Abstract
Central
Processing Unit (CPU) scheduling involves a careful examination of pending
processes to determine the most efficient way to service the requests. Several
scheduling algorithms have been designed to arrange accesses to computer
resources efficiently. Round robin scheduling algorithm (RRSA) is an attractive
algorithm but suffers from the problem of time quantum determination. In the
classical round robin algorithm, quantum time is fixed throughout the scheduling
process. This static nature made it very difficult to optimize the algorithm.
The only solution to this problem is to provide a quantum time that changes
dynamically during execution. Major challenges of dynamic round robin
schedulers reported in the literature are: they do not include Average Response
Time as a criterion for comparison and they do not bother much on preempting
processes with negligible completion time after executing for a given time
quantum leading to an increase in the number of context switches. This research
proposed an algorithm, the Modified Median Round Robin (MMRRA), with a dynamic
time quantum aimed at reducing the overhead of the RRSA. The proposed algorithm
was implemented and evaluated against the following five algorithms in the
literature: Improved Round Robin (IRR), Improved Mean Round Robin with Shortest
Job First (IMRRSJF), Dynamic Round Robin with Controlled Preemption (DRRCP),
Half Life Variable Quantum Time RR (HLVQTRR) and CLASSICAL RR. Which in turns,
proved to perform better in terms of AWT, ATAT and NCS. But, in terms of ART,
HLVQTRR has the best result but still the result for MMRRA was not bad.
CHAPTER ONE
INTRODUCTION
1.1 BACKGROUND OF THE
STUDY
Process
scheduling algorithm has been an interesting field of study in Operating
Systems. Scheduling is a key concept in computer multitasking, multiprocessing
and real-time operating system designs. The operating system uses some sort of
scheduling techniques to allocate resources to processes in the ready queue.
Scheduling refers to the way processes are assigned to run on available Central
Processing Unit (CPU). Certain CPU scheduling techniques or algorithms have
been developed. The overall goal of these algorithms is to: maximize CPU
utilization, reduce average waiting time and average turnaround time, reduce
the number of context switching, increase throughput and try as much as
possible to be fair to all processes. Processor Manager is in charge of
allocating a single CPU to execute the jobs of those users.In a single user
system, the processor is busy only when the user is executing a job but, at any
other time it is idle. Processor Management in this environment is simple.
However, when there are many users with many jobs on the system (this is known
as a multiprogramming environment), the processor must be allocated to each job
in a fair and efficient manner, which can be a complex task. The processor,
also known as the CPU (Central Processing Unit), is the part of the machine
that performs the calculations and executes the programs.
Multiprogramming
requires that the processor be allocated to each job or to each process for a
period of time and de-allocated at an appropriate moment. If the processor is
de-allocated during a program‟s execution, it must be done in such a way that
it can be restarted later as easily as possible, this is a delicate procedure.
A single processor can be shared by several jobs or several processes, but if,
and only if, the operating system has a scheduling policy, as well as a
scheduling algorithm, to determine when to stop working on one job and proceed
to another. Some examples of these scheduling algorithms are:
i
First Come First Serve (FCFS): Attends to processes in their order of arrivals.
ii
Shortest Job First (SJF): Attends to processes in an increasing order of their
burst time.
iii
Round Robin (RR): Gives an equal time slice (Quantum) to every process in the
ready queue in a circular manner. If the Quantum time is greater or equal to
the burst time of the process it will run to completion without being
preempted. Otherwise, the process must be preempted after it must have
exhausted its time Quantum and then return to the tail of the ready queue to
take turn.
iv
Priorities scheduling: Here, processes are attended to based on their
priorities.
The
preemptive nature of Round Robin scheduling can only suggest that it is
designed to handle time sharing systems. As bad as context switching may be, it
is highly needed in time sharing systems, although too much context switching
is an overhead. Another issue is what should be the Quantum time? This is even
more serious because smaller Quantum time will increase the number of context
switching, and a larger value will automatically change the system to ordinary
FCFS. Therefore, an optimal Quantum time is what we need. In the Classical RR
the quantum time is static. This is why it is sometimes called Static RR. Here,
the quantum time is gotten from the average of the processes‟ burst time in the
ready queue and remain constant throughout the entire procedure. The static
nature made it difficult for maximum improvement, and as such research on
Dynamic RR is on. The idea of dynamic RR is to use more than one different
quantum time for processes depending on their circumstances. Some of the
proposed dynamic RR are: Improved Mean Round robin with shortest job first
scheduling, Self-Adjustment time quantum in Round Robin algorithm depending on
Burst time of the New Running Processes (SARR), An Improved Round Robin CPU
Scheduling Algorithm (IRR), A new Round Robin Based Scheduling Algorithm for
Operating System, Dynamic Quantum Using the Mean (An Algorithm), Half-life
variable quantum time RR (HLVQTRR), Dynamic Round Robin with Control Preemption
(DRRCP) etc. So far, from the various proposed Dynamic RR, it has been proven
to be more efficient than the Classical RR when compared and evaluated on the
basis of number of context switching, average waiting time and average
turnaround time. The purpose of this research is to develop a new dynamic RR
algorithm base on the ideas gotten from the different scheduling algorithms like
IRR, IMRR, HLVQTRR, DRRCP etc. that will provide answers to some of the
critical setbacks experienced in the classical RR and the various proposed
dynamic RRs. Comparative analysis would be carried out on Six RR algorithms to
enable this research work reach a meaningful conclusion.
1.2 PROBLEM STATEMENT
The
greatest challenge in RR is Quantum time. That is, what should be the Quantum
time? In the classical RR, Quantum time is fixed throughout the scheduling
process. This static nature made it very difficult to optimize the algorithm.
In order to reduce the number of context switching, average waiting time and
average turnaround time, we must find a dynamic Quantum time. This will provide
a Quantum time that change automatically according to a circumstance so as to
improve the general performance of the system. Each of the proposed dynamic RR
performs better when compared with static RR on the basis of number of context
switching, average waiting time and average turnaround time. If that is the
case, which among them should be implemented and why? In order to answer the
above question, the Modified Median RR (MMRRA) was proposed. Another problem is
that, most of these algorithms do not care to include ART as a criteria for
comparison. And, they do not bother much on preempting processes with
negligible left over. Mis-calculation of number of context switching (NCS) is
another problem to most of these algorithms. The MMRRA would be compared
against the classical RR, Improved Round Robin(IRR), Improved Mean Round
Robin(IMRR), Half Life Variable Quantum Time RR(HLVQTRR) and Dynamic Round
Robin with Controlled Preemption (DRRCP) using analytic and simulation
techniques.
Department: Computer Science (M.Sc)
Format: MS Word
Chapters: 1 - 5, Preliminary Pages, Abstract, References
No. of Pages: 139
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M.SC Thesis in Computer Science
DESIGN AND IMPLEMENTATION OF A MODIFIED MEDIAN ROUND ROBIN ALGORITHM (DIMMRRA)
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