scholarly journals Teknik Penjadwalan Prosesor FIFO, SJF Non Preempetive, Round Robin

2019 ◽  
Vol 1 ◽  
pp. 864
Author(s):  
Ikhsan Parinduri ◽  
Siti Nurhabibah Hutagalung
Keyword(s):  
Waiting Time ◽  
Arrival Time ◽  
Round Robin ◽  
Main Menu ◽  
Start Time ◽  
Processor Scheduling ◽  
Time Value ◽  
Calculation Process ◽  
Burst Time ◽  
Made In

Processor scheduling is divided into several methods including FIFO, Non Preempetive SJF, Round Robin. Implementation can know the performance of the processor which consists of process, waiting time, arrival time and completion stage. In this case the processor scheduling is made in NetBeans IDE.7.0.1 programming with input on the main menu and calculation process display menu with AWT (Average Waiting Time) value with units of ms, table display process: process, burst time and gaint chart : process, waiting time, start time and end time.

scholarly journals Comparison Analysis of CPU Scheduling FCFS, SJF and Round Robin

2017 ◽  
Author(s):  
Andysah Putera Utama Siahaan
Keyword(s):  
Task Scheduling ◽  
Waiting Time ◽  
Scheduling Algorithm ◽  
Round Robin ◽  
The Other ◽  
Comparison Analysis ◽  
Cpu Scheduling ◽  
Multiple Processes ◽  
Burst Time ◽  
Better Than

Task scheduling is needed to maintain every process that comes with a processor in parallel processing. In several conditions, not every algorithm works better on the significant problem. Sometimes FCFS algorithm is better than the other in short burst time while Round Robin is better for multiple processes in every single time. However, it cannot be predicted what process will come after. Average Waiting Time is a standard measure for giving credit to the scheduling algorithm. Several techniques have been applied to maintain the process to make the CPU performance in normal. The objective of this paper is to compare three algorithms, FCFS, SJF, and Round Robin. The target is to know which algorithm is more suitable for the certain process.

scholarly journals Optimal Round Robin CPU Scheduling Algorithm Using Manhattan Distance

2017 ◽  
Vol 7 (6) ◽  
pp. 3664 ◽  
Author(s):  
N. Srilatha ◽  
M. Sravani ◽  
Y. Divya
Keyword(s):  
Waiting Time ◽  
Scheduling Algorithm ◽  
Round Robin ◽  
Manhattan Distance ◽  
Cpu Scheduling ◽  
Cpu Time ◽  
Interactive Environment ◽  
Time Quantum ◽  
Burst Time ◽  
Better Than

In Round Robin Scheduling the time quantum is fixed and then processes are scheduled such that no process get CPU time more than one time quantum in one go. The performance of Round robin CPU scheduling algorithm is entirely dependent on the time quantum selected. If time quantum is too large, the response time of the processes is too much which may not be tolerated in interactive environment. If time quantum is too small, it causes unnecessarily frequent context switch leading to more overheads resulting in less throughput. In this paper a method using Manhattan distance has been proposed that decides a quantum value. The computation of the time quantum value is done by the distance or difference between the highest burst time and lowest burst time. The experimental analysis also shows that this algorithm performs better than RR algorithm and by reducing number of context switches, reducing average waiting time and also the average turna round time.

scholarly journals Round Robin Scheduling Algorithm based on Dynamic time quantum

2019 ◽  
Vol 8 (6) ◽  
pp. 593-595
Keyword(s):  
Operating System ◽  
Waiting Time ◽  
Optimal Algorithm ◽  
Scheduling Algorithm ◽  
Round Robin ◽  
Cpu Scheduling ◽  
Time Quantum ◽  
Turn Around Time ◽  
Dynamic Time ◽  
Burst Time

After studying various CPU scheduling algorithms in Operating System, Round Robin scheduling algorithm is found to be most optimal algorithm in timeshared systems because of the static time quantum that is designated for every process. The efficacy of Round Robin algorithm entirely depends on the static time quantum that is being selected. After studying and analyzing Round Robin algorithm, I have proposed a new modified Round Robin algorithm that is based on shortest remaining burst time which has resulted in dynamic time quantum in place of static time quantum. This improves the performance of existing algorithm by reducing average waiting time and turn-around time and minimizing the number of context switches.

Quantifying Optical Tip-Timing Probe Error With Laboratory Apparatus

2011 ◽  
Author(s):  
Bruce D. Hockaday
Keyword(s):  
Arrival Time ◽  
Optical Signal ◽  
Data Conversion ◽  
Time Of Arrival ◽  
Optical Probes ◽  
Engine Operation ◽  
Timing Resolution ◽  
Blade Tip ◽  
Dynamic Errors ◽  
Made In

Detection of airfoil time of arrival with optical probes has been evolving since the 1980s. Time of arrival data are used to infer airfoil stresses caused by vibration through a sequence of manipulations. The data conversion begins by converting arrival time to blade position, so blade deflection can be determined from the expected non-vibrating position. Various methods are used in the industry to convert deflection data to frequency, amplitude, and stress, which is beyond the scope of this paper. Regardless of the analytical approach used, producing accurate stress information relies on the precise detection and measurement of time of arrival, which equates to blade position. Recent improvements have been made in time of arrival system accuracy by running faster clocks to increase temporal resolution of the measurement. Greater timing resolution, afforded by clock speed, will have diminishing returns when probe and blade-tip interactions begin producing dominant errors. In the case of optical probes, the blade-tip needs to be treated as a curved reflector in the optical system that is capable of introducing dynamic errors. In engine operation the blade-tip moves axially under the probe from untwist, static deflection, and vibration, causing the light to reflect from different parts of the blade-tip. This relative movement between the probe and blade-tip cause the arrival time to change dynamically. Neglecting the dynamic arrival errors caused by the blade-tip’s optical properties will result in blade deflection-errors that propagate into the stress information. This paper presents a laboratory study that quantifies time of arrival errors due to optical interaction with tip radii. The study reports measured arrival position error as a function of location and optical signal power levels. The work is presented in terms of arrival position, producing information that is independent of rotational speed, and vibratory mode.

scholarly journals Super Smart Optimized Round Robin

2016 ◽  
Vol 2 (2) ◽  
pp. 19-21
Author(s):  
Achmad Teguh Wibowo
Keyword(s):  
Waiting Time ◽  
Turnaround Time ◽  
Round Robin ◽  
Priority Scheduling ◽  
Average Waiting Time ◽  
First Come First Serve ◽  
Time Average ◽  
Average Turnaround Time

Aspek penting dalam sistem operasi adalah multiprogramming. Multiprogramming adalah proses atau metode yang digunakan untuk mengekssekusi beberapa proses secara bersamaan dalam memori. Tujuan utamanya adalah untuk meminimalkan Average Waiting Time, Average Turnaround Time, dan memaksimalkan penggunaan CPU. Ada berbagai algoritma yang digunakan dalam multiprogramming seperti First Come First Serve (FCFS), Shortest Job First (SJF), Priority Scheduling (PS) dan Round Robin(RR). Diantara semua itu yang paling sering digunakan adalah Round Robin. Round Robin merupakan algoritma penjadwalan yang optimal dengn sistem timeshared. Dalam RR, waktu kuantum bersifat statis dan algoritma ini bergantung pada besarnya kuantum yang dipilih/digunakan. Kuantum inilah yang berpengaruh pada Average Waiting Time dan Average Turnaround Time nantinya. Tujuan dari makalah ini adalah mengusulkan algoritma yang lebih baik daripada Round Robin sederhana dan Smart Optimized Round Robin sebelumnya.

Efficient Round Robin Algorithm (ERRA) using the Average Burst Time

2019 ◽  
Author(s):  
Masroor Aijaz ◽  
Ramsha Tariq ◽  
Maheen Ghori ◽  
Syeda Wasma Rizvi ◽  
Engr. Farheen Qazi
Keyword(s):  
Round Robin ◽  
Burst Time

scholarly journals Simulasi Penentuan Optimasi Arah Taksi Kosong Dengan Gps Dan Metode Monte Carlo

2010 ◽  
Vol 22 (2) ◽  
pp. 214-228
Author(s):  
Sabungan Halomoan Hutapea ◽  
Rosita Sinaga
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Model ◽  
Waiting Time ◽  
Arrival Time ◽  
Taxi Driver ◽  
Coordinate Position ◽  
Position Data ◽  
The Right ◽  
Monte Carlo Simulation Model

The development of metropolitan cihJ as Jakarta for years is high, thus the demand Jo transportationservices. Tcui is one of mode transportation which is mostly used by middle to high class people. Theproblem is, sometimes many people are wasting time for waiting empty taxi, mean while manyempty taxi, are searching for the passenger.The objective of this simulation model is to direct the taxi, movement to get passenger with the help ofi~b "based software. So then, there is information to direct the taxi, mavement to choose the right Wat}to get passenger with high possibilihJ rate of passenger.The taxi, driver is equipped by GPS that will find out the coordinate position data of geographical. Toinput the data such as position of start-finish and arrival time of passenger it can be done by cellμlarphone then data will be transmit to ~bsite.Using simulation approaching, a Monte Carlo simulation model can be build that will optimize taxi,driver to find passenger. This modeling will be able to estimate the possibilihj of passenger arrival anddistribution of taxi, cars in one area. The comparison of simulation without modeling resuled intincreament of some aspects, such as increment of delivetJ services increase to 81.48%, searching timeand waiting time become 4.12% and 6.45% respectively.Keyword: taxi, movement, waiting time, travel time, Monte-Carlo Simulation

scholarly journals Priority based round robin (PBRR) CPU scheduling algorithm

2019 ◽  
Vol 9 (1) ◽  
pp. 190
Author(s):  
Sonia Zouaoui ◽  
Lotfi Boussaid ◽  
Abdellatif Mtibaa
Keyword(s):  
Operating System ◽  
Real Time ◽  
Waiting Time ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Turnaround Time ◽  
Round Robin ◽  
New Approach ◽  
Real Time Operating System ◽  
Cpu Scheduling

<p>This paper introduce a new approach for scheduling algorithms which aim to improve real time operating system CPU performance. This new approach of CPU Scheduling algorithm is based on the combination of round-robin (RR) and Priority based (PB) scheduling algorithms. This solution maintains the advantage of simple round robin scheduling algorithm, which is reducing starvation and integrates the advantage of priority scheduling. The proposed algorithm implements the concept of time quantum and assigning as well priority index to the processes. Existing round robin CPU scheduling algorithm cannot be dedicated to real time operating system due to their large waiting time, large response time, large turnaround time and less throughput. This new algorithm improves all the drawbacks of round robin CPU scheduling algorithm. In addition, this paper presents analysis comparing proposed algorithm with existing round robin scheduling algorithm focusing on average waiting time and average turnaround time.</p>

scholarly journals Dynamic Task Scheduling based on Burst Time Requirement for Cloud Environment

2021 ◽  
Vol 13 (5) ◽  
pp. 75-87
Author(s):  
Linz Tom ◽  
Bindu V.R.
Keyword(s):  
Task Scheduling ◽  
Optimal Solution ◽  
Round Robin ◽  
Cloud Environment ◽  
New Approach ◽  
Cloud Systems ◽  
Dynamic Task ◽  
Overall Performance ◽  
User Tasks ◽  
Burst Time

Cloud computing has an indispensable role in the modern digital scenario. The fundamental challenge of cloud systems is to accommodate user requirements which keep on varying. This dynamic cloud environment demands the necessity of complex algorithms to resolve the trouble of task allotment. The overall performance of cloud systems is rooted in the efficiency of task scheduling algorithms. The dynamic property of cloud systems makes it challenging to find an optimal solution satisfying all the evaluation metrics. The new approach is formulated on the Round Robin and the Shortest Job First algorithms. The Round Robin method reduces starvation, and the Shortest Job First decreases the average waiting time. In this work, the advantages of both algorithms are incorporated to improve the makespan of user tasks.

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