Data Communications and Networks Course Offerings: 

Data Communications and Networks area aims to provide the fundamental skill set required for telecommunication engineers and IT professionals. The courses cover a broad range of topics in computer networks, wireless networks, signal processing, information theory, cloud computing and IoT areas. Course offerings are designed to keep a good balance between theory and hand-on projects. The courses are well integrated to the research opportunities at Clarkson. 

Clarkson currently has 10 graduate level Data Communications and Networks courses. These courses are offered on-campus and through the distance learning program. Courses are offered in every semester unless otherwise stated. All courses are elective.

Fall Courses

  • EE 507 Computer Networks
  • EE 529 Stochastic Processes in Engineering
  • EE 501 Digital Signal Processing  
  • EE 511 Wireless Sensor Networks
  • EE 570 Coding and Information Transmission

Spring Courses

  • EE 512 Cloud Systems and Networks
  • EE 552 Optimization Techniques in Engineering (even Springs)
  • EE 510 Computer and Network Security
  • EE 514 Wireless Communications and Mobile Networks
  • EE516 Performance analysis of communication networks

The graduate course offerings will be updated from time to time.  However, the number of graduate courses and frequency of their offerings will be maintained.

Research opportunities:

ECE Department has two research labs that offer research opportunities in this area.

Course Descriptions

EE 507 - Computer Networks

This course covers layered networking protocols with an emphasis on common Internet protocols such as TCP, IP, HTTP, and SMTP. It also covers local area networking, focusing on link layer standards such as the IEEE standards for Ethernet and wireless. Additional topics such as security and congestion control will also be covered. EE407 and CS455 are offered each fall as one course with multiple listings.

EE 529 - Stochastic Processes in Engineering

Review of the theory of probability.  Single and multiple random variables topics, such as distributions, moments, conditioning, central limit theorem, and Laws of Large Numbers.  Stochastic processes. Stationary and nonstationary processes.  Time averaging and ergodicity. Correlation and power spectrum. Langevin's equation and Markov processes. Poisson and Gaussian processes. Response of linear systems. Approximate methods for analysis of nonlinear stochastic equations Application to engineering problems, such as random vibrations, turbulence, estimation theory, signal detection, and others.

EE 501 - Digital Signal Processing   

An introduction to discrete-time signal processing. Topics include: A review of orthogonality, Fourier series, Fourier transforms and sampling theory. Smoothing, interpolation, D/A conversion. Digital filters, windows. Design of nonrecursive filters, recursive filters. Correlation and spectra of random signals, spectral estimation. Substantial in depth investigation of advanced topics will be required.

EE 511- Wireless Sensor Networks

This course presents state-of-the-art wireless sensor networks.  Both hardware and operating system considerations based on the OSI protocol stack are covered.  Clustering and localization techniques are presented along with security threats and solutions.   Various wireless senor network applications are also introduced.

EE 570 - Coding and Information Transmission

Error detecting and error correcting codes. Encoding of signals and data compression. Huffman codes. Concepts of information. Limits on attainable data compression. Limits on data rates for reliable or errorless transmission.

EE 512 - Cloud Systems and Networks

This course is an introduction to cloud computing systems and cloud networks. The primary focus will be communication infrastructures and networking principles for cloud computing with an emphasis placed on network virtualization, mobile cloud computing and inter-data-center networks. Topics will include: a thorough presentation of cloud computing service models, namely Infrastructure-as-a-Service (IaaS), Platform–as-a-Service (PaaS) and Software-as-a Service (SaaS); detailed investigation of cloud management issues with an emphasis on mobile cloud computing, cloud data center management and provisioning in cloud networks;  security and privacy in the cloud; and sustainability of cloud systems from a communications perspective. Reading contemporary issues on cloud systems and networking will be an important part of this course. Several technical paper reading/presentation assignments and one term project will be given throughout the semester.

EE 552 - Optimization Techniques in Engineering

Introduction to optimization techniques in engineering. Topics include: engineering applications of optimization, types of optimization problems, linear programming and the simplex method, one-dimensional optimization, unconstrained nonlinear programming, nonlinear programming with equality and inequality constraints, advanced optimization techniques, practical aspects of optimization.

EE 510 - Computer and Network Security

Attacks on networked computer systems are an increasingly important problem. This course covers the types of vulnerabilities that are present in modern computer systems and the types of malicious software that exploit these vulnerabilities. It also covers best practices for preventing, detecting and responding to such attacks including anti-virus software, defensive programming techniques, intrusion detection systems, honeypots and firewalls.

EE 514 -Wireless Communications and Mobile Networks

This course presents basic principles of wireless communications and mobile networks.  Propagation characteristics, modulation and coding techniques, mobility management, signaling, resource allocation, interference management, outage probability, spectrum sensing, medium access, routing and broadband access networks are covered. Cognitive radio networks, vehicular networks, GSM, CDMA, 3GPP and new generation systems are introduced. Various recent topics such as 5G small cells, machine-to-machine communications and tactile Internet are presented.

EE516 - Performance analysis of communication networks

This course is an introduction to queuing systems in communication networks and network calculus. Two primary foci will be on stochastic  modeling of network traffic and application of network calculus to wired/wireless networks with an emphasis placed on quality of service management in next generation networks.  Topics will include: A brief presentation of Markov models and a thorough presentation of the application of queuing systems to network traffic modeling particularly focusing on Little's Theorem and Jacksonian networks. The topics will further include the application of min-plus algebra, traffic envelopes, service and arrival curves, min-plus convolution, sub-additive functions, rate functions, backlog, burst tolerance and leaky buckets to network analysis. Reading contemporary issues on performance analysis of next generation communication systems will be an important part of this course. Several technical paper reading assignments and one term project will be given throughout the semester.