CS590DM: Distributed Systems
for
Architecture Design and Information
Management
Instructor: Yugyung Lee
Class Hours: Tuesdays 10:00am - 12:25pm
Room: FH304
Overview:
Distributed system design for mobile applications is an emerging research area involving broad topics of interest (including models of information processing, coordination, communication and concurrency, mobile computing, distributed architectures, heterogeneity of devices, networks and services, context awareness and resource discovery), a variety of different technologies and applications such as environmental monitoring, industrial sensing and diagnostics, infrastructures, and battlefield awareness. This course examines fundamental and emerging concepts in the technology, applications, and architecture of distributed computing and emphasizes the importance of an application-driven approach to the architectural design and implementation of distributed systems.
Topics:
· Constraints/challenges, collaborative information processing and distributed systems (sensor network, Grid, Pervasive, Web, etc)
· Networking for heterogeneous networks: directed diffusion, aggregation
· Localization and tracking: scenarios, localization, tracking, data association, tracker performance metrics, mobile clustering, leader election, kinetic data structure, global coordination through local actions
· Software architectures: Network discovery/initialization, location/time services, scalable discovery, smart spaces (vehicles and buildings, etc), negotiation architectures, self-assembly, service composition, mobility, and scalable services.
· Information management: sensor database, querying, publish & subscribe, information summarization, geometric querying, sensor fusion, distributed databases, probabilistic reasoning, and algorithmic design.
· Driving applications: environmental monitoring (e.g. traffic, habitat, security), industrial sensing and diagnostics (e.g. factory, appliances), infrastructures (e.g. power grid, water distributions, waste disposal), and battlefield awareness (e.g. multi-target tracking).
Prerequisites:
Graduate courses in software engineering and undergraduate courses in databases, operating systems and networking
Grading:
Research Project: 40%
·
Students
will undertake a significant research project (software design, tools,
analysis, simulation)
·
Groups
of up to three students
·
Students
will present projects in class and write a research paper.
Paper review, Class presentation & Participants: 30%
·
Students
will read 2 papers a week and write a short critique of each paper.
·
Paper
presentation and discussion (topic/paper specified by the instructor)
Exams and In-class
Exercises: 30%
·
One
or two exams
·
Daily
exercise with small problem sets
Grading
policy: 100
- 94
= A; 93 - 90 = A-; 89 - 87 = B+; 86-83 = B; 82- 80 = B-
and so on.
References
Late Submission:
The late policy on
assignments is 10% off the grade if late within one day, 20% off the grade for
two days late, 30% off the grade for three days late. Assignments that are submitted more than three days late will no longer
be accepted. More information will be available on the Announcements web
page.
Policy on Student Attendance and Make-ups:
Each student should
make every attempt to get to class on time. The instructor is
willing to circulate a sign-in
sheet at every class and missing more than two class sessions may result in a reduced grade. With the exception of
documented emergencies, medical reasons or out of town travel related to work,
make-ups will not be possible. Whenever possible, advance notification is
required.
University
Policy on Student Conduct:
Cheating, plagiarism, disruptive
behavior and other forms of unacceptable conduct are subject to strong
sanctions in accordance with university policy. See detailed description of
university policy at the following URL: http://www.umkc.edu/html/handbook/policies-and-regulations/conduct.html
University
policy on English proficiency of Instructors:
"Students who encounter
difficulty in their courses because of the English proficiency of their
instructors should speak directly with their instructors. If additional
assistance is needed, they may contact the UMKC Help Line at 816-235-2222 for
assistance."