Multi-Agents Systems, Sensor Networks, and Cyber-Physical Systems
Trends recently emerging in engineering and micro-system applications such as the development of sensorial materials show a growing demand for autonomous networks of miniaturized smart sensors and actuators embedded in technical structures. With increasing miniaturization and sensor-actuator density, decentralized network and data processing architectures are preferred or required. A multi-agent system can be used for a decentralized and self-organizing approach of data processing in a distributed system like a sensor network, enabling the mapping of distributed data sets to related information, for example, required for object manipulation with a robot manipulator.
Simplification and reduction of synchronization constraints owing to the autonomy of agents is provided by the distributed programming model of mobile agents. Traditionally, mobile agents are executed on generic computer architectures, which usually cannot easily be reduced to single microchip level like they are required, e.g., in sensorial materials with high sensor node densities.
Distributed Data Processing with State-based Agents
Initially, a sensor network is a collection of independent computing nodes. Interaction between nodes is required to manage and distribute data and computed information. One common interaction model is the mobile agent. An agent is capable of autonomous action in an environment with the goal to meet its delegated objectives. An agent is a data processing system, a program executed on a computer system, that is situated in this environment. A multi-agent system is a collection of loosely coupled autonomous agents migrating through the network. Agents can be used in sensor networks for
- Sensor data processing and extraction
- Sensor data fusion, filtering, and reduction of sensor data to information in a region of interest
- Sensor data and information distribution and transport
- Global energy management, exploration and negotiation
Agents can operate state-based. Such an agent consists of a state, holding data variables and the control state, and a reasoning engine, implementing behaviours and actions. In this proposed data processing and communication architecture, the state of an agent is completely kept in messages transferred in the network providing agent mobility. The functional behaviour of an agent can be easily implemented statically with a finite-state machine part of the local data processing system on register-transfer level (RTL), or dynamically by using a programmable code approach.
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