Abstract
The Internet of Things (IoT) has enabled physical objects and devices, often referred to as things, to connect and communicate. This has opened up for the development of novel types of services that improve the quality of our daily lives. The dynamicity and uncertainty of IoT environments, including the mobility of users and devices, make it hard to foresee at design time available things and services. Further, users should be able to achieve their goals seamlessly in arbitrary environments. To address these challenges, we exploit Artificial Intelligence (AI) to engineer smart IoT systems that can achieve user goals and cope with the dynamicity and uncertainty of their environments. More specifically, the main contribution of this paper is an approach that leverages the notion of Belief-Desire-Intention agents and Machine Learning (ML) techniques to realize Emergent Configurations (ECs) in the IoT. An EC is an IoT system composed of a dynamic set of things that connect and cooperate temporarily to achieve a user goal. The approach enables the distributed formation, enactment, adaptation of ECs, and conflict resolution among them. We present a conceptual model of the entities of the approach, its underlying processes, and the guidelines for using it. Moreover, we report about the simulations conducted to validate the feasibility of the approach and evaluate its scalability.
Highlights
The Internet of Things (IoT) has enabled physical objects and devices such as sensors, actuators, and appliances, to connect and collaborate to achieve users’ goals
If an application-agent has a concrete schema that can be used to achieve a high-level task, it evaluates if the things it manages meet the constraints of adopting the roles in the schema, have the capabilities to perform the roles’ tasks, and the preconditions of those capabilities are satisfied in the context
More processing and storage capabilities should be dedicated to deploying an Emergent Configurations Manager (ECM) that supports the realization of Emergent Configurations (ECs) in a smart building than those needed to perform the same task in a smart home
Summary
The Internet of Things (IoT) has enabled physical objects and devices such as sensors, actuators, and appliances, to connect and collaborate to achieve users’ goals. We propose an approach that exploits the notion of Belief-Desire-Intention (BDI) agents [2] to realize Emergent Configurations (ECs) in the IoT. BDI-based agents are autonomous, goal-directed, context-aware, and can communicate and collaborate to form Multi-Agent Systems (MAS) These characteristics make them very suitable to be exploited for realizing ECs [7,8,9]. Our approach adopts a distributed architecture, enables both reactive and proactive adaptations of ECs, and contributes towards automating the achievement of users’ goals by leveraging autonomous agents that act on behalf of the users.
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