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Effect of Data Model Approach in State Probability Analysis of Multi-Level Queue Scheduling
In the uniprocessor environment, the number of jobs arriving at the processor of CPU at a time is very large which causes a long waiting queue. When conflict arises due to shared resources or overlap of instructions or logical error, the deadlock state appears where further processing of jobs is blocked completely. While the scheduler jumps from one job to another in order to perform the processing the transition mechanism appears. This paper presents a general structure of transition scenario for the functioning of CPU scheduler in the presence of deadlock condition in setup of multilevel queue scheduling. A data model based Markov chain model is proposed to study the transition phenomenon and a general class of scheduling scheme is designed. Some specific and well known schemes are treated as its particular cases and are compared under the setup of model through a proposed deadlock-waiting index measure. Simulation study is performed to evaluate the comparative merits of specific schemes belonging to the class designed with the help of varying values of α and d.
Keywords
Process Scheduling, Markov Chain Model, Data Model, State of System, Rest State, Deadlock State, Process Queue, Multi-Level Queue Scheduling, Transition Probability Matrix, Deadlock Index.
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