Full Project – Design and implementation of a database driven cloud computing for university course scheduling, ordering and allocation management system

Full Project – Design and implementation of a database driven cloud computing for university course scheduling, ordering and allocation management system

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CHAPTER ONE

 

 

INTRODUCTION

 

1.1 BACKGROUND OF THE STUDY

 

Timetabling concerns all activities with regard to producing a schedule that must be subjective to different constraints. Timetable can be defined as the optimization of given activities, actions or events to a set of objects in space-time matrix to satisfy a set of desirable constraints.

Timetabling is a problem that concerns every teaching institution. Every year a new timetable must be produced to take account of staff, student and course changes causing a necessarily large amount of work. Computer timetabling and administration systems do exist to ease this burden but each timetabling problem is as individual as the institution from which it originates (Burke,2000).

A key factor in running an educational center or basically an academic environment is the need for a well-planned, well-throughout and clash-free timetable. Back in the days when technology was not in wide use, (lecture) timetables were manually created by the academic institution.

Every school year, tertiary institutions are faced with the tedious task of drawing up academic timetables that satisfies the various courses and the respective examination being offered by the different departments.

Timetable development process starts when each Head of Department provide the following information to be used for timetable scheduling. The information provides the modules with dates, time and venues suitable in a particular semester:

 

  • Examinable courses in a particular semester.
  • Specified time for lectures ( i.e. Between 8am and 4pm)
  • The venue of the scheduled lectures.
  • Dates for lectures to be held (Lectures can be scheduled between Monday and Friday).

A timetabling problem consists of four (4) parameters and they are: T (set of time), R (set of available resources), M (set of scheduled contacts) and C (set of constraints). This problem assigns time and resources to the contacts on such a way that the constraints will be satisfied. In various timetabling problems, educational timetabling has been generally examined from practical standpoint. Academic timetable is very crucial but it consumes time due to its frequent occurrences and usage among higher institution of learning. Another reason for the difficulty is because of the great complexity of the construction of size of lectures and examinations, due to the scheduling size of the lectures and examinations periods and high number of constraints and criteria of allocation which is usually circumvented with the use of little strict heuristics, based on solutions from previous year (Jose, 2008).

 

The quality of the timetable determines the quality of time dedicated by lecturers, students and administrators to academic activities. Various academic timetabling includes:

 

  1. School timetable

 

  1. Lecture timetable

 

  • Examination timetable and

 

  1. Assignment timetable (Qu, Burke, McCollum, Merlot and Lee, 2004).

 

This academic timetable must meet a number of requirements and should satisfy the desires of all entities involved simultaneously as well as possible. The timings of events must be such that nobody has more than one event at the same time (Roberts, 2002).

Design and Implementation of a data based driven cloud computing for university course scheduling, ordering and allocation management system is a  way of optimizing the algorithm used in today’s timetable systems to generate the best of timetabling data with fewer or no clashes.

 

1.2 STATEMENT OF THE PROBLEM

 

  • The manual solution of the timetabling problem usually requires many person-days of work. In addition, the solution obtained maybe unsatisfactory in some aspects.
  • Most educational institutions have resorted to manual generation of their timetables which according to statistics takes much time to get completed and optimal.
  • Lectures scheduled or assigned to periods and rooms over a limited time period are always conflicting with other lectures.

 

1.3 AIM AND OBJECTIVES OF THE STUDY

 

The aim of this work is Design and Implementation of a data based driven cloud computing for university course scheduling, ordering and allocation management system.

The objectives of this work are as follows:

 

  1. To develop an optimized algorithm that can be used in today’s timetable systems to generate the best of timetabling data with fewer or no clashes.
  2. Based on the algorithm developed in (i) above, to develop a source code using PHP(Hypertext preprocessor)
  • To develop a web based database using MYSQL.
  1. To develop the front end of the system using HTML.
  2. To test run the system on sublime text windows.

 

 

 

 

1.4 SIGNIFICANCE OF THE STUDY

 

 

The proposed system will provide an attractive graphical front-end for the administrators and students (mobile platform). It will improve flexibility in timetable construction, the system will save time. Productivity will be improved and the system can be revised i.e. its backend can be revised.

Proper recording of class size, number of courses offered, number and capacity of available lecture halls. Efficient execution of academic activities.

 

1.5 SCOPE AND LIMITATIONS OF THE STUDY

 

This study will only cover the management and allocation of spaces and time for lectures in the<your department>,<your school>.

 

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Full Project – Design and implementation of a database driven cloud computing for university course scheduling, ordering and allocation management system