Catálogo de publicaciones - libros

We are sure that RFID system should be a widely used automatic identification system because of its various advantages and applications. However, many people know that invasion of privacy in RFID system is a still critical problem that makes it difficult to be used widely. Many works for solving this problem have focused on developing light-weight cryptographic modules inside of an RFID tag and building communication protocols with the reader or the back-end server. Another approach is use of proxy agents that control communications between the tag and the reader for protecting privacy. In this paper, we present an enhanced version of MARP scheme. We modified the original MARP scheme for reducing the probability of preventing attacker’s eavesdropping and for reducing the communication number of tags. And back-end servers can authenticate mobile agents more easily using public key cryptography in this scheme. Enhanced MARP scheme guarantees not only privacy protection but also forgery detection, and it only needs slight modification in the current tag hardware.

This work proposes a framework for the design and development of Ontology Agents oriented to manage Rule Base Fuzzy Cognitive Maps (RB-FCM). The approach takes into account the foundations of the Ontology Agents and the baseline of the Fuzzy Cognitive Maps depicted by Rule Bases. With these underlying elements, a specification of a conceptualization about the modeled domain is outcome. Moreover, a knowledge structure, composed by concepts and causal relationships that fit a Fuzzy Rule Base, is grown from. As a result, a semantic repository is stated by means of the Ontology Web Language (OWL). The management of the ontology is fulfilled by an Ontology Agent. This kind of agent takes over the services required to define and update the Ontology items. Also, the Ontology Agent achieves the tasks for answering the queries sent by a community of agents. This set of agents recreates a Multi-Agent System (MAS) that is deployed on the Internet by means of Web Services, where the system carries out causal inferences based on RB-FCM.

To acquire hidden and potentially useful information from context data, ubiquitous computing services began taking advantage of the reasoning capabilities inherent in inference engines. However, since a traditional approach to evaluating inference engines’ performance levels typically focuses on static information reasoning, specific evaluations of requirements that pertain to the ubiquitous computing environment have been largely neglected. Hence, this paper aims to propose an augmented evaluation framework for inference engines, and then examine how OWL-DL-based inference engines perform by applying them to realistic context-aware services. Six measurement criteria are proposed and measured, including scalability as data set gets large, responsiveness for users’ requests, and adaptability to frequent inference requests.

Resource management is one of the key research issues for multi-agent systems. Aside from increasing the system reliability, the load balancer is also able to schedule incoming tasks to the available machines. This paper introduces a load balancing strategy algorithm which can optimize the utilization of several different resources (CPU, memory, etc.) by migrating mobile agents and their tasks to the best alternative nodes. In the course of the research, a few scenarios were simulated and analyzed. In the paper the scenarios along with initial experiment results are presented.

A peer-to-peer (P2P) system consists of a number of decentralized distributed network nodes that are capable of sharing resources without centralized supervision. Many applications such as IP-phone, contents delivery network (CDN), distributed computing adopt P2P technology into their base communication systems. One of the most important functions in P2P system is locating resources, and it is generally hard to achieve due to the intrinsic nature of P2P, i.e. dynamic re-configuration of the network. In this paper, we propose an efficient resource locating method in pure P2P system based on multi-agents. The model of our system is a DHT base P2P system that consists of nodes with DHT (high performance nodes) and nodes without DHT (regular nodes). All the resources as well as resource information are managed by cooperative multi-agents. Migrating multi-agents are expected to reduce communication traffic in the network. Efficient migration is achieved through the clustering of nodes that makes correlated nodes in a group by the logical similarity. The numerical experiments through simulation have shown a significant reduction of generated messages.

In this paper, we propose a new approach to manage data storage and distribution in a data warehouse (DWH) environment. This approach deals with the dynamic data distribution of the DWH on a set of servers. The data distribution that we consider is different from the “classical” one which depends on the data use. The distribution in our approach consists in distributing data when the server reaches his storage capacity limit. This distribution assures the scalability and exploits the storage and processing resources available in the organization using the DWH. It is worth noting that our approach is based on a multi-agent model mixed with the scalability distribution proposed by the Scalable Distributed Data Structures.

The proposed multi-agent model is composed of stationary agent classes: Client, Dispatcher, Domain and Server, and a mobile agent class called Messenger. These agents collaborate and interact to achieve automatically the storage, the splitting (distribution), the redirection and the access operations on the distributed DWH.

We discuss the problem of semantic data integration in a highly-dynamic environment consisting of a community of peer-to-peer cooperating agents (partners). Peers decide when to join and when to leave the system, how to describe their local data, when to communicate and share their resources with partners. An agent issues queries to its partners (friends) which are able partly answer the query and then propagate the query to their partners along semantic paths existing in the system. Semantic paths are determined by schema mappings defined between partners. We propose a method for specifying schema mappings and to translate them to XQuery expressions. Mappings are represented by means of logical formulas. We also propose a declarative specification of semantic-driven communication in the system. The specification is made in a peer-oriented extension of Prolog.

The paper is based on FieldExchange – a computer system responsible for monitoring and supporting resource re-distribution decision making in BT’s Operational Resource Management units. This paper considers the problem of resource allocation in the service industries approached from an agent-based perspective. The problem is formulated as a centralized/distributed planning problem. The paper describes the context of this solution, the general model and solution and four specific implementations with results and discussion.

The simulation model adaptability to real network behavior is the key concept in wireless communications. In a cellular network, many procedures such as call admission, hand-off, etc take place simultaneously for every individual user. Every network procedure acts autonomously, interacts with the network environment (gathers information such as interference conditions), takes decisions (e.g. call establishment), etc. Although this is known in the literature, there is lack of suitable representations for such network procedures in the simulation systems proposed so far, thus compromising simulation model adaptability to real network behavior. To achieve such adaptability we herein propose to change the point of view in network procedure representation. Instead of viewing them as independent programming functions or even objects in a high level language, which are sequentially executed, due to their aforementioned properties it is proposed that such network procedures could be more efficiently modeled as agents. Considering this new approach, the agent cooperation and communication in terms of negotiation and agreement is a critical issue. In this paper we present a centralized cooperative multi-agent negotiation scheme applied to a multi-agent layered architecture for designing and simulating resource allocation in cellular communication systems, based on organizational modeling. Moreover, we show the way that the rules and implementation methods of agent negotiation affect the adaptation grade of simulation model to the real cellular network behavior.

Negotiation is an effective and popular decision-making and coordination behavior in inter-organizations systems, especially in construction supply chain (CSC) which is characterized with fragmentation, low efficiency and multiple partners. This research proposes a multi-agent based negotiation platform for improving the effectiveness and efficiency of cooperative decision-making in CSC adopting agent technology and regarding CSC as a typical multi-agent system. General structure of the agent based negotiation platform is designed, which includes two kinds of agent group: specialty agents and service agents. Since different members in CSC have different preferences on the decision attributes (such as cost, time, quality, safety and environment), a multi-attribute negotiation model is established by designing negotiation protocol and describing the negotiation process.