FIT3142 Distributed computing - Semester 2, 2015

Modern computer systems rely increasingly on distributed computing mechanisms, implemented often as clusters, web services, grids and clouds. Distributed computing systems can provide seamless (or web-like) access to a variety of networked resources, e.g. processing cores, large data stores and information repositories, expensive instruments, high-speed links, sensor networks, and multimedia services for a wide range of applications. This unit provides foundation knowledge and understanding of the basic mechanisms required to implement distributed computing systems, especially clouds, grids, web services and clusters. Topics covered include: Introduction to parallel and distributed computing mechanisms, concurrency and synchronisation, monitors, deadlocks, concurrent program analysis - Deadlock, Safety & Liveness properties, computational and service-oriented grids. LVS and Beowulf Clusters. Gridservices, Webservices, WSDL, HPC Portals, Home Grids, Clouds and Peer-to-Peer (P2P) networks. Distributed applications, and their performance and reliability in relation to processor and network performance constraints.

Mode of Delivery

Workload Requirements

Minimum total expected workload equals 12 hours per week comprising:

(a.) Contact hours for on-campus students:

• Two hours of lectures
• One 2-hour laboratory
• One 1-hour tutorial

(b.) Additional requirements (all students):

• A minimum of 7 hours independent study per week for completing lab and assignment work, private study and revision.

See also Unit timetable information

Unit Relationships

Prohibitions

FIT3010

Prerequisites

(FIT2069, FIT2070 and one of FIT3141 or ECE2041) or (FIT1005/FIT2008 and FIT2022)

Chief Examiner

Campus Lecturer

Tutors

Your feedback to Us

Previous Student Evaluations of this Unit

Students in previous offerings have found this unit to be intellectually stimulating.

Academic Overview

Learning Outcomes

1. understand basic problems in distributed computing, especially in relation to concurrency, parallelism, synchronisation, deadlocks, safety and liveness properties;
2. understand differences between various distributed computing models and widely used distributed computing schemes;
3. understand basic functional and performance concepts in grids and clouds and identify frequent causes of performance problems in grid applications;
4. understand basic software and hardware reliability concepts in grids and identify frequent causes of reliability problems in grid applications;
5. discuss some of the enabling technologies e.g. high-speed links, emulators and storage area networks for building computer grids and clouds;
6. explain the use of some of the cloud computing, grid computing and clustering middleware used to implement virtual super computers, including security mechanisms;
7. explain programming toolkits such as Parallel Virtual Machine (PVM) for writing parallel computer applications;
8. explain HPC Portals, peer-to-peer (P2P) networking and semantic grids;
9. elaborate some of the significant grid and cloud computing areas of application e.g. Bio-Technology, eHealth and eMedicine, Finance, and Computer Networks;
10. install and configure a small computer grid using Globus toolkit middleware;
11. gain basic familiarity with commonly used grid application tools and middleware interfaces;
12. extend the grid and test these applications.

Unit Schedule

*Unit Schedule details will be maintained and communicated to you via your learning system.

Teaching Approach

Assessment Summary

Examination (3 hours): 60%; In-semester assessment: 40%

Assessment Requirements

Assessment Policy

Assessment Tasks

Participation

To meet the learning objectives for this unit students are expected to attend 80% of Tutorials (MURPA) and 80% of Labs. Failure to meet these expectations may cause difficulties in passing the unit.

• Assessment task 1

  Title:

  Assignment 1

  Description:

  This assignment will be a written report requiring some independent reading.
  
  Further details will be provided during the semester.

  Weighting:

  10%

  Criteria for assessment:

  Individual assessment of independent work by student:

  1. How well underlying principles and theories are demonstrated in the student's answers
  2. The appropriateness of the formatted report style
  3. The quality of the student's arguments

  Due date:

  Friday Week 7 (11/Sep), 12PM

  Remarks:

  This task covers the following learning outcomes:

  1. understand differences between various distributed computing models and widely used distributed computing schemes;

• Assessment task 2

  Title:

  Assignment 2

  Description:

  This assignment will be a written report requiring some independent reading.
  
  Further details will be provided during the semester.

  Weighting:

  15%

  Criteria for assessment:

  Individual assessment of independent work by student:

  1. How well underlying principles and theories are demonstrated in the student's answers
  2. The appropriateness of the formatted report style
  3. The quality of the student's arguments

  Due date:

  Friday Week 11 (17/Oct), 12PM

  Remarks:

  This task covers the following learning outcomes:

  1. understand basic functional and performance concepts in grids and clouds and identify frequent causes of performance problems in grid applications;

• Assessment task 3

  Title:

  Laboratory Work

  Description:

  Weekly laboratory exercises and tasks. Individual tasks and assessments.

  Weighting:

  10%

  Criteria for assessment:

  The laboratory work is group-based and it is assessed on correctness and on the quality of the solutions and on the quality of presentation/documentation. Individual marks for each group member will be derived from (i) the peer assessements made by the group under the supervision of the tutor and (ii) the overall marks achieved by the group.

  Due date:

  Weekly (starting Week 2)

  Remarks:

  This task covers the following learning outcomes:

  1. install and configure a small computer grid using Globus toolkit middleware;
  2. gain basic familiarity with commonly used grid application tools and middleware interfaces;
  3. extend the grid and test these applications.

  NB laboratory tasks are being updated in 2015 and will cover in part other learning outcomes.

• Assessment task 4

  Title:

  Tutorial Work

  Description:

  Weekly attendance of MURPA tutorials or FIT Seminars/Colloquia (in G12A/26, Clayton) and reporting by students. The students who are unable to attend a scheduled session owing to timetabling conflicts may have the option to review the MULO recordings available at https://messagelab.monash.edu.au/MURPA and www.infotech.monash.edu.au/seminars
  
  This is an individual assessment, with submission required in Week 11.

  Weighting:

  5%

  Criteria for assessment:

  Individual assessment of independent work by student:

  1. How well underlying principles and theories are demonstrated in the student's answers
  2. The appropriateness of the formatted report style
  3. The quality of the student's arguments

  Due date:

  Friday Week 11 (17/Oct), 12PM

  Remarks:

  This task covers the following learning outcome:

  1. elaborate some of the significant grid and cloud computing areas of application e.g. Bio-Technology, eHealth and eMedicine, Finance, and Computer Networks;

Examinations

• Examination 1

  Weighting:

  60%

  Length:

  3 hours

  Type (open/closed book):

  Closed book

  Electronic devices allowed in the exam:

  Non programmable scientific calculator

  Remarks:

  Exam covers the following learning outcomes:

  1. understand basic problems in distributed computing, especially in relation to concurrency, parallelism, synchronisation, deadlocks, safety and liveness properties;
  2. understand differences between various distributed computing models and widely used distributed computing schemes;
  3. understand basic functional and performance concepts in grids and clouds and identify frequent causes of performance problems in grid applications;
  4. understand basic software and hardware reliability concepts in grids and identify frequent causes of reliability problems in grid applications;
  5. discuss some of the enabling technologies e.g. high-speed links, emulators and storage area networks for building computer grids and clouds;
  6. explain the use of some of the cloud computing, grid computing and clustering middleware used to implement virtual super computers, including security mechanisms;
  7. explain programming toolkits such as Parallel Virtual Machine (PVM) for writing parallel computer applications;
  8. explain HPC Portals, peer-to-peer (P2P) networking and semantic grids;
  9. gain basic familiarity with commonly used grid application tools and middleware interfaces;

Learning resources

Reading list

George Coulouris, Jean Dollimore, Tim Kindberg and Gordon Blair, Distributed Systems: Concepts and Design, Fifth Edition, published by Addison Wesley, May 2011, ISBN 0-13-214301-1 (not prescribed)

Feedback to you

• Informal feedback on progress in labs/tutes
• Graded assignments with comments

Extensions and penalties

Returning assignments

Resubmission of assignments

Resubmission is not permitted.

Referencing requirements

External materials must be properly cited and referenced.

Assignment submission

Online submission

If Electronic Submission has been approved for your unit, please submit your work via the learning system for this unit, which you can access via links in the my.monash portal.

Other Information

Policies

Graduate Attributes Policy

Student Charter

Student services

Monash University Library

Disability Liaison Unit

Other

Engineers Australia Stage 1 competencies

This unit is a core unit in the Bachelor of Software Engineering accredited by Engineers Australia. Engineers Australia Accreditation Policy of Professional Engineering Programs requires that programs demonstrate how engineering graduates are prepared for entry to the profession and achieve Stage 1 competencies. The following information describes how this unit contributes to the development of these competencies for the Bachelor of Software Engineering. (Note: not all competencies may be emphasised in this unit).

Relationship between Unit Learning Outcomes and BSE Course Outcomes

Relationship between Unit Learning Outcomes and Assessments