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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)
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)
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)
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)
Elasticity is a key feature of cloud computing. Its application has become an increasing need due to the dynamic nature of different applications and different workloads imposed by them. This article aims to analyze the behavior of the elasticity in a cloud computing environment, based on some metrics related to response time of allocation operations and(More)
When dealing with Wireless Sensor Networks (WSN) applications that demand a high level cooperation of the sensor nodes, time synchronization is necessary to provide the correctness required for their results. In this work, we show that common issues between routing and time synchronization processes make their integration possible and, thus, can solve the(More)
Regarding the size and the complexity growth of today's networks, several network management models have been studied and proposed. Furthermore, new requirements emerge with the interaction among entities that compose the management system, such as interoperability, collaboration among managers geographically separated, resources sharing, load balancing and(More)