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An Actor-Based Formal Model and Runtime Environment for Resource-Bounded IoT Services

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With sensors becoming increasingly ubiquitous, there is tremendous potential for Internet of Things (IoT) services that can take advantage of the data collected by these sensors. Although there are a… Click to show full abstract

With sensors becoming increasingly ubiquitous, there is tremendous potential for Internet of Things (IoT) services that can take advantage of the data collected by these sensors. Although there are a growing number of technologies focused on IoT services, there is relatively limited foundational work on them. This is partly because of the lack of precise understanding, specification, and analysis of such services, and, consequently, there is limited platform support for programming them. In this paper, we present a formal model for understanding and enabling reasoning about distributed IoT services. The paper first studies the key properties of the IoT services profoundly, and then develops an approach for fine-grained resource coordination and control for such services. The resource model identifies the core mechanisms underlying IoT services, informing design and implementation decisions about them if implemented over a middleware or a platform. We took a multi-agent systems approach to represent IoT services, broadly founded in the actors model of concurrency. Actor-based services can be built by composing simpler services. Furthermore, we created a proximity model to represent an appropriate notion of IoT proximity. This model represents the dynamically evolving relationship between the service’s sensing and acting capabilities and the environments in which these capabilities are exercised. The paper also presents the design of a runtime environment to support the implementation of IoT services. Key mechanisms required by such services will be implemented in a distributed middleware.

Keywords: actor based; iot services; runtime environment; iot; formal model

Journal Title: Algorithms
Year Published: 2022

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