Design and evaluation of high-performance packet switching schemes

The design of high-performance packet switches is essential to efficiently handle the exponential growth of data traffic in the next generation Internet. Shared-memory-based packet switches are known to provide the best possible delay-throughput performance and the lowest packet-loss rate compared with packet switches using other buffering strategies. However, scalability of shared-memory-based switching systems has been restricted by high memory bandwidth requirements, segregation of memory space and centralized control of switching functions that causes the switch performance to degrade as a shared-memory switch is grown in size. The new class of sliding-window based packet switches are known to overcome these problems associated with shared-memory switches. This thesis presents different schemes proposed earlier by Dr. Kumar for use in the sliding-window switch to allocate self-routing parameters. Comparative performance of these schemes have been evaluated in this thesis. The results show the scalability of the switch that can be achieved with different parameter assignment schemes. It is shown that not all assignment schemes have same performance. With appropriate assignment scheme, it is possible to achieve very high throughput-performance and switch size for sliding-window switches

Dynamic Loop Scheduling Using MPI Passive-Target Remote Memory Access

Scientific applications often contain large computationally-intensive parallel loops. Loop scheduling techniques aim to achieve load balanced executions of such applications. For distributed-memory systems, existing dynamic loop scheduling (DLS) libraries are typically MPI-based, and employ a master-worker execution model to assign variably-sized chunks of loop iterations. The master-worker execution model may adversely impact performance due to the master-level contention. This work proposes a distributed chunk-calculation approach that does not require the master-worker execution scheme. Moreover, it considers the novel features in the latest MPI standards, such as passive-target remote memory access, shared-memory window creation, and atomic read-modify-write operations. To evaluate the proposed approach, five well-known DLS techniques, two applications, and two heterogeneous hardware setups have been considered. The DLS techniques implemented using the proposed approach outperformed their counterparts implemented using the traditional master-worker execution model

Electron Bernstein waves emission in the TJ-II Stellarator

Taking advantage of the electron Bernstein waves heating (EBWH) system of the TJ-II stellarator, an electron Bernstein emission (EBE) diagnostic was installed. Its purpose is to investigate the B-X-O radiation properties in the zone where optimum theoretical EBW coupling is predicted. An internal movable mirror shared by both systems allows us to collect the EBE radiation along the same line of sight that is used for EBW heating. The theoretical EBE has been calculated for different orientations of the internal mirror using the TRUBA code as ray tracer. A comparison with experimental data obtained in NBI discharges is carried out. The results provide a valuable information regarding the experimental O-X mode conversion window expected in the EBW heating experiments. Furthermore, the characterization of the radiation polarization shows evidence of the underlying B-X-O conversion process.Comment: 21 pages, 14 figure

Process windows

We describe a method for formally representing the behaviour of complex processes by process windows. Each window covers a part of the system behaviour, i.e. a part of the underlying transition system, and is easier to understand and analyse than the complete transition system. Process windows can overlap and have shared states and transitions so that the complete system behaviour is the union of window behaviours. We demonstrate the advantage of such representations when dealing with complex system behaviours, and discuss potential applications in circuit design and process mining. As a motivational example we consider the problem of covering transition systems by marked graphs, or more generally choicefree Petri nets. The obtained windows correspond to choice-free behavioural scenarios of the system, wherein one window can take over, or wake up, after another window has become inactive. The corresponding wake-up conditions and wake-up markings can be derived automatically.Peer ReviewedPostprint (author's final draft

Generalized feedback detection for spatial multiplexing multi-antenna systems

We present a unified detection framework for spatial multiplexing multiple-input multiple-output (MIMO) systems by generalizing Heller’s classical feedback decoding algorithm for convolutional codes. The resulting generalized feedback detector (GFD) is characterized by three parameters: window size, step size and branch factor. Many existing MIMO detectors are turned out to be special cases of the GFD. Moreover, different parameter choices can provide various performance-complexity tradeoffs. The connection between MIMO detectors and tree search algorithms is also established. To reduce redundant computations in the GFD, a shared computation technique is proposed by using a tree data structure. Using a union bound based analysis of the symbol error rates, the diversity order and signal-to-noise ratio (SNR) gain are derived analytically as functions of the three parameters; for example, the diversity order of the GFD varies between 1 and N. The complexity of the GFD varies between those of the maximum-likelihood (ML) detector and the zero-forcing decision feedback detector (ZFDFD). Extensive computer simulation results are also provided

Monitoring Shared memory: A Toolset Prototype for the INFORMIX OnLine Administrator

The Monitor Program was developed to assist system administrators for the INFORMIX OnLine Database Server with their evaluation of shared memory components used on their system. Using the Open Software Foundation (OSF)/Motif Widget set for Xt Intrinsics on the X Window System, this program creates scaled dials and pop-up windows to display system information at regular intervals. The program is surprisingly simple to operate and is general enough that with just a few modifications, it can be used to monitor any system information, not just shared memory information for OnLine. This program marks a new way to look at systems analysis, and could be the building block of many powerful programs of the future

Risk Prediction of a Multiple Sclerosis Diagnosis

Multiple sclerosis (MS) is a chronic autoimmune disease that affects the central nervous system. The progression and severity of MS varies by individual, but it is generally a disabling disease. Although medications have been developed to slow the disease progression and help manage symptoms, MS research has yet to result in a cure. Early diagnosis and treatment of the disease have been shown to be effective at slowing the development of disabilities. However, early MS diagnosis is difficult because symptoms are intermittent and shared with other diseases. Thus most previous works have focused on uncovering the risk factors associated with MS and predicting the progression of disease after a diagnosis rather than disease prediction. This paper investigates the use of data available in electronic medical records (EMRs) to create a risk prediction model; thereby helping clinicians perform the difficult task of diagnosing an MS patient. Our results demonstrate that even given a limited time window of patient data, one can achieve reasonable classification with an area under the receiver operating characteristic curve of 0.724. By restricting our features to common EMR components, the developed models also generalize to other healthcare systems

Analysis and operational challenges of dynamic ride sharing demand responsive transportation models

There is a wide body of evidence that suggests sustainable mobility is not only a technological question, but that automotive technology will be a part of the solution in becoming a necessary albeit insufficient condition. Sufficiency is emerging as a paradigm shift from car ownership to vehicle usage, which is a consequence of socio-economic changes. Information and Communication Technologies (ICT) now make it possible for a user to access a mobility service to go anywhere at any time. Among the many emerging mobility services, Multiple Passenger Ridesharing and its variants look the most promising. However, challenges arise in implementing these systems while accounting specifically for time dependencies and time windows that reflect users’ needs, specifically in terms of real-time fleet dispatching and dynamic route calculation. On the other hand, we must consider the feasibility and impact analysis of the many factors influencing the behavior of the system – as, for example, service demand, the size of the service fleet, the capacity of the shared vehicles and whether the time window requirements are soft or tight. This paper analyzes - a Decision Support System that computes solutions with ad hoc heuristics applied to variants of Pick Up and Delivery Problems with Time Windows, as well as to Feasibility and Profitability criteria rooted in Dynamic Insertion Heuristics. To evaluate the applications, a Simulation Framework is proposed. It is based on a microscopic simulation model that emulates real-time traffic conditions and a real traffic information system. It also interacts with the Decision Support System by feeding it with the required data for making decisions in the simulation that emulate the behavior of the shared fleet. The proposed simulation framework has been implemented in a model of Barcelona’s Central Business District. The obtained results prove the potential feasibility of the mobility concept.Postprint (published version

Implicit sequence learning and working memory: correlated or complicated?

The relationship between implicit/incidental sequence learning and working memory motivated a series of research because it is plausible that higher working memory capacity opens a “larger window” to a sequence, allowing thereby the sequence learning process to be easier. Although the majority of studies found no relationship between implicit sequence learning and working memory capacity, in the past few years several studies have tried to demonstrate the shared or partly shared brain networks underlying these two systems. In order to help the interpretation of these and future results, in this mini-review we suggest the following factors to be taken into consideration before testing the relationship between sequence learning and working memory: 1) the explicitness of the sequence; 2) the method of measuring working memory capacity; 3) online and offline stages of sequence learning; and 4) general skill- and sequence-specific learning