Sensor network optimization algorithm
Inventors
Farnham, Christopher • Schrage, Daniel
Assignees
Publication Number
US-10032175-B2
Publication Date
2018-07-24
Expiration Date
2029-04-09
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Abstract
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.
Core Innovation
The invention provides an improved algorithm for modeling and optimizing control of a complex and dynamic system, aimed specifically at optimizing resource allocation throughout such a system. It utilizes a market-based negotiation approach, where system resources are depicted as buyers and sellers within an efficient market. Seller agents offer their resources in accordance with limitations specific to the actual resource, while buyer agents seek resources presenting the greatest utility for their needs.
A unique aspect of the invention is the introduction of an efficiency-arbitrage agent, which continuously scans all transactions made by buyer and seller agents to identify and address inefficient market transactions. Whenever the arbitrage agent finds resources matched to high-value tasks where greater overall efficiency can be achieved, it intervenes by buying out resources from less efficient matches and reallocating them to buyers with higher efficiency needs. This ensures that the allocation of resources across the network is globally optimized and not limited by local or regional inefficiencies.
The problem addressed stems from traditional optimization and control techniques, such as feedback control or PID systems, which struggle when system parameters are highly dynamic, nonlinear, or unstable. As the scale and complexity of sensor-based networks increase, so does the challenge of efficiently allocating resources. The invention solves this by providing a method and system that facilitates global efficiency in resource allocation, employing market-based models adapted with an arbitrage agent for application in highly dynamic sensor networks.
Claims Coverage
There are two independent claims in the patent, each defining a system and a method for optimizing allocation of physically operating resources using a communication network, agents, and an arbitrage agent.
System with agent-based market allocation and arbitrage intervention
The system includes: - A communication network connecting physical resources and sensors that detect and transmit task requests. - A computer system that depicts resources as sellers and task requests as buyers, dynamically matching seller resources to buyer task requests based on assigned priority. - An arbitrage agent operating within the computer system which reviews transactions between buyer and seller agents, identifies inefficient matches where allocation is based on high value, and dynamically breaks these matches by buying out the resource and reallocating it to a more efficient task request.
Method for optimizing allocation with dynamic matching and arbitrage agent
The method comprises: - Offering availability of a plurality of physical resources over a communication network using seller agents. - Offering a plurality of task requests generated by sensors over the same network using buyer agents. - Using a computer system to dynamically match sellers and buyers based on priority levels assigned to each task request. - Employing an arbitrage agent to continuously review matches, identify inefficient seller-buyer matches made on the basis of high value, and break those matches by buying the resource out and reallocating it to a buyer with higher efficiency for a more optimal allocation.
The inventive features cover both a system and a method for dynamic optimization of resource allocation via agent-based market modeling and real-time efficiency correction using an arbitrage agent.
Stated Advantages
Provides high efficiency optimization of resources on complex and highly dynamic sensor-based networks.
Enables evaluation of the entire set of possible resource allocations, allowing global determination of the most efficient allocation despite local or regional allocation loops.
Adapts a proven dynamic market model, commonly used in financial systems, for resource allocation in sensor network systems.
With the addition of the efficiency-arbitrage agent, allows for highly efficient control and allocation of resources in complex problem-solving applications.
Documented Applications
Resource allocation in a missile defense system, including allocation of sensor tasks and weapon system resources.
Placement of advertising resources into available spaces on Internet web pages, optimizing for demographic suitability and potential premium value.
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