A decision framework to mitigate vendor lock-in risks in cloud (SaaS category) migration.

Cloud computing offers an innovative business model to enterprise IT services consumption and delivery. However, vendor lock-in is recognised as being a major barrier to the adoption of cloud computing, due to lack of standardisation. So far, current solutions and efforts tackling the vendor lock-in problem have been confined to/or are predominantly technology-oriented. Limited studies exist to analyse and highlight the complexity of vendor lock-in problem existing in the cloud environment. Consequently, customers are unaware of proprietary standards which inhibit interoperability and portability of applications when taking services from vendors. The complexity of the service offerings makes it imperative for businesses to use a clear and well understood decision process to procure, migrate and/or discontinue cloud services. To date, the expertise and technological solutions to simplify such transition and facilitate good decision making to avoid lock-in risks in the cloud are limited. Besides, little research investigations have been carried out to provide a cloud migration decision framework to assist enterprises to avoid lock-in risks when implementing cloud-based Software-as-a-Service (SaaS) solutions within existing environments. Such decision framework is important to reduce complexity and variations in implementation patterns on the cloud provider side, while at the same time minimizing potential switching cost for enterprises by resolving integration issues with existing IT infrastructures. Thus, the purpose of this thesis is to propose a decision framework to mitigate vendor lock-in risks in cloud (SaaS) migration. The framework follows a systematic literature review and analysis to present research findings containing factual and objective information, and business requirements for vendor-neutral interoperable cloud services, and/or when making architectural decisions for secure cloud migration and integration. The underlying research procedure for this thesis investigation consists of a survey based on qualitative and quantitative approaches conducted to identify the main risk factors that give rise to cloud computing lock-in situations. Epistemologically, the research design consists of two distinct phases. In phase 1, qualitative data were collected using open-ended interviews with IT practitioners to explore the business-related issues of vendor lock-in affecting cloud adoption. Whereas the goal of phase 2 was to identify and evaluate the risks and opportunities of lock-in which affect stakeholders’ decision-making about migrating to cloud-based solutions. In synthesis, the survey analysis and the framework proposed by this research (through its step-by-step approach), provides guidance on how enterprises can avoid being locked to individual cloud service providers. This reduces the risk of dependency on a cloud provider for service provision, especially if data portability, as the most fundamental aspect, is not enabled. Moreover, it also ensures appropriate pre-planning and due diligence so that the correct cloud service provider(s) with the most acceptable risks to vendor lock-in is chosen, and that the impact on the business is properly understood (upfront), managed (iteratively), and controlled (periodically). Each decision step within the framework prepares the way for the subsequent step, which supports a company to gather the correct information to make a right decision before proceeding to the next step. The reason for such an approach is to support an organisation with its planning and adaptation of the services to suit the business requirements and objectives. Furthermore, several strategies are proposed on how to avoid and mitigate lock-in risks when migrating to cloud computing. The strategies relate to contract, selection of vendors that support standardised formats and protocols regarding data structures and APIs, negotiating cloud service agreements (SLA) accordingly as well as developing awareness of commonalities and dependencies among cloud-based solutions. The implementation of proposed strategies and supporting framework has a great potential to reduce the risks of vendor lock-in

Modernization of Legacy Information Technology Systems

Large enterprises spend a large portion of their Information Technology (IT) budget on maintaining their legacy systems. Legacy systems modernization projects are a catalyst for IT architects to save cost, provide new and efficient systems that increase profitability, and create value for their organization. Grounded in sociotechnical systems theory, the purpose of this qualitative multiple case study was to explore strategies IT architects use to modernize their legacy systems. The population included IT architects in large enterprises involved in legacy systems modernization projects, one in healthcare, and one in the financial services industry in the San Antonio-New Braunfels, Texas metropolitan area in the United States. The data collection included interviews with eight IT architects, reviewing 12 organizational documents and pertinent artifacts. Data were analyzed using thematic analysis. Prominent themes included collaboration in modernization projects, systems and process documentation, and resources upskilling and technical training. A key recommendation is for IT architects in large enterprises to ensure that team collaboration, system documentation, and resource technical training are built into all aspects of the legacy systems modernization projects. The implications for positive social change include the potential to bring together individuals with diverse backgrounds and different perspectives and skills to develop trust and build positive relationships during legacy systems modernization projects

Citizen Science and Geospatial Capacity Building

This book is a collection of the articles published the Special Issue of ISPRS International Journal of Geo-Information on “Citizen Science and Geospatial Capacity Building”. The articles cover a wide range of topics regarding the applications of citizen science from a geospatial technology perspective. Several applications show the importance of Citizen Science (CitSci) and volunteered geographic information (VGI) in various stages of geodata collection, processing, analysis and visualization; and for demonstrating the capabilities, which are covered in the book. Particular emphasis is given to various problems encountered in the CitSci and VGI projects with a geospatial aspect, such as platform, tool and interface design, ontology development, spatial analysis and data quality assessment. The book also points out the needs and future research directions in these subjects, such as; (a) data quality issues especially in the light of big data; (b) ontology studies for geospatial data suited for diverse user backgrounds, data integration, and sharing; (c) development of machine learning and artificial intelligence based online tools for pattern recognition and object identification using existing repositories of CitSci and VGI projects; and (d) open science and open data practices for increasing the efficiency, decreasing the redundancy, and acknowledgement of all stakeholders

Bioinspired metaheuristic algorithms for global optimization

This paper presents concise comparison study of newly developed bioinspired algorithms for global optimization problems. Three different metaheuristic techniques, namely Accelerated Particle Swarm Optimization (APSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO) are investigated and implemented in Matlab environment. These methods are compared on four unimodal and multimodal nonlinear functions in order to find global optimum values. Computational results indicate that GWO outperforms other intelligent techniques, and that all aforementioned algorithms can be successfully used for optimization of continuous functions

Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF

Learning Outcomes of Classroom Research

Personal pronouns are a linguistic device that is used to engage students at various educational levels. Personal pronouns are multifunctional, and their functions range from inclusion to exclusion, and include establishing of rapport with students. In this chapter, we compare the use of personal pronouns at university and secondary school levels. Our previous study (Yeo & Ting, 2014) showed the frequent use of you in lecture introductions (2,170 instances in the 37,373-word corpus) to acknowledge the presence of students. The arts lecturers were more inclusive than the science lecturers, reflected in the less frequent use of exclusive-we and we for one, as well as the frequent use of you-generalised. We have also compiled and analysed a 43,511-word corpus from 15 English lessons in three Malaysian secondary schools. This corpus yielded 2,019 instances of personal pronoun use. The results showed that you was the most frequently used personal pronoun, followed by we and I. You-audience was used more than you-generalised, and the main function was to give instructions to students. The teachers appeared to be more directive than the lecturers in the previous study, who sometimes used the inclusive-we for you and I and we for I to lessen the social distance with students, indicating that the discourse functions of personal pronouns vary with the educational context. The findings suggest that educators can be alerted to the versatility of personal pronouns, for example, for engaging students in the lesson and for asserting authority in the subject matter. Keywords: student engagement; personal pronouns; lecture; classroom; teache