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Title page for ETD etd-10272008-144028


Type of Document Dissertation
Author Shankaran, Nishanth
URN etd-10272008-144028
Title Adaptive Resource Management Algorithms, Architectures, and Frameworks for Distributed Real-time Embedded Systems
Degree PhD
Department Computer Science
Advisory Committee
Advisor Name Title
Prof. Douglas C. Schmidt Committee Chair
Dr. Chenyang Lu Committee Member
Dr. Xenofon D. Koutsoukos Committee Member
Prof. Gautam Biswas Committee Member
Prof. Janos Sztipanovits Committee Member
Keywords
  • Resource Management
  • Distributed Systems
  • Realtime Systems
Date of Defense 2008-10-24
Availability unrestricted
Abstract
There is an increasing demand for adaptive capabilities in distributed real-time and embedded (DRE) systems that execute in open environments where system operational conditions, input workload, and resource availability cannot be characterized accurately a priori. A challenging problem faced by researchers and developers of such systems is devising effective adaptive resource management strategies that can meet end-to-end quality of service (QoS) requirements of applications. To address this

challenge, this dissertation presents three contributions to the research on adaptive resource management for DRE systems. First, it presents the Hierarchical Distributed Resource-management Architecture (HiDRA), which

provides adaptive resource management using control techniques that enables the system to adapt to workload fluctuations and resource availability for both bandwidth and processor utilization simultaneously. Second, it

describes the structure and functionality of the Resource Allocation and Control Engine (RACE), which is an open-source adaptive resource management framework built atop standards-based QoS-eabled component middleware. Third, it presents three representative DRE system case studies where RACE has been successfully applied. These case studies demonstrate and evaluate

the effectiveness of RACE in the context of representative DRE systems.

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