Reliable self-deployment of distributed cloud applications

Etchevers, Xavier; Salaün, Gwen; Boyer, Fabienne; Coupaye, Thierry; DeźPalma, Noel

doi:10.1002/spe.2400

Cited by 15 publications

(16 citation statements)

References 41 publications

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“…They also propose several kinds of analysis for checking, e.g., the validity of a management plan or the possibility to reach a certain configuration given a plan. [37] presents a self-deployment protocol that aims at configuring a set of software components distributed over a set of virtual machines. This protocol works in a fully automated and decentralized way while supporting VM failures.…”

Section: Composition (Techniques)mentioning

confidence: 99%

Rigorous Design and Deployment of IoT Applications

Krishna

Pallec²,

Mateescu³

et al. 2019

2019 IEEE/ACM 7th International Conference on Formal Methods in Software Engineering (FormaliSE)

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Internet connected devices are becoming increasingly common in consumer homes. These devices combined with software entities are used to build Internet of Things (IoT) applications. As democratization of IoT takes shape, developing reliable IoT applications remains a challenge for consumers because these applications exhibit characteristics such as distribution, dynamicity, and heterogeneity, which make their design, development and maintenance difficult. In this paper, we use formal methods to ensure correct composition of objects and propose a reliable deployment mechanism in the context of an IoT application. Objects are modelled using an interface description model integrating a behavioural specification of the object functionality. We provide formal validation techniques for verifying that the composition is correct. A deployment plan is generated for automating the instantiation of all objects involved in a valid composition. All the proposals have been implemented as a prototype tool and experiments were carried out for evaluating the tool performance and usability.

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Section: Composition (Techniques)mentioning

confidence: 99%

Rigorous Design and Deployment of IoT Applications

Krishna

Pallec²,

Mateescu³

et al. 2019

2019 IEEE/ACM 7th International Conference on Formal Methods in Software Engineering (FormaliSE)

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“…This protocol supports virtual machine and network failures, and always succeeds in deploying an application when faced with a finite number of failures. The main difference with our work is that [11] considers stateless applications whereas we focus on consistent state recovery, and consequently the state of the application needs to be stored.…”

Section: Fault-tolerant Management Systemsmentioning

confidence: 99%

Resilience of Stateful IoT Applications in a Dynamic Fog Environment

Ozeer

Etchevers

Letondeur

et al. 2018

Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

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Fog computing provides computing, storage and communication resources at the edge of the network, near the physical world. Subsequently, end devices nearing the physical world can have interesting properties such as short delays, responsiveness, optimized communications and privacy. However, these end devices have low stability and are prone to failures. There is consequently a need for failure management protocols for IoT applications in the Fog. The design of such solutions is complex due to the specificities of the environment, i.e., (i) dynamic infrastructure where entities join and leave without synchronization, (ii) high heterogeneity in terms of functions, communication models, network, processing and storage capabilities, and, (iii) cyber-physical interactions which introduce non-deterministic and physical world's space and time dependent events. This paper presents a fault tolerance approach taking into account these three characteristics of the Fog-IoT environment. Fault tolerance is achieved by saving the state of the application in an uncoordinated way. When a failure is detected, notifications are propagated to limit the impact of failures and dynamically reconfigure the application. Data stored during the state saving process are used for recovery, taking into account consistency with respect to the physical world. The approach was validated through practical experiments on a smart home platform.

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“…One of the big advantages of an agent‐based approach is the reliability and resiliency against failures as shown by Xavier et al and Kirschnick et al Lavinal et al have shown that the local autonomy of each agent combined with their organizing behavior enables global management autonomy in a distributed environment. The flexibility of the agent‐based approach allows it to manage not only analytical platforms but also the workloads running on top of those platforms as shown by the authors' previous work .…”

Section: Related Workmentioning

confidence: 99%

Orchestrator conversation: Distributed management of cloud applications

et al. 2018

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Managing cloud applications is complex, and the current state of the art is not addressing this issue. The ever-growing software ecosystem continues to increase the knowledge required to manage cloud applications at a time when there is already an IT skills shortage. Solving this issue requires capturing IT operation knowledge in software so that this knowledge can be reused by system administrators who do not have it. The presented research tackles this issue by introducing a new and fundamentally different way to approach cloud application management: a hierarchical collection of independent software agents, collectively managing the cloud application. Each agent encapsulates knowledge of how to manage specific parts of the cloud application, is driven by sending and receiving cloud models, and collaborates with other agents by communicating using conversations. The entirety of communication and collaboration in this collection is called the orchestrator conversation. A thorough evaluation shows the orchestrator conversation makes it possible to encapsulate IT operations knowledge that current solutions cannot, reduces the complexity of managing a cloud application, and happens inherently concurrent. The evaluation also shows that the conversation figures out how to deploy a single big data cluster in less than 100 milliseconds, which scales linearly to less than 10 seconds for 100 clusters, resulting in a minimal overhead compared with the deployment time of at least 20 minutes with the state of the art. INTRODUCTIONManaging cloud applications is complex. System administrators (sysadmins) need to have an in-depth understanding of all the components of the cloud application such as the operating system, webserver, and X.509 certificates. Having such deep knowledge about how to deploy, configure, monitor, and manage these components is almost impossible in the field of big data because of the size of the ecosystem, the complexity of the tools involved, and the rapid pace of innovation. This would not be such a big problem if it was not for the large skills shortage in the fields of IT operations 1 and big data. 2 There is thus a need for the ability to share and reuse the knowledge of sysadmins across teams and companies.Sharing IT knowledge is not a new concept. The field of software development, for example, has a big focus on sharing and reusing knowledge in the form of code libraries. Over the years, a vast number of code libraries have been created that encapsulate an enormous amount of knowledge. Developers use these libraries to quickly write software without having Int J Network Mgmt. 2018;28:e2036.wileyonlinelibrary.com/journal/nem

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Reliable self-deployment of distributed cloud applications

Cited by 15 publications

References 41 publications

Rigorous Design and Deployment of IoT Applications

Rigorous Design and Deployment of IoT Applications

Resilience of Stateful IoT Applications in a Dynamic Fog Environment

Orchestrator conversation: Distributed management of cloud applications

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