Abstract

Abstract

Learning agents have to deal with the exploration-exploitation
dilemma. The choice between exploration and exploitation is very difficult in
dynamic systems; in particular in large scale ones such as economic systems.
Recent research shows that there is neither an optimal nor a unique solution for
this problem. In this paper, we propose an adaptive approach based on meta-rules
to adapt the choice between exploration and exploitation. This new adaptive approach relies on the variations of the performance of the agents. To validate the
approach, we apply it to economic systems and compare it to two adaptive methods: one local and one global. Herein, we adapt these two methods, which were
originally proposed by Wilson, to economic systems. Moreover, we compare different exploration strategies and focus on their influence on the performance of
the agents

Abstract

We are interested to study the state of the art of ontologies and to synthesize it. This paper makes a synthesis of definitions, languages, ontology classifications, ontological engineering, ontological platforms and application fields of ontologies. The objective of this study is to cover and synthesize the ontological concepts through the proposition of a whole of cartographies related to these concepts.

Abstract

To evaluate the impact of peer-to-peer (P2P) applications on traffic in wide area networks, we analyze measurements from a high speed IP backbone link carrying TCP traffic towards several ADSL areas. The first observations are that the prevalent part of traffic is due to P2P applications (almost 80% of total traffic) and that the usage of network becomes symmetric in the sense that customers are not only clients but also servers. This latter point is observed by the significant proportion of long flows mainly composed of ACK segments. When analyzing the bit rate created by long flows, it turns out that the TCP connections due to P2P applications have a rather small bit rate and that there is no evidence for long range dependence. These facts are intimately related to the way P2P protocols are running. We separately analyze signaling traffic and data traffic. It turns out that by adopting a suitable level of aggregation, global traffic can be described by means of usual tele-traffic models based on M/G/∞ queues with Weibullian service times.

Abstract

Measurements from an Internet backbone link carrying TCP traf
f
ic towards different ADSL areas are analyzed in this paper. For
traffic analysis, we adopt a flow-based approach and the popular
mice/elephants dichotomy. The originality of the experimental
data reported in this paper, when compared with previous mea
surements from very high speed backbone links, is in that com
mercial traffic comprises a significant percentage due to peer-to
peer applications. This kind of traffic exhibits some remarkable
properties in terms of mice, elephants and bit rates, which are
thoroughly described in this paper. Mice due to p2p protocols and
mice due to classical Internet applications such as HTTP, ftp, etc.
are analyzed separately. It turns out that by adopting a suitable
level of aggregation, global traffic can be described by means of
usual tele-traffic models based on M/G/∞ queues with Weibul
lian service times. The global bit rate can be approximated by the
superposition of Gaussian processes perturbed by a white noise
and does not exhibit long range dependence.

Abstract

By distinguishing long and short TCP flows, we address in this paper the problem of efficiently computing the characteristics of long flows. Instead of using time consuming off-line flow classification procedures, we investigate how flow characteristics could directly be inferred from traffic measurements by means of digital signal processing techniques. The proposed approach consists of classifying on the fly packets according to their size in order to construct two signals, one associated with short flows and the other with long flows. Since these two signals have intertwined spectral characteristics, we use a blind source separation technique in order to reconstruct the original spectral densities of short and long flow sources. The method is applied to a real traffic trace captured on a link of the France Telecom IP backbone network and proves efficient to recover the characteristics of long and short flows.

Abstract

Economic markets are complex systems. They are characterized by a large and dynamic population of firms. To deal with this complexity, we propose an adaptive multiagent system which models a set of firms in competition with each other within a shared market. The firms are represented by agents; each firm is represented by an adaptive agent. We show the advantages of adaptive agents to represent firms. Moreover, we underline the limits of the economic models which account for the firms only and ignore the organizational forms. We propose a new adaptive multiagent model that includes the organizational forms into the economic models. We simulate this model and discuss its advantages.

Abstract

Measurements from an Internet backbone link carrying TCP traffic towards different ADSL areas are analyzed. For traffic analysis, we adopt a flow based approach and the popular mice/elephants dichotomy, where mice refer to short traffic transfers and elephants to long transfers. The originality of the reported experimental data, when compared with previous measurements from very high speed backbone links, is that the commercial traffic includes a significant part generated by peer-to-peer applications. This kind of traffic exhibits some remarkable properties in terms of mice and elephants, as we describe. It turns out that by adopting a suitable level of aggregation, the bit rate of mice can be described by means of a Gaussian process. The bit rate of elephants is smoother than that of mice and can also be well approximated by a Gaussian process.