A network approach for managing and processing big cancer data in clouds

Translational cancer research requires integrative analysis of multiple levels of big cancer data to identify and treat cancer. In order to address the issues that data is decentralised, growing and continually being updated, and the content living or archiving on different information sources partially overlaps creating redundancies as well as contradictions and inconsistencies, we develop a data network model and technology for constructing and managing big cancer data. To support our data network approach for data process and analysis, we employ a semantic content network approach and adopt the CELAR cloud platform. The prototype implementation shows that the CELAR cloud can satisfy the on-demanding needs of various data resources for management and process of big cancer data

The Internet-of-Things Meets Business Process Management: Mutual Benefits and Challenges

The Internet of Things (IoT) refers to a network of connected devices collecting and exchanging data over the Internet. These things can be artificial or natural, and interact as autonomous agents forming a complex system. In turn, Business Process Management (BPM) was established to analyze, discover, design, implement, execute, monitor and evolve collaborative business processes within and across organizations. While the IoT and BPM have been regarded as separate topics in research and practice, we strongly believe that the management of IoT applications will strongly benefit from BPM concepts, methods and technologies on the one hand; on the other one, the IoT poses challenges that will require enhancements and extensions of the current state-of-the-art in the BPM field. In this paper, we question to what extent these two paradigms can be combined and we discuss the emerging challenges

An Assessment of DevOps Maturity in a Software Project

DevOps is a software development method, which aims at decreasing conflict between software developers and system operators. Conflicts can occur because the developers’ goal is to release the new features of the software to production, whereas the operators’ goal is to keep the software as stable and available as possible. In traditional software development models, the typical amount of time between deployments can be long and the changes in software can become rather complex and big in size. The DevOps approach seeks to solve this contradiction by bringing software developers and system operators together from the very beginning of a development project. In the DevOps model, changes deployed to production are small and frequent. Automated deployments decrease human errors that sometimes occur in manual deployments. Testing is at least partly automated and tests are run after each individual software change. However, technical means are only one part of the DevOps approach. The model also emphasizes changes in organizational culture, which are ideally based on openness, continuous learning, and experimentation. Employees possess the freedom of decision-making while carrying the responsibility that follows. In addition to individual or team-based goals, each employee is encouraged to pursue the common goals. The aim of this thesis is two-fold. Firstly, the goal is to understand and define the DevOps model through a literature review. Secondly, the thesis analyzes the factors that contribute to the successful adoption of DevOps in an organization, including those with the possibility of slowing down or hindering the process. A qualitative case study was carried out on a system development project in a large Finnish technology company. The data consists of semi-structured open-ended interviews with key personnel, and the findings are analyzed and compared to factors introduced in previous DevOps literature, including the DevOps maturity model. The case project is also assessed in terms of its DevOps maturity. Finally, impediments and problems regarding DevOps adoption are discussed. Based on the case study, major challenges in the project include the large size and complexity of the project, problems in project management, occasional communication problems between the vendor and the client, poor overall quality of the software, and defects in the software development process of the vendor. Despite the challenges, the company demonstrated progress in some aspects, such as partly automating the deployment process, creating basic monitoring for the software, and negotiating development and testing guidelines with the vendor

Towards the Automation of Data Networks

Una amplia variedad de empresas, corporaciones, CSPs y especialistas han enfatizado la dificultad de gestionar redes modernas, que introducen innovaciones tecnológicas de alto impacto, como cloud computing, movilidad, nuevos perfiles de tráfico, NFV, IoT, Big Data, entre otras. La automatización de redes es una metodología en la que los dispositivos de red físicos y virtuales se configuran, aprovisionan, administran y prueban automáticamente mediante software. Grandes empresas, como Cisco, Juniper, Red Hat o VMWare ofrecen soluciones propietarias de automatización de red. Además, recientemente ha habido un aumento en la cantidad de herramientas que asisten en la automatización de redes. Ambos hechos han marcado un cambio en la forma en que los administradores construyen y administran las redes. La mayoría de los grandes operadores de comunicaciones trabajan y tienden, en este sentido, a redes verdaderamente autónomas que, eventualmente, requerirán del uso intensivo de Inteligencia Artificial (IA).  Los avances en la temática muestran que tres segmentos específicos CSPs, Proveedores en la Nube, y las empresas se encuentran en diferentes etapas de madurez de la automatización. Se espera, que progresivamente, esta tendencia alcance, también, a las organizaciones de menor envergadura. Este documento presenta un estudio técnico especializado, detallado y actual sobre el estado del arte en automatización de redes, destacando las tendencias que se observan en los entornos de TI, de las empresas y operadores de comunicaciones, más involucrados en esta tecnología y, finalizando, con una discusión sobre herramientas de automatización.A wide variety of enterprises, corporations, communications service providers (CSPs), and experts have highlighted the difficulty of managing modern networks. These networks exhibit high-impact technological innovations, such as cloud computing, mobility, new traffic profiles, network functions virtualization (NFV), the Internet of things (IoT), Big Data, among others. Network automation is a methodology in which physical and virtual network devices are automatically configured, provisioned, managed, and tested using software. Large enterprises such as Cisco, Juniper, Red Hat, and VMWare offer proprietary solutions for network automation. Additionally, the number of tools assisting in network automation has recently increased. Taken together, these developments have changed the way administrators build and manage networks. In this regard, most large communications operators are now working and moving toward truly autonomous networks that will eventually require an intensive use of Artificial Intelligence (AI). Advances in the area show that three specific segments —CSPs, Cloud Providers, and Enterprises— are all at different stages of automation maturity. Over time, network automation is expected to reach smaller organizations as well. This paper presents a specialized, detailed and current technical study on the state of the art in network automation, highlighting the trends observed in information technology (IT) environments, enterprises and communications operators —which are closely involved in this technology—, and concludes with a discussion on automation tools

Digital Service: Technological Agency in Service Systems

This paper defines digital service in the context of technologically enhanced value co-creation between service system entities. Progress in digitalization and Artificial Intelligence (AI) is increasing the relative share of technologically enhanced value co-creation between service system entities (e.g., people, companies, nations). Highly automated technical systems increasingly act as autonomous agents, on behalf of service providers, in value co-creation interactions with the system users. Sufficient conceptualization, abstractions and modeling paradigms for research and development of this type of value co-creation are absent from the literature and introduced in this paper. The main contribution of the paper is introduction and definition of digital service and digital service membrane as fundamental concepts in service science and service systems, with directions for future research on the topic