BEGIN:VCALENDAR VERSION:2.0 X-WR-CALNAME:EventsCalendar PRODID:-//hacksw/handcal//NONSGML v1.0//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York LAST-MODIFIED:20240422T053451Z TZURL:https://www.tzurl.org/zoneinfo-outlook/America/New_York X-LIC-LOCATION:America/New_York BEGIN:DAYLIGHT TZNAME:EDT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 DTSTART:19700308T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT BEGIN:STANDARD TZNAME:EST TZOFFSETFROM:-0400 TZOFFSETTO:-0500 DTSTART:19701101T020000 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT CATEGORIES:College of Engineering,Thesis/Dissertations DESCRIPTION:Topic: Cascading Failure Modeling and Analysis in Functionally Dependent Internet of Things Systems Abstract: The Internet of Things (I oT) is a complex network of components that can automatically collect, exc hange, and process data, providing indispensable support for increasingly complicated and critical missions. However, functional dependencies among heterogeneous components introduce risks of fault propagation and potentia lly high-impact cascading failures (CFs). This research examines CF mechan isms and investigates reliability analysis methods to address the effects of CFs in two types of functionally dependent IoT systems subject to rando m propagation time (RPT) and cross-phase propagation (CPP), respectively. We develop separable, analytical modeling methods for assessing the missio n reliability of considered IoT systems. The proposed methods employ a div ide-and-conquer strategy to decompose the original reliability problem int o a set of independent reduced problems that can be solved in parallel. Th e proposed methods are flexible in accommodating diverse types of time-to- failure distributions. Case studies on heterogeneous unmanned aerial vehic le (UAV) systems are performed to demonstrate the proposed methods and the effects of RPT and CPP on mission reliability. The application of the pro posed model in supporting mission planning is demonstrated through solving reliability and redundancy allocation problems. Correctness of the propos ed methods is validated using Monte Carlo simulations. This proposal also discusses future research directions in extending the proposed methods to capture more practical characteristics of IoT mission systems, developing effective mitigation strategies for enhancing system’s resilience agains t CFs, and artificial intelligence-powered methods for predicting CFs in U AV-based IoT systems. Advisor: Dr. Liudong Xing, Commonwealth Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth Commit tee Members: Dr. Lance Fiondella, Professor, Department of Electrical & Co mputer Engineering, UMASS Dartmouth; Dr. Yuchou Chang, Associate Professor , Department of Computer & Information Science; Dr. David W. Coit, Profess or, Department of Industrial & Systems Engineering, Rutgers University NOT E: All ECE Graduate Students are ENCOURAGED to attend. All interested part ies are invited to attend. Open to the public. *For further information, please contact Dr. Liudong Xing via email at lxing@umassd.edu\nEvent page : https://www.umassd.edu/events/cms/8-28-26-doctoral-candidacy-by-junxing- ren---ece-departm.php\nEvent link: https://umassd.zoom.us/j/99573148168 X-ALT-DESC;FMTTYPE=text/html:

Topic: Cascading Failure Modeli ng and Analysis in Functionally Dependent Internet of Things Systems

Abstract: The Internet of Things (IoT) is a complex network of compon ents that can automatically collect\, exchange\, and process data\, provid ing indispensable support for increasingly complicated and critical missio ns. However\, functional dependencies among heterogeneous components intro duce risks of fault propagation and potentially high-impact cascading fail ures (CFs). This research examines CF mechanisms and investigates reliabil ity analysis methods to address the effects of CFs in two types of functio nally dependent IoT systems subject to random propagation time (RPT) and c ross-phase propagation (CPP)\, respectively. We develop separable\, analyt ical modeling methods for assessing the mission reliability of considered IoT systems. The proposed methods employ a divide-and-conquer strategy to decompose the original reliability problem into a set of independent reduc ed problems that can be solved in parallel. The proposed methods are flexi ble in accommodating diverse types of time-to-failure distributions. Case studies on heterogeneous unmanned aerial vehicle (UAV) systems are perform ed to demonstrate the proposed methods and the effects of RPT and CPP on m ission reliability. The application of the proposed model in supporting mi ssion planning is demonstrated through solving reliability and redundancy allocation problems. Correctness of the proposed methods is validated usin g Monte Carlo simulations. This proposal also discusses future research di rections in extending the proposed methods to capture more practical chara cteristics of IoT mission systems\, developing effective mitigation strate gies for enhancing system’s resilience against CFs\, and artificial inte lligence-powered methods for predicting CFs in UAV-based IoT systems.

Advisor: Dr. Liudong Xing\, Commonwealth Professor\, Department of E lectrical & Computer Engineering\, UMASS Dartmouth

Committee Mem bers: Dr. Lance Fiondella\, Professor\, Department of Electrical & Compute r Engineering\, UMASS Dartmouth\; Dr. Yuchou Chang\, Associate Professor\, Department of Computer & Information Science\; Dr. David W. Coit\, Profes sor\, Department of Industrial & Systems Engineering\, Rutgers University< /p>\n

NOTE: All ECE Graduate Students are ENCOURAGED to attend. All inte rested parties are invited to attend. Open to the public.

*For f urther information\, please contact Dr. Liudong Xing via email at lxing@um assd.edu

Event page: https://www.umass d.edu/events/cms/8-28-26-doctoral-candidacy-by-junxing-ren---ece-departm.p hp
Event link: https ://umassd.zoom.us/j/99573148168

DTSTAMP:20260812T221351 DTSTART;TZID=America/New_York:20260828T100000 DTEND;TZID=America/New_York:20260828T120000 LOCATION:Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A SUMMARY;LANGUAGE=en-us:ELEC Oral Comprehensive Exam for Doctoral Candidacy by Junxing Ren - ECE Department UID:cdc5d103c80de6e1896a4a7895d197c6@www.umassd.edu END:VEVENT END:VCALENDAR