Summit Financial Reporting 101 - Review of Summit Financials Dashboards(Oracle BI) for Financial Reporting | https://calendar.umassd.edu/
Summit Financial Reporting 101 - Review of Summit Financials Dashboards(Oracle BI) for Financial Reporting | https://calendar.umassd.edu/
ELEC Oral Comprehensive Exam for Doctoral Candidacy by Guixiang Lv
WHEN: Thursday, January 5, 20239:30 AM - 11:30 AM
WHERE: > See description for location
COST: Free
DESCRIPTION: Topic: Reliability and Resilience Modeling and Enhancement for Storage Area NetworksLocation: Lester W. Cory Conference RoomScience & Engineering Building (SENG), Room 213AZoom Conference Link: Zoom LinkMeeting ID: 927 1072 5307Passcode: 162575Abstract:Storage area networks (SAN) provide one of the modern effective solutions for the significant growth issue in the remote data storage and access. To deliver the desired quality of service, the reliability and resilience challenges of SANs must be addressed. A major threat to the SAN reliability is cascading failures, where a single incident triggers a chain reaction, causing extensive damages and even crash of the entire system. In the proposed research, we focus on the overload-triggered cascading failures, where the overloading of one device (e.g., switch) can fail this device, causing its workload to be reallocated to other devices, furthering causing overloads and thus failures of those devices in a domino way. We first investigate the effects of data loading on the reliability of an individual switch device in SANs using the proportional-hazards model and accelerated failure-time model. We then investigate the effects of loading on the reliability of an entire SAN through dynamic fault trees and binary decision diagrams-based analysis. Furthermore, to enhance the reliability of the SAN system, we design proactive load redistribution-based mitigation strategies that aim to prevent the occurrence of cascading failures during the specified mission time or at least alleviate the consequence of cascading failures. Load-based and reliability-based node selection rules are considered. The application and effectiveness of the proposed mitigation strategies are demonstrated and compared through detailed case studies of SANs with the mesh topology. Future directions of exploring resilience metrics, models, and strategies for SANs will be discussed.
Advisor(s): Dr. Liudong Xing, Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth
Committee Members: Dr. Hong Liu, Professor and Chairperson, Department of Electrical & Computer Engineering, UMASS Dartmouth
Dr. Honggang Wang, Professor, Department of Electrical & Computer Engineering, UMASS Dartmouth
Dr. Haining Meng, Associate Professor, School of Computer Science, Xi'an University of Technology, China
NOTE: All ECE Graduate Students are ENCOURAGED to attend. All interested parties are invited to attend. Open to the public.
*For further information, please contact Dr. Liudong Xing at 508.999.8883 or via email at liudong.xing@umassd.edu.
CONTACT: > See Description for contact information
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