Parallel Processing in Holonic Systems

Scheduling is a basic activity in large scale systems with unexpected and high complexity demands. Instances of these complex systems are found in manufacturing, logistics, economics, traffic control, and biology. The number of entities and their interconnections are the reasons motivate researchers to find solutions which are not based on central control structures. Multi-agent based architecture is a distributed collections of interacting entities which function without a supervisor. The advantage of holonic self-organization concepts lies in the fact that they contribute to achieve more efficient performance. According to these principles, several approaches have been and are being designed, which are considered weak in handling emergency demands in an industrial environment. The concepts of multi-agent and holonic systems are addressed and discussed in this chapter where their advantages and weak points are revealed with a focused in holonic control architecture in overcome the weak points. The main objective of this architecture is to reduce time and complexity overload. The concept of parallel processing and task priority are of concern here. Task priority reduces time delay in an unexpected situation causes for handling critical tasks. The techniques like self-organization methods, high percentage of autonomy for controller holons, use of common data source, and increasing parallel processes are applied in reducing output delivery time. This newly proposed architecture is tested in a simulation environment.

Keywords: Holonic systems, Multi-agent systems, Parallel processing, Scheduling, Self-organization, Task priority.