联系方式

  • QQ:99515681
  • 邮箱:99515681@qq.com
  • 工作时间:8:00-21:00
  • 微信:codinghelp

您当前位置:首页 >> C/C++编程C/C++编程

日期:2020-08-23 02:34

COMP SCI 3004/7064 - Operating Systems Assignment 1

Important Notes

• Handins:

– The deadline for submission of your assignment is .

– For undergraduate students, you may do this assignment as a team of two students

and hand in one submission per team.

– For postgraduate students, you have to do this assignment individually and make

individual submissions.

– All implementations have to be done in C++.

– You need to submit your source code using the web submission system. You should

attach you and your partner’s name and student number in your submission.

– Late submissions will attract a penalty: the maximum mark you can obtain will be

reduced by 25% per day (or part thereof) past the due date or any extension you are

granted.

• Marking scheme:

– 20 marks for 10 randomly generated tests (2 marks per test).

If you have any questions, please send them to the student discussion forum. This way you

can all help each other and everyone gets to see the answers.

The assignment

The aim of this assignment is to improve your learning experience in the process scheduling

algorithms. You are required to design an online ticketing system for the Melbourne Cup held

every year in Melbourne Arena. Specifically, there are 10,500 seats for public booking via this

system for a single match. Figure 1 shows the distribution of the seat sections, where all the

yellow and green areas are for public reservations.

In the system, all the customers are grouped into five priority classes (numbers), ranged from

1 to 5, according to their loyalty (accumulated points) to this ticketing system. A smaller priority

number indicates a higher priority. All ticketing processes (purchase/cancellation) generated by

a customer are assigned with the same priority number of that customer. To maximise the

system service performance, you are required to implement a scheduling algorithm using multilevel

queue strategy with two queues: a high priority Queue 1 and a low priority Queue 2, where

Queue 1 has absolute priority over Queue 2. In other words, customers in Queue 2 will only be

processed if there is no customer in Queue 1.

A new customer on arrival will be put on Queue 1 if his/her priority number ≤ 3 or Queue

2 otherwise.

Detailed actions in these queues are described below:

1

Figure 1: Hisense Arena

Queue 1: This is the High-Priority queue (priority number ≤ 3). Customers in this

queue are treated in the way of combined Highest Priority First (HPF) and Weighted Round

Robin (WRR — definition see below) on priority as follows: Select the highest priority customer

(customers with the same priority are processed in their arrival order), and then process this

customer’s request for a ticket quota of N =

weighted time quantum

5 time units tickets non-preemptively, then

move this customer to the end of (the priority-subqueue of) Queue 1, where

• weighted time quantum = (10 − customer’s priority number) × 10

• 1 ticket costs 5 time units to process.

• customer’s priority number is the customer’s current priority number.

Weighted Round Robin (WRR): Given n processes P1, P2, . . . , Pn, where process Pi has

a weight wi (1 ≤ i ≤ n), WRR allocates Pi a weighted time quantum of wi time units (i.e.

a share of P wi

n

i=1 wi

CPU time). In this assignment, to simplify the implementation, a process’

weight is (10 − customer’s priority number), and customer’s priority number is the customer’s

current priority number.

2

For example, The priority number 2 in this queue is decreased by one run of this customer,

i.e. once booked the first N =

(10−2)×10

5 = 16 tickets its priority will become 3 and its ticket

quota for the next run will book N =

(10−3)×10

5 = 14 (instead of 16 in its first run).

Customers of the same priority are processed in their arrival order. The priority of a

customer in this queue is decreased by one every 2 runs of this customer, i.e. when a customer

has been processed 2 times under its current priority, its priority number will be increased by

1. When a customer’s priority number reaches 4, it will be demoted from Queue 1 to Queue 2.

Queue 2: This is the Low-Priority queue (priority number ≥ 4). Customers in this queue

are handled in Shortest Remaining Time First. That is, select the customer with shortest

remaining time, regardless of their priorities, and process this customer’s request preemptively

(to any a new arrival or promoted customer in Queue 1).

Customers of the same job length (time units) are processed in their priority number increasing

order. Customers of the same job length and priority are processed in their arrival

order.

Note: once a running customer X in this queue is interrupted by a promoted or new arriving

customer in Queue 1, customer X will quit execution immediately and the new customer in Queue

1 will get the CPU to run.

Aging mechanism

Because Queue 1 has priority over Queue 2, and the HPF strategy is applied, starvation

may occur. That is, some customers in Queue 2 may never get to run because there is always

a job with higher priority in Queue 1. To address the starvation issue, you must implement the

following aging mechanism that dynamically promotes a customer of Queue 2 to Queue 1 when

he/she experiences starvation.

The priority of a customer in this queue (Queue 2) is increased by one every 100 time units

run of other customers since the last run of this customer. That is, if a customer has waited 100

time units of other customers since his/her last run, his/her priority number will be decreased

by one. In this way, the priority number of each customer in Queue 2 decreases gradually in

proportion to the waiting time since the last run. When a customer’s priority number reaches

3, it will be promoted from Queue 2 to Queue 1.

Note:

• Order of simultaneous arrivals of same-priority customers:

For customers arriving at the same time with the same priority to both queues, we assume

their arrival order follows the increasing order of their customer IDs.

• Order of new arrivals, preemption and promotion

• For Queue 1, there may be three types of customers with the same priority arriving simultaneously

at the end of (the priority-subqueue of) Queue 1 — a new arrival customer A

to Queue 1, a customer B with this priority of Queue 1 moved to the end of Queue 1 (by

Weighted-Round-Robin), and a promoted customer C from Queue 2 to Queue 1. In this

case, their execution) order in Queue 1 will be Queue1 → A → B → C

• For Queue 2, there may be two types of customers arriving simultaneously to Queue 2

— a new arrival customer A to Queue 2 and a demoted customer B from Queue 1, their

relative arrival order in Queue 2 will be Queue2 → B → A.

Test

Input

We have N customers, Each customer is identified by a line in the input file. The line

describes the customer ID, arrival time(Can be divisible by 5), priority, age and the total tickets

3

required. For example a1 5 1 0 50 describes a customer a1 which arrived at time 5 with priority

number 1 and age 0, and requires 50 tickets. One ticket processing consumes one time unit.

Output

The output includes N+1 lines. it provides information of each customer execution. First

line is string include ”name arrival end ready running waiting”. The next N lines (sorted by

termination time) should report the customer ID, arrival and termination times, ready time (the

first time the system processes his/her request) and durations of running and waiting.

Web-submission instructions

• First, type the following command, all on one line (replacing xxxxxxx with your student

ID):

svn mkdir –parents -m ”OS”

https://version-control.adelaide.edu.au/svn/axxxxxxx/2020/s2/os/assignment1

• Then, check out this directory and add your files:

svn co https://version-control.adelaide.edu.au/svn/axxxxxxx/2020/s2/os/assignment1

cd assignment1

svn add TicketBooker.cpp

svn add StudentFile1.cpp

svn add StudentFile2.cpp

· · ·

svn commit -m ”assignment1 solution”

• Next, go to the web submission system at:

https://cs.adelaide.edu.au/services/websubmission/

Navigate to 2020, Semester 2, Operating Systems, Assignment 1. Then, click Tab ”Make

Submission” for this assignment and indicate that you agree to the declaration. The

automark script will then check whether your code compiles. You can make as many

resubmissions as you like. If your final solution does not compile you won’t get any marks

for this solution.

• We will test your codes by the following Linux commands:

g++ TicketBooker.cpp -o TicketBooker

./TicketBooker input.txt>output.txt

• For undergraduate student write students name and ID on File Header comments of TicketBooker.cpp

4


版权所有:编程辅导网 2021 All Rights Reserved 联系方式:QQ:99515681 微信:codinghelp 电子信箱:99515681@qq.com
免责声明:本站部分内容从网络整理而来,只供参考!如有版权问题可联系本站删除。 站长地图

python代写
微信客服:codinghelp