Researchers in this area investigate computer and network systems:

  • Design, develop, and prototype systems and networks with scalability, efficiency, reliability, privacy and security in mind.
  • Evaluate their performance and effectiveness through experiments, measurements and analysis.
  • Develop cutting-edge next-generation algorithms, architectures, and protocols for distributed systems and networks, including Internet of Things (IoT), cloud systems, pervasive and mobile systems, wireless and sensor networks.

Ph.D. Students

  • Asma Eidhah Aloufi (advisor: Peizhao Hu)
  • Moiz Arif (advisor: M. Mustafa Rafique)
  • Mohammed Armanuzzaman Tomal (advisor: Ziming Zhao)
  • Sahil Gupta (advisors: H.B. Acharya and Minseok Kwon)
  • Garegin Grygorian (advisor: Minseok Kwon)
  • Naureen Hoque (advisor: Hanif Rahbari)
  • Viktoria Koscinski (advisor: Peizhao Hu)
  • Avinash Kumar Maurya (advisor: M. Mustafa Rafique)
  • Justin Namba (advisor: Michael Mior)
  • Mohammad Saidur Rahman (advisor: Matt Wright)
  • Nibesh Shrestha (advisor: Mohan Kumar)
  • Xi Tan (advisor: Ziming Zhao)
  • Peter Willis (advisor: Nirmala Shenoy and H.B. Acharya)

Related Courses

Credits 3
An introduction to the hardware and software organization of computer systems. The course emphasizes a multilevel model of computer organization. Topics include the digital logic level; the micro architecture level; the machine instruction set level; the operating system level; and the assembly language level. Programming assignments will be required.
Credits 3
This course is an introduction to the organization and programming of systems comprising multiple computers. Topics include the organization of multi-core computers, parallel computer clusters, computing grids, client-server systems, and peer-to-peer systems; computer networks and network protocols; network security; multi-threaded programming; and network programming. Programming projects will be required.
Credits 3
This course is an in-depth study of data communications and networks. The course covers design of, and algorithms and protocols used in, the physical, data link, network, transport, and application layers in the Internet; methods for modeling and analyzing networks, including graphs, graph algorithms, and discrete event simulation; and an introduction to network science. Programming projects will be required.
Credits 3
An in-depth study of operating system concepts. Topics include process synchronization, interprocess communication, deadlock, multiprogramming and multiprocessing, processor scheduling and resource management, memory management, static and dynamic relocation, virtual memory, file systems, logical and physical I/O, device allocation, I/O processor scheduling, process and resource protection. Programming projects involving the development of or modification to operating system kernel features will be required.
Credits 3
Application of operating system concepts to the design of hardware interfaces for a multiprogramming environment. Laboratory work includes the development of a multiprogramming (optionally, multiprocessing) kernel with system call and interrupt handling facilities, and the building of device drivers for a variety of peripheral devices. This course provides extensive experience with those aspects of systems programming that deal directly with the hardware interface. A significant team programming project is a major component of this course.
Credits 3
Computer Architecture is a study of the design of both modern and classic computer hardware. Topics include: a review of classical computer architectures; the design of operation codes and addressing modes, data formats, and their implementation; internal and external bus structures; architectural features to support virtual storage and page-replacement policies, high-level language features, and operating systems. Students will write programs which simulate the organization of several different processor architectures to help further their understanding of design choices.
Credits 3
This course is an introduction to the concepts and principles of computer networks. Students will design and implement projects using application protocols, and will study transport, network, and data link protocols and algorithms. The course also includes an introduction to local area networks, data transmission fundamentals, and network security. Programming projects and reading research papers will be required.
Credits 3
An introduction to the study of distributed systems. The course covers distributed system architectures such as client-server and peer-to-peer, distributed system design issues such as communication, fault tolerance, coordination, and deadlock, distributed system middleware such as remote method invocation (RMI) and tuple space, and the theory of distributed algorithms such as logical clocks and leader election. Programming projects are required.
Credits 3
This course is a study of the hardware and software issues in parallel computing. Topics include an introduction to the basic concepts, parallel architectures and network topologies, parallel algorithms, parallel metrics, parallel languages, granularity, applications, parallel programming design and debugging. Students will become familiar with various types of parallel architectures and programming environments.
Credits 3
This course examines current topics in Systems. This is intended to allow faculty to pilot potential new graduate offerings. Specific course details (such as prerequisites, course topics, format, learning outcomes, assessment methods, and resource needs) will be determined by the faculty member(s) who propose a specific topics course in this area. Specific course instances will be identified as belonging to the Distributed Systems cluster, the Architecture and Operating Systems cluster, the Security cluster, or some combination of these three clusters.
Credits 3
Cyberinfrastructure integrates all parts of large-scale computing including a set of software, services, and tools in order to solve large-scale computing problems. This course will give an overview of the problems and solutions of large-scale computing, e.g., Large Hydron Collider. Students will design and develop new tools for cyberinfrastructure. Presentations and written reports are required. Note: Knowledge in data structure and object-oriented design, or permission of instructor is required.
Credits 3
This course is designed to provide students with knowledge of sensor network security with respect to practical implementations. In particular, secure sensor network design for Supervisor Control And Data Acquisition (SCADA) is discussed. SCADA encompasses technologies that manage and control much of the infrastructure that we depend on every day without realizing it. The failure or corruption of SCADA systems can not only be inconvenient but also hazardous when the resource is critical or life threatening. Securing SCADA systems is of great strategic importance. The role of sensor networks in SCADA is discussed and sensor security protocols for SCADA applications are evaluated and studied. To be successful in this course students should be knowledgeable in basic networking, systems, and security technologies.
Credits 3
This course explores current topics in Computing Security. It is intended as a place holder course for faculty to experiment new course offerings in Computing Security undergraduate program. Course specific details change with respect to each specific focal area proposed by faculty.

Research Projects

  • Measuring and Improving Public Key Infrastructure on the Internet [Chung]
  • Identifying Privacy Leakages in Online Social Network [Chung]
  • ARM-based system and software security [Zhao]
  • Cache side channel attacks [Zhao]
  • RDMA and Container Networking [Kwon, Rafique]
  • SDN-based IoT Security [Acharya, Kwon]
  • Programmable FIB Caching [Kwon]
  • Distributed File Replication [Kwon, Rafique]
  • Website Fingerprinting in Tor [Wright]
  • Automatic Caching for Distributed Applications in Apache Spark [Mior]
  • SparkFHE: Distributed Dataflow Processing with Fully Homomorphic Encryption [Hu]
  • Designing and developing mechanism for efficient distributed deep learning on high-performance systems [Rafique]
  • Citizen Science Grid [Desell]
  • Machine learning for modulation obfuscation and frequency-offset-aware demodulation [Rahbari]
  • Trust in emerging wireless systems and communications [Rahbari]
  • Exploiting wireless frame preamble to support new physical-layer functions [Rahbari]
  • Distributed Computing in Networks of UAVs/Drones [Kumar, Kwon, Hosseini]
  • Protocols for Byzantine Fault-tolerance [ Kumar]
  • Middleware for IoT-CPS Systems [Kumar]

Research Labs