Linear complete differential resultants and the implicitization of linear DPPEs

The linear complete differential resultant of a finite set of linear ordinary differential polynomials is defined. We study the computation by linear complete differential resultants of the implicit equation of a system of n$n$ linear differential polynomial parametric equations in n−1$n-1$ differential parameters. We give necessary conditions to ensure properness of the system of differential polynomial parametric equations.     

Real-time hierarchical stereo Visual SLAM in large-scale environments

In this paper we present a new real-time hierarchical (topological/metric) Visual SLAM system focusing on the localization of a vehicle in large-scale outdoor urban environments. It is exclusively based on the visual information provided by a cheap wide-angle stereo camera. Our approach divides the whole map into local sub-maps identified by the so-called fingerprints (vehicle poses). At the sub-map level (low level SLAM), 3D sequential mapping of natural landmarks and the robot location/orientation are obtained using a top-down Bayesian method to model the dynamic behavior. A higher topological level (high level SLAM) based on fingerprints has been added to reduce the global accumulated drift, keeping real-time constraints. Using this hierarchical strategy, we keep the local consistency of the metric sub-maps, by mean of the EKF, and global consistency by using the topological map and the MultiLevel Relaxation (MLR) algorithm. Some experimental results for different large-scale outdoor environments are presented, showing an almost constant processing time.     

A methodology to specify three-dimensional interaction using Petri Nets

This work presents a methodology to formally model and to build three-dimensional interaction tasks in virtual environments using three different tools: Petri Nets, the Interaction Technique Decomposition taxonomy, and Object-Oriented techniques. User operations in the virtual environment are represented as Petri Net nodes; these nodes, when linked, represent the interaction process stages. In our methodology, places represent all the states an application can reach, transitions define the conditions to start an action, and tokens embody the data manipulated by the application. As a result of this modeling process we automatically generate the core of the application's source code. We also use a Petri Net execution library to run the application code. In order to facilitate the application modeling, we have adapted Dia, a well-known graphical diagram editor, to support Petri Nets creation and code generation. The integration of these approaches results in a modular application, based on Petri Nets formalism that allows for the specification of an interaction task and for the reuse of developed blocks in new virtual environment projects.     

Providing EAP-based Kerberos pre-authentication and advanced authorization for network federations

Kerberos is a well-known standard protocol which is becoming one of the most widely deployed for authentication and key distribution in application services. However, whereas service providers use the protocol to control their own subscribers, they do not widely deploy Kerberos infrastructures to handle subscribers coming from foreign domains, as happens in network federations. Instead, the deployment of Authentication, Authorization and Accounting (AAA) infrastructures has been preferred for that operation. Thus, the lack of a correct integration between these infrastructures and Kerberos limits the service access only to service provider's subscribers. To avoid this limitation, we design an architecture which integrates a Kerberos pre-authentication mechanism, based on the use of the Extensible Authentication Protocol (EAP), and advanced authorization, based on the standards SAML and XACML, to link the end user authentication and authorization performed through an AAA infrastructure with the delivery of Kerberos tickets in the service provider's domain. We detail the interfaces, protocols, operation and extensions required for our solution. Moreover, we discuss important aspects such as the implications on existing standards.     

Introducing dynamic diversity into a discrete particle swarm optimization

Particle swarm optimization (PSO) is an evolutionary metaheuristic inspired by the flocking behaviour of birds, which has successfully been used to solve several kinds of problems, although there are few studies aimed at solving discrete optimization problems. One disadvantage of PSO is the risk of a premature search convergence. To prevent this, we propose to introduce diversity into a discrete PSO by adding a random velocity. The degree of the introduced diversity is not static (i.e. preset before running PSO) but instead changes dynamically according to the heterogeneity of the population (i.e. if the search has converged or not). We solve the response time variability problem (RTVP) to test these two new ideas. The RTVP is an NP-hard combinatorial scheduling problem that has recently appeared in the literature. It occurs whenever products, clients or jobs need to be sequenced in such a way that the variability in the time between the instants at which they receive the necessary resources is minimized. The most efficient algorithm for solving non-small instances of the RTVP published to date is a classical PSO algorithm, referred to by the authors as PSO-M1F. In this paper, we propose 10 discrete PSO algorithms for solving the RTVP: one based on the ideas described above (PSO  -_c3dyn$c_3\text{<italic>dyn</italic>}$) and nine based on strategies proposed in the literature and adapted for solving a discrete optimization problem such as the RTVP. We compare all 11 PSO algorithms and the computational experiment shows that, on average, the best results obtained are due to our proposal of dynamic control mechanism for introducing diversity.     

Computational intelligence tools for next generation quality of service management

In this paper we explore the interest of computational intelligence tools in the management of heterogeneous communication networks, specifically to predict congestion, failures and other anomalies in the network that may eventually lead to degradation of the quality of offered services. We show two different applications based on neural and neuro-fuzzy systems for quality of service (QoS) management in next generation networks for voice and video service over heterogeneous Internet protocol (V2oIP) services. The two examples explained in this paper attempt to predict the communication network resources for new incoming calls, and visualizing the QoS of a communication network by means of self-organizing maps.     

Traffic analysis and synthetic models of second life

Virtual Worlds (VW), such as Massive Multiplayer Online Social Games, have been gaining increasing attention in the last few years, mainly due to the new way users interact with them. However, little effort has been devoted to understand their traffic profile and the implications to the traffic management area. With the current growing rate of VWs’ usage, their traffic demand could eventually impose a significant burden on the operation of a typical Internet Service Provider (ISP) network. In this paper, we seek to understand the traffic behavior of an increasingly popular VW application, namely Second Life (SL), from both the connection and network level perspectives. We also show results of a traffic analysis of a SL client, when an avatar performs different actions in the VW, at different places and under different network conditions. Our results show that SL makes intensive use of network resources (mostly bandwidth), since the capacity needed for having a full SL experience (listening to live music) may reach 500 kbps. We then extend the traffic analysis work on SL by providing analytical models for its traffic profile. We aim at helping the network management and planning area to estimate the impact of an intense use of such VW on access links or core networks. Such synthetic models are also useful to the networking research community for the use in network simulations.     

Maintaining strong mutual visibility of an evader moving over the reduced visibility graph

In this paper, we address the problem of determining whether a mobile robot, called the pursuer, is able to maintain strong mutual visibility (a visibility notion between regions over a convex partition of the environment) of an antagonist agent, called the evader. We frame the problem as a non cooperative game. We consider the case in which the pursuer and the evader move at bounded speed, traveling in a known polygonal environment with or without holes, and in which there are no restrictions as to the distance that might separate the agents. Unlike our previous efforts (Murrieta-Cid et al. in Int J Robot Res 26:233–253, 2007), we give special attention to the combinatorial problem that arises when searching for a solution through visiting several locations in an environment with obstacles. In this paper we take a step further, namely, we assume an antagonistic evader who moves continuously and unpredictably, but with a constraint over its set of admissible motion policies, as the evader moves in the shortest-path roadmap, also called the reduced visibility graph (RVG). The pursuer does not know which among the possible paths over the RVG the evader will choose, but the pursuer is free to move within all the environment. We provide a constructive method to solve the decision problem of determining whether or not the pursuer is able to maintain strong mutual visibility of the evader. This method is based on an algorithm that computes the safe areas (areas that keep evader surveillance) at all times. We prove decidability of this problem, and provide a complexity measure to this evader surveillance game; both contributions hold for any general polygonal environment that might or not contain holes. All our algorithms have been implemented and we show simulation results.     

Elastic Resource Allocation Algorithms for Collaboration Applications

Cloud technologies can provide elasticity to real-time audio and video (A/V) collaboration applications. However, cloud-based collaboration solutions generally operate on a best-effort basis, with neither delivery nor quality guarantees, and high-quality business focused solutions rely on dedicated infrastructure and hardware-based components. This article describes our 2-year of research in the EMD project, which targets to migrate a hardware-based and business focused A/V collaboration solution to a software-based platform hosted in the cloud, providing higher levels of elasticity and reliability. Our focus during this period was an educational collaboration scenario with teachers and students (locally present in the classroom or remotely following the classes). A model of collaboration streaming (e.g. network topology, codecs, stream, streaming workflow, software components) is defined as base for software deployment and preemptive VM allocation techniques. These heuristics are evaluated using a version of the CloudSim simulator extended to generate and simulate realistic collaboration scenarios, to manage network congestion and to monitor a.o. cost and session delay metrics. Our results show that the algorithms reduce costs when compared to previously designed approaches, having an effectiveness of 99% in meeting A/V collaboration setup deadlines, which is a stringent requirement for this collaboration application.