Abstract
Task management is of a paramount importance because of the daily execution of more or less urgent and important tasks. In this paper, we propose a policy to indicate the necessary tasks and calculate their ranking, using a compromise between the available resources and the quality of service (QoS) granularity in the same task type. We applied a guaranteed technique in order to achieve an intelligent loss of tasks according to the importance of each task. A dynamicity of constraints was then used to attain an increase of availability, performance, reliability and system dependability. The results obtained from the proposed policy reveal that this type of policy can be extremely valuable for companies that wish to focus their efforts and resources to guarantee a satisfactory QoS for their clients.
Highlights
The enterprise environment is constantly subject to more or less significant disturbances which greatly influence the enterprise performance and its quality of service (QoS)
The access delay, in case of a unit overload improved with a dynamic EE-(m,k)-firm constraints, since it depends on tasks criticality that will be dynamically treated by the system
We proposed the EE-(m,k)-firm policy to indicate the necessary tasks and calculate their ranking, using a compromise between the available resources and the QoS granularity in the same task type
Summary
The enterprise environment is constantly subject to more or less significant disturbances which greatly influence the enterprise performance and its quality of service (QoS) These disturbances are specified by completely uncontrollable variables by the enterprise, because they are numerous and have a very different nature. In addition these variables include, the immediate competition from its main competitors within the enterprises. Enterprise modeling remains always a challenge, despite the significant advances in modeling technology. Such a modeling must cover all aspects of the system studied: functional, physical, informational and organizational. It is necessary to make the favorable choice of model of data and processes and to develop an integration platform to exploit the partial models
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