EP1331564A1

Fuzzy logic based intelligent load control for distributed environment

Abstract

A load control system for a Multi-Application/Process Multi-media&Telecommunication System is disclosed. A typical Internet Services Server does not provide any support to limit the rate of connections per second and/or the rate of requests per second to dynamically adapt to server load and/or satisfy a policy constraint on service guarantees. As a result, it is likely for an Internet Services Server to become saturated (overloaded) when servicing content to clients. In an overloaded condition, a typical server suffers severe performance degradation, with the overall throughput falling significantly and client connectivity and perceived performance (such as the delay in completing the request) becoming unpredictable. The invention solves these problems by a mechanism which is based on the use of a fuzzy logic expert system. The fuzzy logic expert system computes in a first step (NOM, Normal Operation Mode) an overload level (load monitoring and overload detection) for the system according to the monitored resources (like CPU, memory, Ios, queues...) and to a predefined fuzzy logic rule-based scenario. If a defined overload level is reached, then the FLEXSYS (Fuzzy Logic EXpert SYStem) computes in a second step (OOM, Overload Operation Mode) which overload handling actions (overload handling) have to be taken (according to a second FLEXSYS scenario).

EP1331564A1, drawing sheet 1
Sheet 1 of 120

Term

Term ended

Projected expiry passed 24 January 2022, 4.7 years ago.

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6 claims: 1 independent, 5 dependent

  1. 1
    A method for controlling overload of a data processing system, comprising:a) monitoring a load of said data processing system, whereby parameters for a degree of utilisation of resources of said data processing system are determined, and b) running an overload operation mode (OOM) of said data processing system, including the steps of 1) feeding said parameters into a fuzzy logic expert system, which comprises a fuzzy rule base having rules and associated fuzzy logic variables, 2) identifying important rules among said rule base in accordance with said parameters via said fuzzy logic expert system, and 3) calculating values for the fuzzy logic variables, which are associated with the important rules, and 4) handling the overload based on the identified rules and the calculated values of said associated fuzzy logic variables.
  2. 5
    The method according to one of the claims 1 to 3, wherein the monitoring of the load of said data processing system is performed according to a clock rate, which is higher in the overload operation mode than in the normal operation mode.
  3. 6
    The method according to one of the claims 1 to 5, wherein the degree of utilisation of at least one of the following resources is monitored:CPU load, memory utilisation, I/O load.