Market-Based Sensor Network Resource Allocation
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Solution Overview
Problem
Complex and highly dynamic sensor-based networks face challenges in optimizing resource allocation due to competing objectives and inefficiencies in traditional control systems, especially when systems are nonlinear and unstable, leading to suboptimal resource allocation and potential errors.
Innovation Solution
A market-based algorithm that uses resource allocation techniques derived from financial market models, where resources are depicted as buyers and sellers, with the introduction of an efficiency-arbitrage agent to identify and correct inefficient transactions, ensuring optimal allocation by shifting from a seller-driven to a buyer-driven market.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional feedback control systems (PID control) are used, then control simplicity is maintained, but the system cannot handle nonlinear, time-varying, and unstable sensor network parameters
Solution Approach 1:
The patent replaces traditional mechanical feedback control mechanisms with a market-based algorithmic system. Resources are allocated through virtual auctions and bidding processes rather than conventional PID controllers, enabling the system to handle nonlinear dynamics through economic mechanisms rather than mathematical control equations.
Solution Approach 2:
The system dynamically changes allocation parameters based on real-time sensor data and market conditions. Virtual prices and bid values are continuously adjusted according to changing network conditions, allowing the system to adapt to nonstationary environments without requiring explicit dynamic models.
2Quantity of substance
If the number of sensor inputs and resources increases, then network coverage and capability improve, but the complexity of the optimization process increases dramatically
Solution Approach 1:
The patent segments the optimization problem into individual resource auction processes. Each resource or sensor can be independently evaluated and allocated through separate virtual auctions, avoiding the need to optimize the entire network simultaneously. This modular approach reduces overall complexity while scaling with network size.
Solution Approach 2:
The system introduces virtual market intermediaries that facilitate resource allocation. These virtual auctions act as mediators between sensor inputs and control actions, translating complex multi-objective optimization into simpler price-based exchange mechanisms that are easier to compute and manage.
3Power
If simple on-off feedback control is used, then computational requirements are low, but the system produces large errors and inefficient resource allocations in dynamic environments
Solution Approach 1:
The system implements continuous feedback through virtual pricing mechanisms. Resource values and bid prices are continuously updated based on sensor feedback and market conditions, creating a self-correcting allocation system that adapts to changing conditions without requiring complex computational control algorithms.
Solution Approach 2:
The market-based system enables resources to self-allocate based on their intrinsic values and bid prices. Rather than requiring centralized control to optimize allocation, the system allows resources to automatically adjust their allocation status through economic mechanisms, reducing computational burden while improving allocation efficiency.
Data Source
AI summary
An algorithm for modeling and optimizing control of a complex and dynamic system is provided to facilitate an allocation of the resources on the network that is the most efficient. The algorithm serves to depict the complex network of available resources using market-based negotiation wherein resources are defined as available buyers and sellers in an efficient market. Selling agents are offering their available resources for sale in accordance with parameters that correspond to the actual limitations of that actual resource and the buyers are looking to make a purchase from one of the sellers that presents a resource with the greatest utility to them. In order to overcome inefficiencies that result from the potential of inefficient allocation, the present invention has further endeavored to introduce an efficiency-arbitrage agent that scans the overall body of transactions to identify and remedy inefficient market transactions.