Adaptive Middleware of Things

Cavalcanti, David; Carvalho, Ranieri; Rosa, Nelson

doi:10.1109/iscc53001.2021.9631408

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…Previous research on the so-called adaptive middleware can indeed contribute to support dynamic adaptation in PIS, including proposals on context-aware applications (Huebscher and McCann, 2006), ubiquitous computing (Yau and Karim, 2004), wireless sensor networks (Portocarrero et al, 2016), IoT (Cavalcanti et al, 2021), cyber-physical systems (García-Vallis and Baldoni, 2015), and cloud computing (Rafique et al, 2017). Adaptive middleware can be defined as a kind of middleware that enables modifying the behavior of a distributed application in response to changes in requirements or operating conditions (Sadjadi and McKinley, 2003).…”

Section: Pis Adaptive Middlewarementioning

confidence: 99%

Middleware Supporting PIS: Requirements, Solutions, and Challenges

Taconet

Batista

Borges

et al. 2022

The Evolution of Pervasive Information Systems

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Section: Pis Adaptive Middlewarementioning

confidence: 99%

Middleware Supporting PIS: Requirements, Solutions, and Challenges

Taconet

Batista

Borges

et al. 2022

The Evolution of Pervasive Information Systems

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“…The development of adaptive middleware is not a new topic in the middleware community [4]. Adaptive middleware systems are widely utilised in several application domains and computing environments, such as cloud [6], wireless sensor networks [14] and Internet of Things [5], just to mention the most important ones. Despite the diversity of existing adaptive middleware systems, developing control-theoretical solutions is not common in this research field.…”

Section: Introductionmentioning

confidence: 99%

Using Controllers to Adapt Messaging Systems: An Initial Experience

Rosa¹,

Cavalcanti²

2022

Anais Do X Workshop De Visualização, Evolução E Manutenção De Software (VEM 2022)

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Adaptive middleware systems have been designed for various computing environments, including wireless sensor networks, IoT and cloud computing. Whatever the environment, however, the adaptation logic of these middleware systems rarely adopts control theory concepts. To shed some light on this topic, this paper presents the steps to using control theory in implementing an adaptive mechanism for a popular middleware model: message-oriented middleware, also known as messaging systems. These steps have been employed in a widely adopted open-source messaging system named RabbitMQ. This paper’s contributions are on how to employ control theory step-by-step in messaging systems, along with some initial results on using P, PI and PID controllers.

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Customizable and adaptable middleware of things

Cavalcanti,

Rosa

2024

Int J Communication

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SummaryMiddleware has become an essential element in the construction of distributed Internet of Things (IoT) applications. While it plays a central role in hiding the complexities of distribution, middleware systems have also been responsible for dealing with the uncertainties in IoT environments, such as changes during operation (e.g., inaccuracies in sensor data collection) and fluctuations in resource availability, for example, the battery. These uncertainties demand attention as they can result in application failures or, even worse, jeopardize the safety of applications. Existing middleware systems are being enhanced with self‐adaptive capabilities to address these uncertainties. It means they can make runtime adjustments to the middleware and applications (built atop them) without complete shutdowns. Despite the variety of available adaptive solutions, IoT applications often face uncertainties, each requiring a distinct adaptive action. For instance, the need to fine‐tune a thing's workload due to battery consumption is a common challenge. Furthermore, these applications are susceptible to changes occurring at various layers, presenting a complex challenge of managing them simultaneously. This paper introduces Middleware Extendify (MEx), a solution for building and executing IoT adaptive middleware systems. MEx simplifies the implementation of middleware and provides an underlying environment that executes the middleware and supports a range of adaptation mechanisms. This approach ensures that the middleware meets the evolving demands of applications and copes with changes at runtime. The evaluation of MEx encompasses different adaptive middleware implementations to measure the impact of the proposed adaptation mechanisms. The results indicate that adaptation comes with acceptable performance costs while offering the ability to fine‐tune middleware functionality or align IoT applications more effectively.

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Adaptive Middleware of Things

Cited by 4 publications

References 16 publications

Middleware Supporting PIS: Requirements, Solutions, and Challenges

Middleware Supporting PIS: Requirements, Solutions, and Challenges

Using Controllers to Adapt Messaging Systems: An Initial Experience

Customizable and adaptable middleware of things

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