Abstract - Ph D thesis Mehdi Amirijoo

QoS Control of Real-Time Data Services under Uncertain Workload


Real-time systems comprise computers that must generate correct results in a
timely manner. This involves a wide spectrum of computing systems found in
our everyday life ranging from computers in rockets to our mobile phones.
The criticality of producing timely results defines the different types of
real-time systems. On one hand, we have the so-called hard real-time
systems, where failing to meet deadlines may result in a catastrophe. In
this thesis we are, however, concerned with firm and soft real-time systems,
where missing deadlines is acceptable at the expense of degraded system
performance. The usage of firm and soft real-time systems has increased
rapidly during the last years, mainly due to the advent of applications in
multimedia, telecommunication, and e-commerce. These systems are typically
data-intensive, with the data normally spanning from low-level control data,
typically acquired from sensors, to high-level management and business data.
In contrast to hard real-time systems, the environments in which firm and
soft real-time systems operate in are typically open and highly
unpredictable. For example, the workload applied on a web server or base
station in telecommunication systems varies according to the needs of the
users, which is hard to foresee. In this thesis we are concerned with
quality of service (QoS) management of data services for firm and soft
real-time systems. The approaches and solutions presented aim at providing a
general understanding of how the QoS can be guaranteed according to a given
specification, even if the workload varies unpredictably. The QoS
specification determines the desired QoS during normal system operation, and
the worst-case system performance and convergence rate toward the desired
setting in the face of transient overloads. Feedback control theory is used
to control QoS since little is known about the workload applied on the
system. Using feedback control the difference between the measured QoS and
the desired QoS is formed and fed into a controller, which computes a change
to the operation of the real-time system. Experimental evaluation shows that
using feedback control is highly effective in managing QoS such that a given
QoS specification is satisfied. This is a key step toward automatic
management of intricate systems providing real-time data services.



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Last modified on October 2007 by Anne Moe