Approximate performability and dependability analysis using generalized stochastic Petri Nets

Since current day fault-tolerant and distributed computer and communication systems tend to be large and complex, their corresponding performability models will suffer from the same characteristics. Therefore, calculating performability measures from these models is a difficult and time-consuming task.\ud \ud To alleviate the largeness and complexity problem to some extent we use generalized stochastic Petri nets to describe to models and to automatically generate the underlying Markov reward models. Still however, many models cannot be solved with the current numerical techniques, although they are conveniently and often compactly described.\ud \ud In this paper we discuss two heuristic state space truncation techniques that allow us to obtain very good approximations for the steady-state performability while only assessing a few percent of the states of the untruncated model. For a class of reversible models we derive explicit lower and upper bounds on the exact steady-state performability. For a much wider class of models a truncation theorem exists that allows one to obtain bounds for the error made in the truncation. We discuss this theorem in the context of approximate performability models and comment on its applicability. For all the proposed truncation techniques we present examples showing their usefulness

An Optimal Single-Path Routing Algorithm in the Datacenter Network DPillar

DPillar has recently been proposed as a server-centric datacenter network and is combinatorially related to (but distinct from) the well-known wrapped butterfly network. We explain the relationship between DPillar and the wrapped butterfly network before proving that the underlying graph of DPillar is a Cayley graph; hence, the datacenter network DPillar is node-symmetric. We use this symmetry property to establish a single-path routing algorithm for DPillar that computes a shortest path and has time complexity O(k), where k parameterizes the dimension of DPillar (we refer to the number of ports in its switches as n). Our analysis also enables us to calculate the diameter of DPillar exactly. Moreover, our algorithm is trivial to implement, being essentially a conditional clause of numeric tests, and improves significantly upon a routing algorithm earlier employed for DPillar. Furthermore, we provide empirical data in order to demonstrate this improvement. In particular, we empirically show that our routing algorithm improves the average length of paths found, the aggregate bottleneck throughput, and the communication latency. A secondary, yet important, effect of our work is that it emphasises that datacenter networks are amenable to a closer combinatorial scrutiny that can significantly improve their computational efficiency and performance

Fault localization in service-based systems hosted in mobile ad hoc networks

Fault localization in general refers to a technique for identifying the likely root causes of failures observed in systems formed from components. Fault localization in systems deployed on mobile ad hoc networks (MANETs) is a particularly challenging task because those systems are subject to a wider variety and higher incidence of faults than those deployed in fixed networks, the resources available to track fault symptoms are severely limited, and many of the sources of faults in MANETs are by their nature transient. We present a suite of three methods, each responsible for part of the overall task of localizing the faults occurring in service-based systems hosted on MANETs. First, we describe a dependence discovery method, designed specifically for this environment, yielding dynamic snapshots of dependence relationships discovered through decentralized observations of service interactions. Next, we present a method for localizing the faults occurring in service-based systems hosted on MANETs. We employ both Bayesian and timing-based reasoning techniques to analyze the dependence data produced by the dependence discovery method in the context of a specific fault propagation model, deriving a ranked list of candidate fault locations. In the third method, we present an epidemic protocol designed for transferring the dependence and symptom data between nodes of MANET networks with low connectivity. The protocol creates network wide synchronization overlay and transfers the data over intermediate nodes in periodic synchronization cycles. We introduce a new tool for simulation of service-based systems hosted on MANETs and use the tool for evaluation of several operational aspects of the methods. Next, we present implementation of the methods in Java EE and use emulation environment to evaluate the methods. We present the results of an extensive set of experiments exploring a wide range of operational conditions to evaluate the accuracy and performance of our methods.Open Acces

A design flow for performance planning : new paradigms for iteration free synthesis

In conventional design, higher levels of synthesis produce a netlist, from which layout synthesis builds a mask specification for manufacturing. Timing anal ysis is built into a feedback loop to detect timing violations which are then used to update specifications to synthesis. Such iteration is undesirable, and for very high performance designs, infeasible. The problem is likely to become much worse with future generations of technology. To achieve a non-iterative design flow, early synthesis stages should use wire planning to distribute delays over the functional elements and interconnect, and layout synthesis should use its degrees of freedom to realize those delays

Dynamic construction of back-propagation artificial neural networks.

by Korris Fu-lai Chung.Thesis (M.Phil.) -- Chinese University of Hong Kong, 1991.Bibliography: leaves R-1 - R-5.LIST OF FIGURES --- p.viLIST OF TABLES --- p.viiiChapter 1 --- INTRODUCTIONChapter 1.1 --- Recent Resurgence of Artificial Neural Networks --- p.1-1Chapter 1.2 --- A Design Problem in Applying Back-Propagation Networks --- p.1-4Chapter 1.3 --- Related Works --- p.1-6Chapter 1.4 --- Objective of the Research --- p.1-8Chapter 1.5 --- Thesis Organization --- p.1-9Chapter 2 --- MULTILAYER FEEDFORWARD NETWORKS (MFNs) AND BACK-PRO- PAGATION (BP) LEARNING ALGORITHMChapter 2.1 --- Introduction --- p.2-1Chapter 2.2 --- From Perceptrons to MFNs --- p.2-2Chapter 2.3 --- From Delta Rule to BP Algorithm --- p.2-6Chapter 2.4 --- A Variant of BP Algorithm --- p.2-12Chapter 3 --- INTERPRETATIONS AND PROPERTIES OF BP NETWORKSChapter 3.1 --- Introduction --- p.3-1Chapter 3.2 --- A Pattern Classification View on BP Networks --- p.3-2Chapter 3.2.1 --- Pattern Space Interpretation of BP Networks --- p.3-2Chapter 3.2.2 --- Weight Space Interpretation of BP Networks --- p.3-3Chapter 3.3 --- Local Minimum --- p.3-5Chapter 3.4 --- Generalization --- p.3-6Chapter 4 --- GROWTH OF BP NETWORKSChapter 4.1 --- Introduction --- p.4-1Chapter 4.2 --- Problem Formulation --- p.4-1Chapter 4.3 --- Learning an Additional Pattern --- p.4-2Chapter 4.4 --- A Progressive Training Algorithm --- p.4-4Chapter 4.5 --- Experimental Results and Performance Analysis --- p.4-7Chapter 4.6 --- Concluding Remarks --- p.4-16Chapter 5 --- PRUNING OF BP NETWORKSChapter 5.1 --- Introduction --- p.5-1Chapter 5.2 --- Characteristics of Hidden Nodes in Oversized Networks --- p.5-2Chapter 5.2.1 --- Observations from an Empirical Study --- p.5-2Chapter 5.2.2 --- Four Categories of Excessive Nodes --- p.5-3Chapter 5.2.3 --- Why are they excessive ？ --- p.5-6Chapter 5.3 --- Pruning of Excessive Nodes --- p.5-9Chapter 5.4 --- Experimental Results and Performance Analysis --- p.5-13Chapter 5.5 --- Concluding Remarks --- p.5-19Chapter 6 --- DYNAMIC CONSTRUCTION OF BP NETWORKSChapter 6.1 --- A Hybrid Approach --- p.6-1Chapter 6.2 --- Experimental Results and Performance Analysis --- p.6-2Chapter 6.3 --- Concluding Remarks --- p.6-7Chapter 7 --- CONCLUSIONS --- p.7-1Chapter 7.1 --- Contributions --- p.7-1Chapter 7.2 --- Limitations and Suggestions for Further Research --- p.7-2REFERENCES --- p.R-lAPPENDIXChapter A.1 --- A Handwriting Numeral Recognition Experiment: Feature Extraction Technique and Sampling Process --- p.A-1Chapter A.2 --- Determining the distance d= δ2/2r in Lemma 1 --- p.A-

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

Characterisation of a reconfigurable free space optical interconnect system for parallel computing applications and experimental validation using rapid prototyping technology

Free-space optical interconnects (FSOIs) are widely seen as a potential solution to present and future bandwidth bottlenecks for parallel processing applications. This thesis will be focused on the study of a particular FSOI system called Optical Highway (OH). The OH is a polarised beam routing system which uses Polarising Beam Splitters and Liquid Crystals (PBS/LC) assemblies to perform reconfigurable interconnection networks. The properties of the OH make it suitable for implementing different passive static networks. A technology known as Rapid Prototyping (RP) will be employed for the first time in order to create optomechanical structures at low cost and low production times. Off-theshelf optical components will also be characterised in order to implement the OH. Additionally, properties such as reconfigurability, scalability, tolerance to misalignment and polarisation losses will be analysed. The OH will be modelled at three levels: node, optical stage and architecture. Different designs will be proposed and a particular architecture, Optimised Cut-Through Ring (OCTR), will be experimentally implemented. Finally, based on this architecture, a new set of properties will be defined in order to optimise the efficiency of the optical channels

Innovative Algorithms and Evaluation Methods for Biological Motif Finding

Biological motifs are defined as overly recurring sub-patterns in biological systems. Sequence motifs and network motifs are the examples of biological motifs. Due to the wide range of applications, many algorithms and computational tools have been developed for efficient search for biological motifs. Therefore, there are more computationally derived motifs than experimentally validated motifs, and how to validate the biological significance of the ‘candidate motifs’ becomes an important question. Some of sequence motifs are verified by their structural similarities or their functional roles in DNA or protein sequences, and stored in databases. However, biological role of network motifs is still invalidated and currently no databases exist for this purpose. In this thesis, we focus not only on the computational efficiency but also on the biological meanings of the motifs. We provide an efficient way to incorporate biological information with clustering analysis methods: For example, a sparse nonnegative matrix factorization (SNMF) method is used with Chou-Fasman parameters for the protein motif finding. Biological network motifs are searched by various clustering algorithms with Gene ontology (GO) information. Experimental results show that the algorithms perform better than existing algorithms by producing a larger number of high-quality of biological motifs. In addition, we apply biological network motifs for the discovery of essential proteins. Essential proteins are defined as a minimum set of proteins which are vital for development to a fertile adult and in a cellular life in an organism. We design a new centrality algorithm with biological network motifs, named MCGO, and score proteins in a protein-protein interaction (PPI) network to find essential proteins. MCGO is also combined with other centrality measures to predict essential proteins using machine learning techniques. We have three contributions to the study of biological motifs through this thesis; 1) Clustering analysis is efficiently used in this work and biological information is easily integrated with the analysis; 2) We focus more on the biological meanings of motifs by adding biological knowledge in the algorithms and by suggesting biologically related evaluation methods. 3) Biological network motifs are successfully applied to a practical application of prediction of essential proteins