Both goals can be achieved by a balanced load of the incoming transactions requiring for data manipulation over the processing units available. The well-known problem is that no algorithm exists that yields optimal performance for the entire bandwidth of the input. Two other problems are that such a complex real-world application cannot be modeled completely by means of analytical methods, and that the information available at runtime is rather imprecise. In this paper, we suggest a fuzzy switching device, which integrates different, simple load balancing algorithms and selects a particular algorithm depending on the actual system state expressed in fuzzy terms. The simple load balancing algorithms are selected on the basis of a cost function model.
Fuzzy control is more than just an alternative to classical control theory.
While it is easy to design a fuzzy controller with only a few input variables, the designer encounters difficulties when the number of input variables of the controller increases, since the size of the rule set can grow exponentially. Even though classical control theory has been applied very successfully, its major drawback is that it requires a lot of mathematical insights. But classical control theory has developed the notion of the state controller, which grows only linearly in the number of input variables. Also, the concept of the state controller allows for an easy design process. This paper shows how the notion of the state controller can be transferred to fuzzy control without using any of the typical mathematical issues, such as differential equations or Laplace transformation.