SEEC: A Framework for Self-aware Computing
Name
MIT-CSAIL-TR-2010-049.pdf
Size
1.49 MB
Format
Adobe PDF
Checksum (MD5)
d0ebaacaaf7631b8e14b3a70fb4f0bab
Author(s)
Hoffmann, Henry
Maggio, Martina
Santambrogio, Marco D.
Leva, Alberto
Agarwal, Anant
Advisor(s)
Anant Agarwal
Date Issued
October 13, 2010
Series/Report no.
MIT-CSAIL-TR-2010-049
Abstract
As the complexity of computing systems increases, application programmers must be experts in their application domain and have the systems knowledge required to address the problems that arise from parallelism, power, energy, and reliability concerns. One approach to relieving this burden is to make use of self-aware computing systems, which automatically adjust their behavior to help applications achieve their goals. This paper presents the SEEC framework, a unified computational model designed to enable self-aware computing in both applications and system software. In the SEEC model, applications specify goals, system software specifies possible actions, and the SEEC framework is responsible for deciding how to use the available actions to meet the application-specified goals. The SEEC framework is built around a general and extensible control system which provides predictable behavior and allows SEEC to make decisions that achieve goals while optimizing resource utilization. To demonstrate the applicability of the SEEC framework, this paper presents fivedifferent self-aware systems built using SEEC. Case studies demonstrate how these systems can control the performance of the PARSEC benchmarks, optimize performance per Watt for a video encoder, and respond to unexpected changes in the underlying environment. In general these studies demonstrate that systems built using the SEEC framework are goal-oriented, predictable, adaptive, and extensible.
Subjects
Autonomic Computing
Adaptive Computing
Multicore
Control Theory
Persistent DSpace Link
