The aim of this assignment is to improve your learning experience on process scheduling
algorithms. You are required to design an online ticketing system for the Melbourne Arena, one
of the largest stadiums in Australia that offers state-of-the-art facility for hosting sports and
entertainment events including the Australian Open tennis tournament held annually.
Specifically, there are 10,500 seats for public booking via this system for a single match. Figure ??
shows the distribution of the seat sections, where all the yellow and green areas are for public
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.
Figure 1: Hisense Arena
A new customer on arrival will be put on Queue 1 if his/her priority number ≤ 3 or Queue
Detailed actions in these queues are described below:
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
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.
Customers of the same priority are processed in their arrival order. The priority of a customer in this queue is decreased by 1 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.
For example, the priority number 2 in this queue is decreased by 1 after 2 runs of this
customer, i.e. once booked 2 × N = 2 ×
5 = 32 tickets its priority will become 3 and
its ticket quota for the next 2 runs will be N =
5 = 14 (instead of 16 in its previous 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
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.
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.
• 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.
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
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 5 time unit.
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.
• First, type the following command, all on one line (replacing xxxxxxx with your student
svn mkdir –parents -m ”OS”
• Then, check out this directory and add your files:
svn co https://version-control.adelaide.edu.au/svn/axxxxxxx/2020/s2/os/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:
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
• Do not forget to include your name(s) and student ID(s) in File Header comments of