EECS 684: Current Topics in Database Systems, Winter 2006


Reading List



Course Description

Database systems have come along a long way since their inception in the 1970s. Database Management Systems (DBMSs) have been widely successful and are the heart of most information management system. However, there are a number of significant challenges that future DBMSs must meet if they are to continue playing the center role in information processing and management. We are on the verge of a new revolution in ubiquitous computing in which zillions of devices, ranging from small personal digital assistants (PDAs) to “invisible” embedded sensor devices, will demand answers to queries under a wide range of system conditions. These devices will rely on a distributed backend infrastructure to deliver the query results. The data sets in the back-end systems are growing at astonishing rates, demanding scalable distributed data management techniques. Furthermore, the data sets are increasingly complex, and are not limited to simple alphanumeric data types (which traditional relational DBMS manage very effectively). Database query processing and database storage techniques that exist today fall far short of meeting the demands of these future systems. What then are the techniques that will deliver this new world to us? This is the question that we will explore in this course. The course will focus primarily on query processing and query evaluation techniques that are likely to be applicable in mobile, distributed, and sensor database environments of the future. Since most of the questions in this area are unanswered, this course will be very exploratory.

The syllabus for this course is a list of paper readings. Some of these papers are also included in the popular “red book”, which is on reserve at the library. For roughly the first half of the semester, I will present papers to bring you up-to-speed with the database query processing and data management techniques that are currently deployed in DBMSs, and also cover a few papers describing techniques that are likely to be successful in the environment outlined above. The second half of the semester will include paper presentation by the students. We will cover ~2-3 papers a week and every student in the class must read all these papers (including the papers that your fellow class-mates present). Before each class you will be required to hand in a brief summary (~10 sentences total) of the paper that will be discussed in the class. The summary should not a facsimile of the abstract of the paper, but should be your assessment of the key contributions and limitations of the paper. The reviews will be graded on a scale of 0-4 (4 being the highest grade).

Note for Masters Students: EECS 684 is approved for 500-level Masters credit.

Course Project

A class project, in which you pick a topic in this area and explore it in detail, is a big component of this course. I will provide a list of suggested project topics, though you are free to select a project outside of this list provided you get prior approval. You will have to meet with me every third week throughout the semester updating me on the progress of your project. I will help with the direction, but unless you take the initiative to actively explore the topic you choose, you are unlikely to accomplish much in the project. I will expect that at the end of the course, your project report should be at a level of a workshop/conference submission.

For the projects you may work in a group. The maximum group size is 2, and I encourage most projects to be individual projects. My expectations will be scaled based on the group size.

Time and Place

TTH 9:00-10:30, 3437 EECS.

Office Hours

T 10:30-12:30, 4717 CSE, or by prior appointment. [Note OH are in the new CSE building next to the DOW building]


EECS 484 or equivalent. Note EECS 584 is not a pre-requisite for this course.


No formal text. The reading list is a collection of papers, which is posted on the course web page.

Reference text: We will occasionally refer to the following sources. Note you don’t need to purchase these textbooks; two copies of each of these references are on reserve at the Media Union Library.

·        Red Book: Readings in Database Systems (4th edition) - edited by Michael Stonebraker and Joe Hellerstein, Morgan Kaufmann Publisher.

·        Cow Book: Database Management Systems (3rd edition) - by Raghu Ramakrishnan and Johannes Gehrke, McGraw Hill 1999.


·        One midterm: 35%. Date: TBD.

·        Course Project: 50%.
Two project updates: 10%
Project presentation: 5%
Final Project Report and Demo: 35%.

·        Student Paper Presentation: 5%.

·        Paper Summaries and Class Participation: 10%.