacity data from candidate network devices and processes this information to determine optimal network combinations. This intermediary layer abstracts the complexity of device compatibility and resource allocation, allowing the main system to focus on high-level functionality without being overwhelmed by detailed configuration parameters.
2Productivity
If the system receives capacity data from multiple candidate network devices to determine optimal configurations, then the productivity and efficiency of resource allocation is improved, but the time required for configuration determination increases
Solution Approach 1:
The system performs preliminary actions by pre-receiving and storing capacity data from candidate network devices before actual configuration is needed. This advance preparation allows the system to quickly determine optimal network combinations without needing to collect all necessary information in real-time, thus improving resource allocation efficiency while minimizing configuration determination time during actual operation.
Solution Approach 2:
The patent employs partial action by receiving capacity data from multiple candidate devices but only processing and selecting from a subset that meets the desired functionality requirements. This approach avoids the time-consuming task of evaluating all possible device combinations exhaustively while still achieving efficient resource allocation by focusing on relevant candidates only.
3Reliability
If the system determines network combinations based on capacity data, then the reliability of task performance is improved, but the measurement and detection of device capacities becomes more complex
Solution Approach 1:
Candidate network devices autonomously provide their own capacity data without requiring external measurement or detection systems. Each device self-describes its capabilities and available resources, eliminating the complex infrastructure needed for external capacity measurement while ensuring reliable task performance through accurate, device-provided information.
Data Source
AI summary
Systems and methods of determining network configurations for a modular computing entity are disclosed. For instance, a desired functionality to be implemented by a modular computing entity can be identified. Capacity data associated with one or more candidate network devices that are available to join a network associated with the modular computing entity is received. A network combination to implement the desired functionality can be determined based at least in part on the received capacity data. The network combination can include at least a subset of the candidate network devices.