Showing papers by "Alberto Prieto published in 2009"

Statistical Characterization of Steady-State Visual Evoked Potentials and Their Use in Brain---Computer Interfaces

Abstract: Steady-state visual evoked potential (SSVEP)-based brain---computer interfaces (BCIs) use the spectral power of the potentials for classification as they can be voluntarily enhanced or diminished by the subject by means of selective attention. The features traditionally extracted from the EEG and used for BCIs have been characterized as a normal distribution, although some studies have shown recently that this normal distribution is not the most appropriate for SSVEPs. In this paper we attempt to characterize the power of SSVEPs as a random variable that follows Rayleigh and exponential distributions when the stimulus is attended and ignored, respectively. BCIs based on SSVEPs can improve the transfer-bit and successful-classification rates if this new model is used instead of the traditional one based on the normal distribution.

Adaptive real-time monitoring for large-scale networked systems

Abstract: The focus of this thesis is continuous real-time monitoring, which is essential for the realization of adaptive management systems in large-scale dynamic environments. Real-time monitoring provides the necessary input to the decision-making process of network management. We have developed, implemented, and evaluated a design for real-time continuous monitoring of global metrics with performance objectives, such as monitoring overhead and estimation accuracy. Global metrics describe the state of the system as a whole, in contrast to local metrics, such as device counters or local protocol states, which capture the state of a local entity. Global metrics are computed from local metrics using aggregation functions, such as SUM, AVERAGE and MAX. A key part in the design is a model for the distributed monitoring process that relates performance metrics to parameters that tune the behavior of a monitoring protocol. The model has been instrumental in designing a monitoring protocol that is controllable and achieves given performance objectives. Our design has proved to be effective in meeting performance objectives, efficient, adaptive to changes in the networking conditions, controllable along different performance dimensions, and scalable. We have implemented a prototype on a testbed of commercial routers, which proves the feasibility of the design, and, more generally, the feasibility of effective and efficient real-time monitoring in large network environments.

Controlling performance trade-offs in adaptive network monitoring

Abstract: A key requirement for autonomic (i.e., self-*) management systems is a short adaptation time to changes in the networking conditions. In this paper, we show that the adaptation time of a distributed monitoring protocol can be controlled. We show this for A-GAP, a protocol for continuous monitoring of global metrics with controllable accuracy. We demonstrate through simulations that, for the case of A-GAP, the choice of the topology of the aggregation tree controls the trade-off between adaptation time and protocol overhead in steady-state. Generally, allowing a larger adaptation time permits reducing the protocol overhead. Our results suggest that the adaptation time primarily depends on the height of the aggregation tree and that the protocol overhead is strongly influenced by the number of internal nodes. We outline how A-GAP can be extended to dynamically self-configure and to continuously adapt its configuration to changing conditions, in order to meet a set of performance objectives, including adaptation time, protocol overhead, and estimation accuracy.

A New Offloaded/Onloaded Network Interface for High Performance Communication

Abstract: The availability of multi-core processors and programmable NICs (Network Interface Cards), such as TOEs (TCP/IP Offloading Engines), provides new opportunities for designing efficient network interfaces to cope with the gap between the improvement rates of link bandwidths and microprocessor performance. This gap poses important challenges related with the high computational requirements associated to the traffic volumes and wider functionality that the network interface has to support. An opportunity to reach these goals comes from the exploitation of the parallelism in the communication path by distributing the protocol processing work across processors available in the computer, i.e. multi-core microprocessors and programmable NICs. Thus, alternatives such as offloading and onloading try to release host CPU cycles by this approach. Nevertheless, whereas onloading uses another general-purpose processor, either included in a multi-core microprocessor or in a symmetric multiprocessor (SMP), offloading takes advantage of processors in programmable network interface cards (NICs). Some experimental results demonstrate that the relative improvement on peak throughput offered by offloading and onloading depends on the rate of application workload to communication overhead, the message sizes, and on the characteristics of system architecture, more specifically the bandwidth of the buses and the way the NIC is connected to the system processor and memory. Thus, in this paper we propose a network interface that takes the advantages of both offloading and onloading approaches while avoids their respective drawbacks. The performance analyses done by using a full-system simulator, shows that, in the benchmarks and application used for the experiments, our hybrid interface improves the latency and bandwidth behavior of the onloading and offloading approaches.

Using UN/CEFACT'S Modelling Methodology (UMM) in e-Health Projects

Abstract: UN/CEFACT's Modelling Methodology (UMM) is a methodology created to capture the business requirements of inter-organizational business processes, regardless of the underlying technology. An example of how to apply UMM to an inter-enterprise e-health project is presented in this paper.

Adaptive Performance Management for SMS Systems

Abstract: We present a design for performance management of SMS systems. The design takes as input the administrator's performance objectives, which can be adjusted at run-time. Based on these objectives, the design takes the necessary actions to achieve them and it dynamically adapts to changing networking conditions. It does so by periodically solving a linear optimization problem that computes a new configuration for the SMS system. We have evaluated the design through extensive simulations in various scenarios using traces from a production SMS system. It has proved effective in achieving the administrator's performance objectives, and efficient in terms of computational cost. Our experiments also show that the design is adaptive, i.e., it effectively adapts the systems's configuration to changes in the networking conditions, in order to continuously meet the performance objectives. Finally, the feasibility of our design is proved through the development of a prototype on a commercial SMS platform.

Multiple AM Modulated Visual Stimuli in Brain-Computer Interface

Abstract: Steady-state visual evoked potential (SSVEP) based Brain-computer interfaces (BCIs) use the spectral power at the flickering frequencies of the stimuli as the feature for classification in an Attend/Ignore multi-class paradigm. The performance of a BCI based on this principle increases with the number of stimuli. However the number of the corresponding flickering frequencies is limited due to several factors. Besides the frequency response of SSVEPs is not uniform for the full range of frequencies and varies among individuals, being difficult to establish accurate decision boundaries. In this paper we propose a new technique to overcome this limitation based on the AM modulation of the flickering stimuli that reuses the same modulating frequencies with different phase.

Improving the Performance of Bandwidth-Demanding Applications by a Distributed Network Interface

Abstract: In the last years, the market is demanding (scientific, multimedia, real-time, etc.) applications with high bandwidth requirements. To support this, the bandwidth of the network links has increased to reach multiple gigabit per second. Nevertheless, taking advantage of multigigabit per second links requires a lot of processor cycles for communication tasks, diminishing the processor cyles that remains available for the application. Actual multiprocessor and multicore architectures as well as programmable NICs (Network Interface Cards) provide new opportunities to exploit the parallelism, distributing the communication overhead across the processors available in the node. We have designed a network interface that takes advantage of the different processors available in the node. In this paper, the advantages of this optimized network interface are shown by analyzing the performance of a web server application.

Independent Component Analysis Aided Diagnosis of Cuban Spino Cerebellar Ataxia 2

Abstract: Precedent studies have found abnormalities in the oculomotor system in patients with severe SCA2 form of autosomal dominant cerebellar ataxias (ADCA), including the latency, peak velocity, and deviation in saccadic movements, and causing changes in the morphology of the patient response waveform. This different response suggests a higher degree of statistic independence in sick patients when compared to healthy individuals regarding the patient response to the visual saccadic stimulus. We processed electro-oculogram records of six patient diagnosed with severe ataxia SCA2 and six healthy subjects used as control, employing independent component analysis (ICA), significant differences have been found in the statistical independence of the person response with the stimulus for 60° saccadic tests.