Danielo Goncalves Gomes

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This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for wireless sensor networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate. Simulations were made(More)
Cloud computing is now a well-consolidated paradigm for on-demand services provisioning on a pay-as-you-go model. Elasticity, one of the major benefits required for this computing model, is the ability to add and remove resources “on the fly” to handle the load variation. Although many works in literature have surveyed cloud computing and its features,(More)
In this paper we present a proposal that combines the benefits of autonomic and semantic sensor networks to build a semantic middleware for autonomic wireless sensor networks. The key feature of the proposed middleware is a rule-based reasoning engine based on ontology and fuzzy logic. We also propose a semantic-aware topology control based on computing(More)
We propose a semantic clustering model based on a fuzzy inference system to find out the semantic neighborhood relationships in wireless sensor networks in order to both reduce energy consumption and improve the data accuracy. As a case study we describe a structural health monitoring application which was used to illustrate and assess the proposed model.(More)
This paper proposes an architecture to handle the allocation of virtual machines based on the processing power for heterogeneous Clouds, where there is a wide variety of CPU types. Our major contribution is a novel representation of the processing capacity in terms of the Processing Unit (PU) and the CPU usage limitation in order to isolate the processing(More)
Wireless Sensor Networks have critical resource constraints and minimizing resources usage is crucial to extend the network lifetime. Energy saving in WSNs can be achieved through several techniques, such as topology control and clustering, to provide a longer lifetime and scalability to the network. In this paper we propose a semantic clustering model(More)
Simple linear regression is usually used for WSN data reduction. The mechanism is concerned about energy consumption, but neglects the prediction accuracy. The prediction error from it is often ignored and inconsistencies are forwarded to the user application. This paper proposes to use a method based on multiple linear regression to improve prediction(More)
The concepts and designs of 4WARD project for the Future Internet involve a clean-slate architecture with various networking innovations, including a new connectivity paradigm called Generic Path (GP). In GP architecture, several facilities are designed to efficiently support complex value-added applications and services with assured Quality of Service(More)