Loading...
3 results
Search Results
Now showing 1 - 3 of 3
- Resource allocation model for sensor clouds under the sensing as a service paradigmPublication . Guerreiro, Joel; Rodrigues, Luis; Correia, NoéliaThe 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.
- Resource design in federated sensor networks using RELOAD/CoAP overlay architecturesPublication . Rodrigues, Luis; Guerreiro, Joel; Correia, NoéliaSensor networks can be federated for wide-area geographical coverage using RELOAD/CoAP architectures. In this case, proxy nodes of constrained environments form a P2P overlay to announce device resources or sensor data. Although this is a standard-based solution, consistency problems may arise because P2P resources (data objects stored at the overlay network) may end up including similar device resource entries. This is so because device resource entries, or sensor data, can be announced under different P2P resource umbrellas, meaning that any update to them will require changing multiple P2P resources. Here in this article, a multi-layer approach is proposed to solve this issue, allowing for a more efficient storage/retrieval of IoT data. Information at the overlay network is kept consistent, although additional P2P anonymous resources must be created. A mathematical model is proposed for the planning of such multi-layer organization of P2P resources, together with a heuristic algorithm. A required overlay service is also discussed.
- 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.