Priority Based Dynamic Round Robin (PBDRR) Algorithm with Intelligent Time Slice for Soft Real Time Systems

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http://ijacsa.thesai.org/ Priority Based Dynamic Round Robin (PBDRR) Algorithm with Intelligent Time Slice for Soft Real Time Systems #1 Prof. Rakesh Mohanty #2 Prof. H. S. Behera Department of Computer Science & Engineering Veer Surendra Sai University of Technology, Burla Sambalpur, Orissa, India #1 rakesh.iitmphd@gmail.com #2 hsbehera_india@yahoo.com #3 Khusbu Patwari #4 Monisha Dash #5 M. Lakshmi Prasanna Department of Computer Science & Engineering Veer Surendra Sai University of Technology, Burla Sambalpur, Orissa, India

Abstract—In this paper, a new variant of Round Robin (RR) algorithm is proposed which is suitable for soft real time systems. RR algorithm performs optimally in timeshared systems, but it is not suitable for soft real time systems. Because it gives more number of context switches, larger waiting time and larger response time. We have proposed a novel algorithm, known as Priority Based Dynamic Round Robin Algorithm(PBDRR), which calculates intelligent time slice for individual processes and changes after every round of execution. The proposed scheduling algorithm is developed by taking dynamic time quantum concept into account. Our experimental results show that our proposed
algorithm performs better than algorithm in [8] in terms of reducing the number of context switches, average waiting time and average turnaround time. Keywords- Real time system; Operating System; Scheduling; Round Robin Algorithm; Context switch; Waiting time; Turnaround time. I. INTRODUCTION
Real Time Systems (RTS) are the ones that are designed to provide results within a specific time-frame. It must have well defined fixed and response time constraints and the processing must be done within the defined constraints or the system will fail. RTS are basically divided into three types: hard, firm and soft. In hard real time systems, failure to meet deadline or response time constraints leads to system failure. In firm real time systems, failure to meet deadline can be tolerated. In soft real time systems, failure to meet deadline doesn’t lead to system failure, but only performance is degraded[6]. Space research, weather forecast, seismic detection, audio conferencing, video conferencing, money withdrawal from ATM, railway and flight reservation etc are some of the applications of real time systems. The simple RR algorithm cannot be applied in soft real time systems as it gives longer waiting and response time. Yashuwaanth and et. al. [8] have proposed a scheduling algorithm for soft real time systems where Intelligent Time Slice(ITS) for all the processes has been calculated. The processes are scheduled using RR with ITS as time quantum. By taking dynamic time concept with ITS, we have proposed a new algorithm which gives improved performance than the algorithm proposed in [8]. A. Real Time Scheduling Algorithms Some of the well known real-time scheduling algorithms are described as follows. Rate Monotonic Algorithm(RM) is a fixed priority scheduling algorithm which consists of assigning the highest priority to the highest frequency tasks in the system, and lowest priority to the lowest frequency tasks.
At any time, the scheduler chooses to execute the task with the highest priority. By specifying the period and computational time required by the task, the behavior of the system can be categorized apriori. Earliest-Deadline-First Algorithm (EDF) uses the deadline of a task as its priority. The task with the earliest deadline has the highest priority, while the task with the latest deadline has the lowest priority. Minimum- Laxity-First Algorithm (MLF) assigns a laxity to each task in a system, and then selects the task with the minimum laxity to execute next. Laxity is defined as the difference between deadline by which the task must be completed and the amount of computation remaining to be performed. Maximum- Urgency-First Algorithm (MUF) is a combination of fixed and dynamic priority scheduling. In this algorithm each task is given an urgency which is defined as a combination of two fixed priorities, and a dynamic priority. One of the fixed priorities, called the criticality, has highest priority among the three, and then comes the dynamic priority which has precedence over the user priority (fixed priority). The dynamic priority is inversely proportional to the laxity of a task. B. Related Work In real time systems, the rate monotonic algorithm is the optimal fixed priority scheduling algorithm where as the earliest-deadline-first and minimum-laxity-first algorithms are the optimal dynamic priorities scheduling algorithms as (IJACSA) International Journal of Advanced Computer Science and Applications,
Vol. 2, No.2, February 2011

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