Storage Solutions for Big Data Systems: A Qualitative Study and Comparison

Big data systems development is full of challenges in view of the variety of application areas and domains that this technology promises to serve. Typically, fundamental design decisions involved in big data systems design include choosing appropriate storage and computing infrastructures. In this age of heterogeneous systems that integrate different technologies for optimized solution to a specific real world problem, big data system are not an exception to any such rule. As far as the storage aspect of any big data system is concerned, the primary facet in this regard is a storage infrastructure and NoSQL seems to be the right technology that fulfills its requirements. However, every big data application has variable data characteristics and thus, the corresponding data fits into a different data model. This paper presents feature and use case analysis and comparison of the four main data models namely document oriented, key value, graph and wide column. Moreover, a feature analysis of 80 NoSQL solutions has been provided, elaborating on the criteria and points that a developer must consider while making a possible choice. Typically, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings forth second facet of big data storage, big data file formats, into picture. The second half of the research paper compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Decentralized storage and blockchain are seen as the next generation of big data storage and its challenges and future prospects have also been discussed

Privacy matters:issues within mechatronics

As mechatronic devices and components become increasingly integrated with and within wider systems concepts such as Cyber-Physical Systems and the Internet of Things, designer engineers are faced with new sets of challenges in areas such as privacy. The paper looks at the current, and potential future, of privacy legislation, regulations and standards and considers how these are likely to impact on the way in which mechatronics is perceived and viewed. The emphasis is not therefore on technical issues, though these are brought into consideration where relevant, but on the soft, or human centred, issues associated with achieving user privacy

Rethinking Digital Forensics

© IAER 2019In the modern socially-driven, knowledge-based virtual computing environment in which organisations are operating, the current digital forensics tools and practices can no longer meet the need for scientific rigour. There has been an exponential increase in the complexity of the networks with the rise of the Internet of Things, cloud technologies and fog computing altering business operations and models. Adding to the problem are the increased capacity of storage devices and the increased diversity of devices that are attached to networks, operating autonomously. We argue that the laws and standards that have been written, the processes, procedures and tools that are in common use are increasingly not capable of ensuring the requirement for scientific integrity. This paper looks at a number of issues with current practice and discusses measures that can be taken to improve the potential of achieving scientific rigour for digital forensics in the current and developing landscapePeer reviewe

Design Management Capability in Entrepreneurship: A Case Study of Xiaomi

In recent years, entrepreneurship has become a popular topic and attracted many young people to start their own companies. In entrepreneurship, design was generally viewed as essential to innovation, replacing the conventional role of the engineer. Unlike traditional businesses, which generally take a longer time to become established in the more stable economic context of mass-production, current start-ups have to face fierce competition and have the tendency to expand rapidly and accommodate the dynamic business environment. Consequently, design management is considered to be crucial to business growth, since it contributes to both competitive advantages and strategic flexibility. However, start-up companies are well-known for their high failure ratio. This triggered our initial research question: what is the role of design in a start-up to support it in achieving success? Through a case study of Xiaomi, a well-known successful entrepreneurship in China, the new capabilities of entrepreneurial design management were reported. It was further classified into three key topics in line with the three stages of entrepreneurial business development. Difference with design management capabilities reported in previous studies, the new capabilities show the dynamic nature of entrepreneurial design management

Connected systems in smart cities: use-cases of integration of buildings information with smart systems

Realisation of smart cities is highly dependent on innovative connections between the deployed systems in the cities. This implies that successfully deployment of individual smart systems which meet citizens’ needs, is not sufficient to make a city smart. Indeed, the smart cities require to innovate and connect establish infrastructures for the citizens and organisations. To enable connected systems in smart cities, the possibilities to exchange and integration information between different systems is essential. Construction industry is one of the domains which owns huge amount of valuable information asset. Buildings information can be utilised to create initiatives associated with various domains like, urban and infrastructure planning, maintenance/facility management, and energy monitoring. However, there are some barriers to realise these initiatives. This paper introduces and elaborates the details about three use-cases which need to utilise buildings information to present innovative smart services. The three use cases are: 1) Energy Usage Monitoring for positive energy usage district areas in Smart Cities (a use case from River City-anonymous name of the city); 2) Services for Facility Management Industry (a use-case from Estates office in Quay University); 3) Safety & risk management for buildings in 3D Hack event in Dublin. Each use-case considers various stakeholders’ perspectives. Also they include elaborated details related to the barriers and challenges associated with utilisation and integration of buildings information. This paper concludes by the detailed barriers to benefit from valuable buildings information to create innovative smart services. Further, recommendations are provided to overcome the presented challenges

Business Models for Internet of Things Platforms: Empirical Development of a Taxonomy and Archetypes

A wide range of Internet of Things platform providers operate diverse business models to cater for the manifold requirements of the IoT. This paper contributes to a more precise understanding of IoT platforms as an essential building block of the IoT based on the characteristics of its business models. Even though research listing technological dimensions according to which IoT platforms differ, they have neither been systematically derived nor been linked to the business model concept. In turn, they lack descriptive power on the heterogeneous value creation mechanisms of the platform providers. Within our research, we first analyzed 195 IoT platforms and systemically developed a taxonomy allowing the characterization of IoT platform business models. Second, based on this taxonomy, we identified nine archetypes of IoT platform business models and illustrated typical combinations of business model characteristics. Equipped with such an understanding, practice and research can analyze existing IoT platforms more accurately