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- RELOAD/CoAP architecture for the federation of wireless sensor networksPublication . Pisco, Luís; Guerreiro, Joel; Correia, NoéliaSensing devices are expected to interconnect over large geographical areas and federations of wireless sensor networks are expected in a near future. In such environments a critical issue is how to discover the resources available at devices in a scalable manner. For this purpose, a Constrained Application Protocol (CoAP) Usage for REsource LOcation And Discovery (RELOAD), a generic self-organizing Peer-to-Peer (P2P) overlay network service, has been defined to be used as a lookup service, to store available device resources and as a cache for sensor data. Each P2P resource, at the RELOAD/CoAP overlay, includes references to device resources, hosted at one or more constrained nodes, but no provision is made for the insertion of bindings/references to P2P resources already available at the P2P overlay network. Such feature would increase the efficiency and consistency of storage, avoiding duplicate references, a very relevant issue for future IoT applications relying on the federation of wireless sensor networks. In this article an extension to the service provided by CoAP Usage is proposed so that resource bindings can be managed. Two binding models, and a heuristic algorithm for their implementation, are proposed. Results show that such models lead to a better resource organization, reducing the number of sensor resource entries and/or fetches to the P2P overlay.
- Allocation of resources in SAaaS Clouds managing thing mashupsPublication . Guerreiro, Joel; Rodrigues, Luis; Correia, NoéliaThe 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 cloud-based 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 quickly solve the problem.