Ernest Ketcha Ngassam

A framework for the dynamic implementation of finite automata for performance enhancement

The aim of this work is to provide a model for the dynamic implementation of finite automata for enhanced performance. Investigations have shown that hardcoded finite automata outperforms the traditional table-driven implementation up to some threshold. Moreover, the kind of string being recognized plays a major role in the overall processing speed of the string recognizer. Various experiments are depicted to show when the advantages of using hardcoding as basis for implementing finite automata (instead of using the classical table-driven approach) become manifest. The model, a dynamic algorithm that combines both hardcoding and table-driven is introduced.

Efficient automata constructions and approximate automata

In this paper, we present data structures and algorithms for efficiently constructing approximate automata. An approximate automaton for a regular language L is one which accepts at leastL. Such automata can be used in a variety of practical applications, including network security pattern matching, in which false-matches are only a performance nuisance. The construction algorithm is particularly efficient, and is tunable to yield more or less exact automata.

A taxonomy of DFA-based string processors

A range of implementation strategies of DFA-based string recognizers is suggested. The strategies are associated with parameters which modify the implementation of conventional DFA implementations (table-driven and hardcoded). These parameters are used to provide a formal characterization of DFA-based string recognizers. Various instantiations of these parameters correspond to various DFA-based string processing algorithms. The algorithms derived are further classified, based on the refinement of some of them, resulting in a taxonomy tree. The tree will form the basis for further studies on the design and implementation of DFA-based string processors.

DYNAMIC ALLOCATION OF FINITE AUTOMATA STATES FOR FAST STRING RECOGNITION

The spatial and temporal locality of reference on which cache memory relies to minimize cache swaps, is exploited to design a new algorithm for finite automaton string recognition. It is shown that the algorithm, referred to as the Dynamic State Allocation algorithm outperforms the traditional table-driven algorithm for strings that tend to repeatedly access the same set of states, provided that the string is long enough to amortize the allocation cost. Further improvements on the algorithm result in even better performance.

ON IMPLEMENTATION AND PERFORMANCE OF TABLE-DRIVEN DFA-BASED STRING PROCESSORS

Table-driven (TD) DFA-based string processing algorithms are examined from a number of vantage points. Firstly, various strategies for implementing such algorithms in a cache-efficient manner are identified. The denotational semantics of such algorithms is encapsulated in a function whose various arguments are associated with each implementation strategy. This formal view of the implementation strategies suggests twelve different algorithms, each blending together the implementation strategies in a particular way. The performance of these algorithms is examined in against a set of artificially generated data. Results indicate a number of cases where the new algorithms outperform the traditional TD algorithm.

A framework for the choreography of intelligent e-services

In this paper a framework for the choreography of intelligent electronic services (e-services) that follows the Service-Oriented Architecture principle is presented. The composition abilities of intelligent e-services in the framework enable them to match a users request for service consumption. The framework is based on a dynamic model of message query-based with casual knowledge-based expansion. A practical illustration of the application of the framework relies on a domain-specific e-service aggregation following an e-mentoring business scenario. The e-mentoring scenario is chosen in order to take advantage of the innovative features offered by the current World Wide Web, which has evolved into a provider of services.

A data management and analytic model for business intelligence applications

Most organisations use several Data Management and Business Intelligence solutions which are on-premise and/or cloud-based to manage and analyse their constantly growing business data. Challenges faced by organisations nowadays include but not limited to: growth limitations, big data, inadequate analytics, computing, and data storage capabilities. A data management and analytic model is proposed for organisations to rely on for decisive guidance when planning to procure and implement a unified business intelligence solution. The model which is considered hybrid relies on existing on-premise and cloud models with limitations mitigated. To assess the state of business intelligence utilisation, and validate and improve the proposed architecture, two case studies targeting users and experts were conducted following quantitative and qualitative approaches. The findings further recognised the proposed hybrid architecture as appropriate for managing complex organisations with big data challenges.

An integrated framework for benchmarking e-government projects

Governments worldwide are using e-Governance to improve efficiency and effectiveness of public administration systems and service delivery. The digitally dynamic nature of the world today represents an opportunity for developing countries to fully embrace e-Governance and thereby contributing to meeting the needs of the citizenry. Successful implementation of e-governance projects ought to be guided by sound mechanisms to minimize failure and ensure a positive impact. Frameworks such as e-Readiness, strategy-based and maturity as well as stage-based e-governance frameworks seldom focus on monitoring and evaluation of projects and lack emphasis on the project life-cycle. We hereby rely on the foregoing shortcomings to propose an integrated framework for benchmarking the implementation of e-governance projects. Our suggested framework represents an important tool to be relied upon by stakeholders to increase accountability on e-governance projects and maximize their chance for success.

A framework for the monitoring and evaluation of e-governance projects in developing countries

E-governance (e-Gov) is increasingly taking centre stage all over the world. Countries like United States, Japan and Singapore have successfully transformed their governance process through e-Gov. Information and Communication Technology (ICT) have become an integral part of the social fabric of many countries. Although, E-Gov has chalked significant gains in the developed world, this is yet to be fully realized in the developing world. One of the major causes of the failure of e-Gov projects in developing world has been due to a lack of monitoring and evaluation and a failure by sponsoring bodies to realize that the projects that worked in the developed world may not necessarily do so in the developing world because of differences in socio-economic realities. This paper proposes a framework for monitoring and evaluating e-Gov projects. The framework is premised by the identification of critical success factors peculiar to the effective and efficient implementation of e-governance projects based on an improved contextual project lifecycle.

Methodology for improving Data Quality Management in South African government departments

To enable effective and efficient service delivery, addressing data quality problems is an item of high importance on the business agenda of managers in government departments. However, the constant use of manual and legacy information systems, in South African government departments contributes significantly to poor data quality. This work proposes a conceptual model for improving Data Quality Management in South African government departments. The conceptual model is based on the Technology-Organization-Environment (TOE) framework. A key feature of the model is the recognition of the importance of inter-governmental systems integration/interface, electronic capturing of data and user biometric access control to improving Data Quality Management in government departments.