Abstract of the thesis proposal
The term “quality”
as it is commonly understood in the context of QoS is “something”
by which a user of the service (in a very large meaning) will judge
how good the service is.
Today, a lot of
different services from many distinct application areas ask for
some side needs, sometimes preferable to provide, but sometimes
strictly connected to the service itself. Consider, for example, a
streaming video transmission on a network: surely it is important
that the data-packet with a given video-frame arrives at
destination, but it is also important, at the same time, that the
packet arrives within precise time bounds, otherwise it would be
useless to reproduce it.
fields of this framework can be represented by i) Networks
and principally Constraint-Based Routing, ii) Web
services, for the negotiation of Service Level Agreements, and
iii) Trust Management and trust inference decision However
the application areas are not exclusively restricted to these three
classes: think for example to an extension concerning the QoS
management for Workflows.
Examples of QoS
metrics for the network links can be the bandwidth, delay, jitter
the number of hops, probability of packet loss, for Web Services
can be the cost or the availability, and for Trust Management, the
trust decision depends on the chosen trust metric.
Our wish is to
model the entities that ask and provide the resources connected to
services, and the negotiation interactions among them, for example
by using Soft Concurrent Constraint Programming.
For this reason,
we reckon that the use of Soft Constraints as the fundamentals of
our formal framework, could be promising a decision. As a matter of
fact, we think that the c-semiring is a general structure that can
be perfectly instantiated to represent and model the composition of
most of the QoS metrics. This feature provide to us all the
expressiveness and the flexibility that a framework needs to be
adapted to many application fields, while classic crisp constraint
could show evident limitations.
negotiation of quality could be slightly over-constrained, since
the requests of the client/consumer could be not fully satisfiable
(by the service provider) at the present moment, because of other
pending requests; on the other hand, the best possible solution,
that gets closer to the consumer needs, can however be found,
proposed and estimated by the potential client.
We are currently
planning to enhance the QoS model, by including all its possible
features and by finally translating the QoS satisfaction (and/or
optimization) problem in a corresponding Soft Constraint
At last, we want
to describe Shortest Path and Steiner Tree problems with Soft
Constraint Logic Programming (i.e. in a declarative fashion), in
order to model unicast and multicast QoS routing.