How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

Purpose – The purpose of this paper is to discuss new approaches for managing personal knowledge in the Web 2.0 era. The paper questions whether Web 2.0 technologies (social software) are a real panacea for the challenges associated with the management of knowledge. Can Web 2.0 reconcile the conflicting interests of managing organisational knowledge with personal objectives? Does Web 2.0 enable a more effective way of sharing and managing knowledge at the personal level?Design/methodology/approach – Theoretically deductive with illustrative examples.Findings – Web 2.0 plays a multifaceted role for communicating, collaborating, sharing and managing knowledge. Web 2.0 enables a new model of personal knowledge management (PKM) that includes formal and informal communication, collaboration and social networking tools. This new PKM model facilitates interaction, collaboration and knowledge exchanges on the web and in organisations.Practical implications – Based on these findings, professionals and scholars wil...

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Personal Knowledge Management: The role of Web 2.0 tools for managing knowledge at individual and organisational levels

Understanding cloud-native applications after 10 years of cloud computing - A systematic mapping study

In the last few years, we have witnessed the huge popularity of one of the most promising technologies of the modern era: the Internet of Things. In IoT, various smart objects (smart sensors, embedded devices, PDAs, and smartphones) share their data with one another irrespective of their geographical locations using the Internet. The amount of data generated by these connected smart objects will be on the order of zettabytes in the coming years. This huge amount of data creates challenges with respect to storage and analytics given the resource constraints of these smart devices. Additionally, to process the large volume of information generated, the traditional cloud-based infrastructure may lead to long response time and higher bandwidth consumption. To cope up with these challenges, a new powerful technology, edge computing, promises to support data processing and service availability to end users at the edge of the network. However, the integration of IoT and edge computing is still in its infancy. Task scheduling will play a pivotal role in this integrated architecture. To handle all the above mentioned issues, we present a novel architecture for task selection and scheduling at the edge of the network using container-as-a-service (CoaaS). We solve the problem of task selection and scheduling by using cooperative game theory. For this purpose, we developed a multi-objective function in order to reduce the energy consumption and makespan by considering different constraints such as memory, CPU, and the user's budget. We also present a real-time internal and external container migration technique for minimizing the energy consumption. For task selection and scheduling, we have used lightweight containers instead of the conventional virtual machines to reduce the overhead and response time as well as the overall energy consumption of fog devices, that is, nano data centers (nDCs). Our empirical results demonstrate that the proposed scheme reduces the energy consumption and the average number of SLA violations by 21.75 and 11.82 percent, respectively.

Container-as-a-Service at the Edge: Trade-off between Energy Efficiency and Service Availability at Fog Nano Data Centers

The use of containers in cloud architectures has become widespread, owing to advantages such as limited overheads, easier and faster deployment, and higher portability. Moreover, they present a suitable architectural solution for the deployment of applications created using a microservice development pattern. Despite the large number of solutions and implementations, there remain open issues that have not been completely addressed in container automation and management. Container resource allocation influences system performance and resource consumption, and so it is a key factor for cloud providers. We propose a genetic algorithm approach, using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), to optimize container allocation and elasticity management, motivated by the good results obtained with this algorithm in other resource management optimization problems in cloud architectures. Our optimization algorithm enhances system provisioning, system performance, system failure, and network overhead. A model for cloud clusters, containers, microservices, and four optimization objectives is presented. Experimental results demonstrate that our approach is a suitable solution for addressing the problem of container allocation and elasticity, and it obtains better objective values than the container management policies implemented in Kubernetes.

Genetic Algorithm for Multi-Objective Optimization of Container Allocation in Cloud Architecture

NoSQL and especially graph databases are constantly gaining popularity among developers of Web 2.0 applications as they promise to deliver superior performance when handling highly interconnected data compared to traditional relational databases. Apache Shindig is the reference implementation for OpenSocial with its highly interconnected data model. However, the default back-end is based on a relational database. In this paper we describe our experiences with a different back-end based on the graph database Neo4j and compare the alternatives for querying data with each other and the JPA-based sample back-end running on MySQL. Moreover, we analyze why the different approaches often may yield such diverging results concerning throughput. The results show that the graph-based back-end can match and even outperform the traditional JPA implementation and that Cypher is a promising candidate for a standard graph query language, but still leaves room for improvements.

Performance of graph query languages: comparison of cypher, gremlin and native access in Neo4j

Docker provides a good basis to run composite applications in the cloud, especially if those are not cloud-aware, or cloud-native. However, Docker concentrates on managing containers on one host, but SaaS providers need a container management solution for multiple hosts. Therefore, a number of tools emerged that claim to solve the problem. This paper classifies the solutions, maps them to requirements from a case study and identifies gaps and integration requirements. We close some of these gaps with our own integration components and tool enhancements, resulting in the currently most complete management suite.

Docker Cluster Management for the Cloud - Survey Results and Own Solution

Enterprise knowledge infrastructures , Enterprise knowledge infrastructures , مرکز فناوری اطلاعات و اطلاع رسانی کشاورزی

Enterprise knowledge infrastructures

Knowledge management represents a key issue for both information systems’ academics and practitioners, including those who have become disillusioned by actual results that fail to deliver on exaggerated promises and idealistic visions. Social software, a tremendous global success story, has prompted similarly high expectations regarding the ways in which organizations can improve their knowledge handling. But can these expectations be met, whether in academic research or the real world? This article seeks to identify current research trends and gaps, with a focus on social knowledge environments. The proposed research agenda features four focal challenges: semi-permeable organizations, social software in professional work settings, crowd knowledge, and cross-border knowledge management. Three solutions emerge as likely methods to address these challenges: design-oriented solutions, analytical solutions, and interdisciplinary dialogue.

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Social Knowledge Environments

The capability to operate cloud-native applications can generate enormous business growth and value. But enterprise architects should be aware that cloud-native applications are vulnerable to vendor lock-in. We investigated cloud-native application design principles, public cloud service providers, and industrial cloud standards. All results indicate that most cloud service categories seem to foster vendor lock-in situations which might be especially problematic for enterprise architectures. This might sound disillusioning at first. However, we present a reference model for cloud-native applications that relies only on a small subset of well standardized IaaS services. The reference model can be used for codifying cloud technologies. It can guide technology identification, classification, adoption, research and development processes for cloud-native application and for vendor lock-in aware enterprise architecture engineering methodologies.

René Peinl

Papers

Performance of graph query languages: comparison of cypher, gremlin and native access in Neo4j

Docker Cluster Management for the Cloud - Survey Results and Own Solution

Enterprise knowledge infrastructures

Social Knowledge Environments

ClouNS - a Cloud-Native Application Reference Model for Enterprise Architects