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Title page for ETD etd-11162015-090359


Type of Document Dissertation
Author Emfinger, William Alexander
Author's Email Address waemfinger@gmail.com
URN etd-11162015-090359
Title Network Performance Analysis and Management for Cyber-Physical Systems and Their Applications
Degree PhD
Department Electrical Engineering
Advisory Committee
Advisor Name Title
Dr. Gabor Karsai Committee Chair
Dr. Aniruddha Gokhale Committee Member
Dr. Bharat Bhuva Committee Member
Dr. Mitch Wilkes Committee Member
Dr. Xenofon Koutsoukos Committee Member
Keywords
  • prediction
  • performance
  • systems
  • physical
  • network
  • real-time
  • embedded
  • analysis
  • cyber
  • spacecraft
  • denial of service
  • distributed denial of service
  • calculus
Date of Defense 2015-10-15
Availability unrestricted
Abstract
Cyber-Physical Systems (CPS) are becoming increasingly distributed in nature. These distributed systems interact closely with the physical world and require the use of communications channels between the computational nodes of the system as well as to external systems. Since such systems are generally remotely deployed and managed, applications deployed onto the systems must be analyzed and verified before deployment to ensure that the network can provide enough resources to the applications and to ensure that applications will not degrade the system's overall functionality. To facilitate the development of these systems, we created analysis techniques for accurately and precisely predicting run-time application network performance and resource utilization from design-time models of the network and the applications. To validate this work, we developed network traffic production and measurement code and used run-time network emulation to enforce the network characteristics. Using these experimental results, we compared the accuracy and precision of our predictive techniques with state of the art analysis techniques. Furthermore, we implemented our modeling semantics in a communications middleware to measure the data production of each application and compared it against the application's network resource requirements. By comparing the stated resource requirements to the application's actual resource utilization, we could detect deviations and take mitigation actions. Using this measurement and detection, we showed how denial of service (DoS) and distributed DoS (DDoS) attacks could be mitigated.
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