5G network slicing using SDN and NFV: A survey of taxonomy, architectures and future challenges

This paper suggests how the ‘grey literature’, the diverse and heterogeneous body of material that is made public outside, and not subject to, traditional academic peer-review processes, can be used to increase the relevance and impact of management and organization studies (MOS). The authors clarify the possibilities by reviewing 140 systematic reviews published in academic and practitioner outlets to answer the following three questions: (i) Why is grey literature excluded from/included in systematic reviews in MOS? (ii) What types of grey material have been included in systematic reviews since guidelines for practice were first established in this discipline? (iii) How is the grey literature treated currently to advance management and organization scholarship and knowledge? This investigation updates previous guidelines for more inclusive systematic reviews that respond to criticisms of current review practices and the needs of evidence-based management.

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Shades of Grey: guidelines for working with the grey literature in systematic reviews for management and organizational studies

Fog computing aims at extending the Cloud by bringing computational power, storage, and communication capabilities to the edge of the network, in support of the IoT. Segmentation, distribution, and adaptive deployment of functionalities over the continuum from Things to Cloud are challenging tasks, due to the intrinsic heterogeneity, hierarchical structure, and very large scale infrastructure they will have to exploit. In this paper, we propose a simple, yet general, model to support the QoS-aware deployment of multicomponent IoT applications to Fog infrastructures. The model describes operational systemic qualities of the available infrastructure (latency and bandwidth), interactions among software components and Things, and business policies. Algorithms to determine eligible deployments for an application to a Fog infrastructure are presented. A Java tool, FogTorch , based on the proposed model has been prototyped.

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QoS-Aware Deployment of IoT Applications Through the Fog

Software testing is any activity aimed at evaluating an attribute or capability of a program or system and determining that it meets its required results. Although crucial to software quality and widely deployed by programmers and testers, software testing still remains an art, due to limited understanding of the principles of software. The difficulty in software testing stems from the complexity of software: we can not completely test a program with moderate complexity. Testing is more than just debugging. The purpose of testing can be quality assurance, verification and validation, or reliability estimation. Testing can be used as a generic metric as well. Correctness testing and reliability testing are two major areas of testing. Software testing is a trade-off between budget, time and quality.

Software testing

Containers as a lightweight technology to virtualise applications have recently been successful, particularly to manage applications in the cloud. Often, the management of clusters of containers becomes essential and the orchestration of the construction and deployment becomes a central problem. This emerging topic has been taken up by researchers, but there is currently no secondary study to consolidate this research. We aim to identify, taxonomically classify and systematically compare the existing research body on containers and their orchestration and specifically the application of this technology in the cloud. We have conducted a systematic mapping study of 46 selected studies. We classified and compared the selected studies based on a characterisation framework. This results in a discussion of agreed and emerging concerns in the container orchestration space, positioning it within the cloud context, but also moving it closer to current concerns in cloud platforms, microservices and continuous development.

Cloud Container Technologies: A State-of-the-Art Review

We present a container-based architecture for supporting autonomic data stream processing application on fog computing infrastructures. Our architecture runs applications as Docker containers, and it exploits the native features of Docker to dynamically scale up/down the resources of a fog node assigned to the applications running on it. Preliminary results demonstrate that Docker containers are appropriate for building migratable autonomic solutions on fog infrastructures.

Container-based Support for Autonomic Data Stream Processing through the Fog

Finding available services in TOSCA-compliant clouds

The OASIS TOSCA specification aims at enhancing the portability of cloud-based applications by defining a language to describe and manage service orchestrations across heterogeneous clouds. A service template is defined as an orchestration of typed nodes, which can be instantiated by matching other service templates. In this paper, after defining the notion of exact matching between TOSCA service templates and node types, we define three other types of matching (plug-in, flexible and white-box), each permitting to ignore larger sets of non-relevant syntactic differences when type-checking service templates with respect to node types. We also describe how service templates that plug-in, flexibly or white-box match node types can be suitably adapted so as to exactly match them.

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Matching Cloud Services with TOSCA

Since deployment automation technologies are heterogeneous regarding their supported features and modeling languages, selecting a concrete technology is difficult and can result in a lock-in. Therefore, we presented the Essential Deployment Metamodel (EDMM) in previous work that abstracts from concrete technologies and provides a normalized metamodel for creating technology-independent deployment models. In this demonstration, we present tool support for EDMM in the form of the EDMM Modeling and Transformation System, which enables (i) creating EDMM models graphically and (ii) automatically transforming them into models supported by concrete deployment automation technologies.

The EDMM Modeling and Transformation System

Exploiting microservices to architect enterprise applications is becoming commonplace. This makes it crucial to provide some support for designing and analyzing microservice‐based applications, for example, for understanding whether a microservice‐based application adheres to the main design principles of microservices and for choosing how to refactor it when this is not the case. To provide such support, in this article we present the μ TOSCA toolchain. More precisely, we first introduce the μ TOSCA model to represent the architecture of microservice‐based applications with the OASIS standard TOSCA. We then describe a technique to automatically mine the architecture of a microservice‐based application and represent it with μ TOSCA, given the Kubernetes deployment of the application. We also present a methodology to analyze the μ TOSCA representation of a microservice‐based architecture to systematically identify the architectural smells potentially affecting the corresponding application and to resolve them. Finally, we present two prototype tools, μMiner and μFreshener, implementing our mining solution and the support for identifying and resolving architectural smells in microservice‐based applications, respectively. We then assess —by discussing some case studies— how effectively μMiner, μFreshener, and the μ TOSCA toolchain can support researchers and practitioners working with microservices.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/spe.2974

Jacopo Soldani

Papers

Container-based Support for Autonomic Data Stream Processing through the Fog

Finding available services in TOSCA-compliant clouds

Matching Cloud Services with TOSCA

The EDMM Modeling and Transformation System

The μTOSCA toolchain: Mining, analyzing, and refactoring microservice‐based architectures