MADCAT: A Methodology for Architecture and Deployment of Cloud Application Topologies

Inzinger, Christian; Nastić, Stefan; Sehic, Sanjin; Vögler, Michael; Li, Fēi; Dustdar, Schahram

doi:10.1109/sose.2014.9

Cited by 38 publications

(22 citation statements)

References 33 publications

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“…As proposed in [11], building IoT cloud systems includes creating and/or selecting suitable software-defined IoT units, provisioning and composing more complex units and building custom business logic components. This (iterative) development process is structured along four main phases (cf.…”

Section: Main Design Principles and Development Methodology For Softwmentioning

confidence: 99%

“…SDG-Pro does not propose a novel software-defined approach for IoT cloud systems. It builds on the design principles that were elicited in our previous research [7,9,10] and adopts development methodology we proposed in [11], extending them to provide programming abstractions that facilitate development of the essential application artifacts. SDG-Pro's programming model is designed to enforce the main design principles of software-defined IoT cloud systems at application level, from the early development stages.…”

Section: The Sdg-pro Frameworkmentioning

confidence: 99%

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SDG-Pro: a programming framework for software-defined IoT cloud gateways

Nastić

Truong

Dustdar

2015

J Internet Serv Appl

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Recently, emerging IoT cloud systems create numerous opportunities for a variety of stakeholders in terms of optimizing their existing business processes, as well as developing novel cross-organization and cross-domain applications. However, developers of such systems face a plethora of challenges, mainly due to complex dependencies between the application business logic and the underlying IoT cloud infrastructure, as well as difficulties to provision and govern vast, geographically distributed IoT cloud resources. In this paper, we introduce SDG-Pro -a novel programming framework for software-defined IoT cloud systems. The main features of our framework include programming abstractions: Software-Defined Gateways, Intents, Intent Scopes, and Data and Control Points, as well as provisioning and governance APIs that allow for programmatic management of software-defined gateways throughout their entire lifecycle. The SDG-Pro framework enables easier, efficient and more intuitive development of IoT cloud applications. It promotes the everything-as-code paradigm for IoT cloud applications in order to provide a uniform, programmatic view on the entire development process. To illustrate the feasibility of our framework to support development of IoT cloud applications, we evaluate it using a real-world case study on managing fleets of electric vehicles.

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Section: Main Design Principles and Development Methodology For Softwmentioning

confidence: 99%

Section: The Sdg-pro Frameworkmentioning

confidence: 99%

SDG-Pro: a programming framework for software-defined IoT cloud gateways

Nastić

Truong

Dustdar

2015

J Internet Serv Appl

Self Cite

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“…As foundation for said abstraction we use MADCAT (Inzinger et al, 2014) and its extensions, which we introduced in Smart Fabric (Schleicher et al, 2015a on certain DIs, along with the ability to link TU to DAUs. Additionally, we provide an implementation of the abstract concepts along with the proposed methodology extensions for the SDD Framework.…”

Section: System Modelmentioning

confidence: 99%

Modeling and management of usage-aware distributed datasets for global Smart City Application Ecosystems

Schleicher

Vögler

Inzinger

et al. 2017

PeerJ Computer Science

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The ever-growing amount of data produced by and in today's smart cities offers significant potential for novel applications created by city stakeholders as well as third parties. Current smart city application models mostly assume that data is exclusively managed by and bound to its original application and location. We argue that smart city data must not be constrained to such data silos so that future smart city applications can seamlessly access and integrate data from multiple sources across multiple cities. In this paper, we present a methodology and toolset to model available smart city data sources and enable efficient, distributed data access in smart city environments. We introduce a modeling abstraction to describe the structure and relevant properties, such as security and compliance constraints, of smart city data sources along with independently accessible subsets in a technology-agnostic way. Based on this abstraction, we present a middleware toolset for efficient and seamless data access through autonomous relocation of relevant subsets of available data sources to improve Quality of Service for smart city applications based on a configurable mechanism. We evaluate our approach using a case study in the context of a distributed city infrastructure decision support system and show that selective relocation of data subsets can significantly reduce application response times.

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“…However there were multiple articles that were discussing architectural approaches for development of cloud-ready applications (Sodhi et al (2011)), principles (Andrikopoulos et al (2012)), patterns (Wilder (2012), Fehling et al (2011, 2014). Later works in this area were more related to conventional application migration to the cloud (Andrikopoulos et al (2013)) or development methods or frameworks (Inzinger et al (2014), Ardagna et al (2012)). …”

Section: [Rq3] What Architectures Are Currently Used For Cloud-ready mentioning

confidence: 99%

Systematic Literature Review of the Cloud-ready Software Architecture

Pozdniakova¹,

Mažeika²

2017

BJMC

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Abstract. Many companies are adopting cloud for hosting applications delivered as a service over the Internet. An application service delivered in this way is referred as Software as a Service (SaaS). The SaaS providers get benefits from getting cloud resources provisioned on-demand and through pay-as-you-go billing models. These capabilities enable faster application development and deployment with lower upfront investment into infrastructure. To benefit the most from the cloud, software architecture must be designed with consideration that software will run on the cloud. However, a legacy application is often developed by using monolithic architecture approach and might not get all advantages provided by a cloud computing. A growing monolithic application gets less flexible in development, has longer provisioning time, slows down the speed of innovation and lowers economy of scale. As result of such problems, not only commercial companies, but also the various academic researchers aim to design software as a "cloud-native" application. This kind of software has specific non-functional requirements that define scalability, reliability, fault tolerance and other cloud-specific requirements. This systematic literature review is based on the case studies, published articles and other literature related to the cloud-native or cloud-ready applications. It generalizes common traits of non-functional requirements defined in analyzed resources. Also, it walks through architectural styles of the applications running on a cloud and presents recently developed architectures that are used for large-scale software services delivered on a cloud.

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MADCAT: A Methodology for Architecture and Deployment of Cloud Application Topologies

Cited by 38 publications

References 33 publications

SDG-Pro: a programming framework for software-defined IoT cloud gateways

SDG-Pro: a programming framework for software-defined IoT cloud gateways

Modeling and management of usage-aware distributed datasets for global Smart City Application Ecosystems

Systematic Literature Review of the Cloud-ready Software Architecture

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