Data Mining - Concepts and Techniques.

Data Mining Practical Machine Learning Tools and Techniques

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

The theory of affordances

National Institute of Standards and Technology における超伝導研究及び生活

Microservice-based architectures are gaining popularity for their benefits in software development. Distributed tracing can be used to help operators maintain observability in this highly distributed context, and find problems such as latency, and analyse their context and root cause. However, exploring and working with distributed tracing data is sometimes difficult due to its complexity and application specificity, volume of information and lack of tools. The most common and general tools available for this kind of data, focus on trace-level human-readable data visualisation. Unfortunately, these tools do not provide good ways to abstract, navigate, filter and analyse tracing data. Additionally, they do not automate or aid with trace analysis, relying on administrators to do it themselves. In this paper we propose using tracing data to extract service metrics, dependency graphs and work-flows with the objective of detecting anomalous services and operation patterns. We implemented and published open source prototype tools to process tracing data, conforming to the OpenTracing standard, and developed anomaly detection methods. We validated our tools and methods against real data provided by a major cloud provider. Results show that there is an underused wealth of actionable information that can be extracted from both metric and morphological aspects derived from tracing. In particular, our tools were able to detect anomalous behaviour and situate it both in terms of involved services, work-flows and time-frame. Furthermore, we identified some limitations of the OpenTracing format—as well as the industry accepted tracing abstractions—, and provide suggestions to test trace quality and enhance the standard.

Automated Analysis of Distributed Tracing: Challenges and Research Directions

Determining the size of a network and its diameter are important functions in distributed systems, as there are a number of algorithms which rely on such parameters, or at least on estimates of those values. The Extrema Propagation technique allows the estimation of the size of a network in a fast, distributed and fault tolerant manner. The technique was previously studied in a simulation setting where rounds advance synchronously and where there is no message loss. This work presents two main contributions. The first, is the study of the Extrema Propagation technique under asynchronous rounds and integrated in the Network Friendly Epidemic Multicast (NeEM) framework. The second, is the evaluation of a diameter estimation technique associated with the Extrema Propagation. This study also presents a small enhancement to the Extrema Propagation in terms of communication cost and points out some other possible enhancements. Results show that there is a clear trade-off between time and communication that must be considered when configuring the protocol—a faster convergence time implies a higher communication cost. Results also show that its possible to reduce the total communication cost by more than 18% using a simple approach. The diameter estimation technique is shown to have a relative error of less than 10% even when using a small sample of nodes.

/pdf/probabilistic-estimation-of-network-size-and-diameter-55ttzeesrq.pdf

Probabilistic Estimation of Network Size and Diameter

Service providers are increasingly forced to cooperate to strengthen their core competencies and to create partner networks to offer new services. In order to facilitate the collaboration process, business ecosystems have been building which allow service providers to offer their own as well as combined e-services with other providers over the Internet. This paper introduces the Inter-enterprise Service Engineering methodology (ISE) which has been developed in the Texo use case of the Theseus project and provides a comprehensive, interdisciplinary, and model-driven approach to e-service development in business ecosystems. One major aim of ISE is to integrate business as well as technical stakeholders in the eservice development process and support them with appropriate models, methods, and tools.

Service Engineering in Business Ecosystems

Description Concrete Description From S. Chandrasekaran’s Talk 20 Web Service Message Protocol SOAP  SOAP is an XML Messaging Protocol  that allows software running on disparate operating systems, running in different environments to make Remote Procedure Calls (RPC).

/pdf/semantic-web-services-and-processes-semantic-composition-and-14lmrs666v.pdf

Semantic Web Services and Processes: Semantic Composition and Quality of Service

Standardization efforts to simplify the management of cloud applications are being conducted in isolation. The objective of this paper is to investigate to which extend two promising specifications, USDL and TOSCA, can be integrated to automate the lifecycle of cloud applications. In our approach, we selected a commercial SaaS CRM platform, modeled it using the service description language USDL, modeled its cloud deployment using TOSCA, and constructed a prototypical platform to integrate service selection with deployment. Our evaluation indicates that a high level of integration is possible. We were able to fully automatize the remote deployment of a cloud service after it was selected by a customer in a marketplace. Architectural decisions emerged during the construction of the platform and were related to global service identification and access, multi-layer routing, and dynamic binding.

/pdf/cloud-computing-automation-integrating-usdl-and-tosca-54xsm5jvy0.pdf

Cloud computing automation: integrating USDL and TOSCA

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