Quality of service middleware
| Published date | 01 February 2003 |
| Pages | 47-51 |
| DOI | https://doi.org/10.1108/02635570310456896 |
| Date | 01 February 2003 |
| Author | Warren Adis |
| Subject Matter | Economics,Information & knowledge management,Management science & operations |
Quality of service middleware
Warren Adis
Computer Science Department, Iona College, New Rochelle, New York, NY
Quality of service (QoS)
dimensions
QoS refers to optimizing the performance of a
network relative to a specific application and
takes place through resource management. It
is accomplished through management tools
that reserve bandwidth, prioritize usage,
monitor change, and scale resources to
provide performance assurances (Wang et al.,
2000). Therefore with QoS, there is an
increased probability that an application, if
allowed to proceed at all, will have the
network resources it needs for the duration
of the session.
The QoS paradigm may be summarized by
paraphrasing Date (1991) when he developed
Rule 0 for distributed processing. Rule 0
states that a distributed system should look
and behave exactly like a non-distributed
system. Rule 0 is a straightforward way of
saying that the middleware infrastructure
provides full transparency and QoS for all
remote system services. To design systems
that meet these requirements, a superior
form of middleware is required to handle
interoperability issues.
Table I summarizes the technical,
administrative and transmission issues of
both QoS and middleware. Within the QoS
technical column are the broader issues that
underlie transmissions, such as the behavior
of edge and core services as well as handling
of more complex traffic patterns. The QoS
Administrative column summarizes the
contractual relationship between client and
server, while QoS transmission deals with
transport and network layer issues (Adis,
1998).
The design task is to build QoS middleware
to increase its transparency, scalability and
adaptability to demands of real-time
applications that operate in a changing and
sometimes antagonistic environment. QoS
strategy is dependent on being able to use the
technical, administrative, and transmission
parameters found in Table I to:
.optimize the communication channels;
.develop dynamic techniques for
addressing and handling change and for
prioritizing tasks;
.monitor and manage objects, components,
and the ``end-to-end'' environment;
.track and maintain the QoS contract
established at run-time;
.reconfigure in real-time the mix of
components and middleware services.
When successful, these QoS middleware
parameters can meet the performance level
necessary to guarantee to a user that an
application, traveling across the network,
will have contracted services at a reasonable
cost, and with minimum impact on other
network requests.
Quality vs overhead
QoS middleware has the management tools to
arbitrate between network requirements and
network overhead. Figure 1 shows the direct
relationship between QoS and network
overhead. The more network guarantees,
reservations, and allocated throughput, the
more network overhead, as more resources
are directed towards monitoring, policing,
and managing services (Gray, 1998).
For instance, to provide the necessary
services for an application, there must be an
initial contract evaluation, which spells out
the timeframe for the request, and the worst
case scenario for acceptance. The worst case
scenario describes the least acceptable
bandwidth, the maximum delay or jitter, and
other inhibiting QoS factors. The last issue
that affects the contract is the adaptive
response of the middleware to out of bounds
performance. The administrative function
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[47]
Industrial Management &
Data Systems
103/1 [2003] 47-51
#MCB UP Limited
[ISSN 0263-5577]
[DOI 10.1108/02635570310456896]
Keywords
Service quality,
Information technology,
Management,
Telecommunications
Abstract
Quality of service (QoS)
middleware is a core technology
that will drive the next paradigm in
distributed computing. It underlies
how computer researchers are
addressing the technical demands
caused by the exponential growth
of Internet activity, the demand for
intensive computing in terms of
multimedia and distributed
applications, and the
unpredictability of constantly
changing Internet traffic patterns.
CORBA represents a class of
middleware that has incorporated
many QoS features.
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