Parallel processing over a peer-to-peer network : constructing the poor man’s supercomputer

The aggregation of typical home computers through a peer-to-peer (P2P) framework over the Internet would yield a virtual supercomputer of unmatched processing power, 95% of which is presently being left unutilized. However, the global community appears to be still hesitant at tapping into the well of unharnessed potential offered by exploiting distributed computing. Reasons include the lack of personal incentive for participants, and the high degree of expertise required from application developers. Our vision is to tackle the aforementioned obstacles by building a P2P system capable of deploying user-defined tasks onto the network for distributed execution. Users would only be expected to write standard concurrent code accessing our application programming interface, and may rely on the system to transparently provide for optimal task distribution, process migration, message delivery, global state, fault tolerance, and recovery. Strong mobility during process migration is achieved by pre-processing the source code. Our results indicate that near-linear efficiencies – approximately 94% ± 2% of the optimal – may be obtained for adequately coarse-grained applications, even when deployed on a heterogeneous net- work.peer-reviewe

Fast user-level inter-thread communication, synchronisation

This project concerns the design and implementation of user-level inter-thread synchronisation and communication algorithms. A number of these algorithms have been implemented on the SMASH user-level thread scheduler for symmetric multiprocessors and multicore processors. All inter-thread communication primitives considered have two implementations: the lock-based implementation and the lock-free implementation. The performance of concurrent programs using these user-level primitives are measured and analyzed against the performance of programs using kernel-level inter-thread communication primitives. Besides, the differences between the lock- based implementations and lock-free implementations are also analyzed.peer-reviewe

A software development framework for hardware centric applications: an architectural perspective

Throughout the history of Software Engineering, software development has been looked at from various perspectives, in terms of: usability, suitability for proposed problem, speed of development, relevance to real world scenarios, as well as in terms of the hardware that it needs to manifest itself in the real world. This paper delves deeper into the aspect of the actual core concept in software engineering: that of mapping software onto hardware[1], focused specifically on Hardware Centric systems (HCS), (systems where the hardware dictates to an influential level, the actual nature of the software); examining the various frameworks and concepts that exist for displaying this mapping from an architecture point of view, so as to establish if there is a need for a more complete and/or effective framework. It also proposes a roadmap proposal for a base architecture framework for the development of Hardware Centric applications, which will then be employed to determine if a suitable framework already exists.peer-reviewe

Information driven SDLC concepts

Although software engineering has matured greatly over the years, a large number of ICT projects continue to fail. Studies continue to identify non-technical issues such as poor communication, shifting requirements and poor executive involvement as the main causes of these failures. In a previous paper, the authors identified such causes and posed the question as to why currently available software development life cycles fall short of dealing with them. They also proposed the development of an information driven software development life cycle. In this paper, the concept of an information driven SDLC is explored further and a number of concepts are discussed in this regard.peer-reviewe

Using hidden Markov models in credit card transaction fraud detection

In this paper we shall propose a credit card transaction fraud detection framework which uses Hidden Markov Models, a well established technology that has not as yet been tested in this area and through which we aim to address the limitations posed by currently used technologies. Hidden Markov Models have for many years been effectively implemented in other similar areas. The flexibility offered by these models together with the similarity in concepts between Automatic Speech Recognition and credit card fraud detection has instigated the idea of testing the usefulness of these models in our area of research. The study performed in this project investigated the utilisation of Hidden Markov Models by means of proposing a number of different frameworks, which frameworks are supported through the use of clustering and profiling mechanisms. The profiling mechanisms are used in order to build Hidden Markov Models which are more specialised and thus are deployed on training data that is specific to a set of cardholders which have similar spending behaviours. Clustering techniques were used in order to establish the association between different classes of transactions. Two different clustering algorithms were tested in order to determine the most effective one. Also, different Hidden Markov Models were built using different criteria for test data. The positive results achieved portray the effectiveness of these models in classifying fraudulent and legitimate transactions through a resultant percentage value which indicates the prominence of the transaction being contained in the respective model.peer-reviewe

Handwritten signature verification by independent component analysis

This study explores a method that learns about the image structure directly from the image ensemble in contrast to other methods where the relevant structure is determined in advance and extracted using hand-engineered techniques. In tasks involving the analysis of image ensembles, important information is often found in the higher-order relationships among the image pixels. Independent Component Analysis (ICA) is a method that learns high-order dependencies found in the input. ICA has been extensively used in several applications but its potential for the unsupervised extraction of features for handwritten signature verification has not been explored. This study investigates the suitability of features extracted from images of handwritten signatures using the unsupervised method of ICA to successfully discriminate between different classes of signatures.peer-reviewe