The Sensing as a Service is emerging as a new Internet of Things (IoT) business model for sensors and data sharing in the cloud. Under this paradigm, a resource allocation model for the assignment of both sensors and cloud resources to clients/applications is proposed. This model, contrarily to previous approaches, is adequate for emerging IoT Sensing as a Service business models supporting multi-sensing applications and mashups of Things in the cloud. A heuristic algorithm is also proposed having this model as a basis. Results show that the approach is able to incorporate strategies that lead to the allocation of fewer devices, while selecting the most adequate ones for application needs.

The sensing and actuation as-a-service is an emerging business model to make sensors, actuators and data from the Internet of Things more attainable to everyday consumer. With the increase in the number of accessible Things, mashups can be created to combine services/data from one or multiple Things with services/data from virtual Web resources. These may involve complex tasks, with high computation requirements, and for this reason cloud infrastructures are envisaged as the most appropriate solution for storage and processing. This means that cloudbased services should be prepared to manage Thing mashups. Mashup management within the cloud allows not only the optimization of resources but also the reduction of the delay associated with data travel between client applications and the cloud. In this article, an optimization model is developed for the optimal allocation of resources in clouds under the sensing and actuation as-a-service paradigm. A heuristic algorithm is also proposed to solve the problem more quickly.

Abstract-M2M communication is expected to occur at a global level and for this reason federations of device networks are also expected. In such large scale environments, a critical issue is how to discover the available resources in a scalable manner. For this purpose CoAP Usage for RELOAD, a generic selforganizing P2P overlay network service, has been proposed to be used as a lookup service, to store available resources and as a cache for sensor data. However, such approach alone does not allow building an aggregate resource hierarchy, a very relevant issue for an efficient organization of data in future IoT applications. Here we address this issue and propose an architecture incorporating a resource aggregation/disaggregation service.

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