José Neuman de Souza

Elasticity in cloud computing: a survey

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, there is a lack of a detailed analysis about elasticity for the cloud. As an attempt to fill this gap, we propose this survey on cloud computing elasticity based on an adaptation of a classic systematic review. We address different aspects of elasticity, such as definitions, metrics and tools for measuring, evaluation of the elasticity, and existing solutions. Finally, we present some open issues and future directions. To the best of our knowledge, this is the first study on cloud computing elasticity using a systematic review approach.

A routing protocol based on energy and link quality for Internet of Things applications.

The Internet of Things (IoT) is attracting considerable attention from the universities, industries, citizens and governments for applications, such as healthcare, environmental monitoring and smart buildings. IoT enables network connectivity between smart devices at all times, everywhere, and about everything. In this context, Wireless Sensor Networks (WSNs) play an important role in increasing the ubiquity of networks with smart devices that are low-cost and easy to deploy. However, sensor nodes are restricted in terms of energy, processing and memory. Additionally, low-power radios are very sensitive to noise, interference and multipath distortions. In this context, this article proposes a routing protocol based on Routing by Energy and Link quality (REL) for IoT applications. To increase reliability and energy-efficiency, REL selects routes on the basis of a proposed end-to-end link quality estimator mechanism, residual energy and hop count. Furthermore, REL proposes an event-driven mechanism to provide load balancing and avoid the premature energy depletion of nodes/networks. Performance evaluations were carried out using simulation and testbed experiments to show the impact and benefits of REL in small and large-scale networks. The results show that REL increases the network lifetime and services availability, as well as the quality of service of IoT applications. It also provides an even distribution of scarce network resources and reduces the packet loss rate, compared with the performance of well-known protocols.

Improving Prediction Accuracy for WSN Data Reduction by Applying Multivariate Spatio-Temporal Correlation

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 involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, our proposal outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction. To the best of our knowledge, we believe that we are probably the first to address prediction based on multivariate correlation for WSN data reduction.

The Design of a New Policy Model to Support Ontology-Driven Reasoning for Autonomic Networking

The purpose of autonomic networking is to manage the business and technical complexity of networked components and systems. However, the lack of a common lingua franca makes it impossible to use vendor-specific network management data to ascertain the state of the network at any given time. Furthermore, the tools used to analyze management data, which include information and data models, ontologies, machine learning algorithms, and policy languages, are all different, and hence require different data in different formats. This paper describes a new version of the Directory Enabled Networks next generation (DEN-ng) policy model, which is part of the FOCALE autonomic network architecture. This new policy model has been built using three guiding principles: (1) the policy model is rooted in information models, so that it can govern managed entities, (2) the model is expressly constructed to facilitate the generation of ontologies, so that reasoning about policies constructed from the model may be done, and (3) the model is expressly constructed so that a policy language can be developed from it.

WSNs clustering based on semantic neighborhood relationships

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. We conduct experiments in order to evaluate the proposal in two different scenarios of damage with different data aggregation methods. We also compared our proposal, using the same data set, with a deterministic clustering method and with the LEACH algorithm. The results indicate that our approach is an energy-efficient clustering method for WSNs, outperforming both the deterministic clustering and LEACH algorithms in about 70% and 47% of energy savings respectively. The energy saving comes from the fact that we have a more efficient in-network data aggregation process since by exploiting the semantic relation between sensor nodes we can potentially aggregate more similar data and consequently, decrease the data redundancy (thus minimizing transmissions). Nodes that are semantically unrelated can operate in low-duty cycle, further reducing the energy consumption. Moreover, our proposal has the potential to improve the data accuracy provided for the application where accuracy is a QoS requirement in typical WSN applications.

A semantic middleware for autonomic wireless sensor networks

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 semantic neighborhoods relationships. The middleware was tailored to provide support for Structural Health Monitoring applications. However, it has a flexible architecture and it can be extensible to several other application domains such as ambient intelligence, habitat monitoring and fire detection. We use the oil platform structural health monitoring domain as a case study. The paper presents the middleware architecture and the proposed ontologies.

The design of a novel context-aware policy model to support machine-based learning and reasoning

The purpose of autonomic networking is to manage the business and technical complexity of networked components and systems. However, the lack of a common lingua franca makes it impossible to use vendor-specific network management data to ascertain the state of the network at any given time. Furthermore, the tools used to analyze management data are all different, and hence require different data in different formats. This complicates the construction of context from diverse information sources. This paper describes a new version of the DEN-ng context-aware policy model, which is part of the FOCALE autonomic network architecture. This model has been built using three guiding principles: (1) both the context model and the policy model are rooted in information models, so that they can govern managed entities, (2) each model is expressly constructed to facilitate the generation of ontologies, so that reasoning about policies constructed from the model may be done, and (3) the model is expressly constructed so that a policy language that supports machine-based reasoning and learning can be developed from it.

A Systematic Review of Shared Sensor Networks

While Wireless Sensor Networks (WSNs) have been traditionally tasked with single applications, in recent years we have witnessed the emergence of Shared Sensor Networks (SSNs) as integrated cyber-physical system infrastructures for a multitude of applications. Instead of assuming an application-specific network design, SSNs allow the underlying infrastructure to be shared among multiple applications that can potentially belong to different users. On one hand, a potential benefit of such a design approach is to increase the utilization of sensing and communication resources, whenever the underlying network infrastructure covers the same geographic area and the sensor nodes monitor the same physical variables of common interest for different applications. On the other hand, compared with the existing application-specific design, the SSNs approach poses several research challenges with regard to different aspects of WSNs. In this article, we present a systematic literature survey on SSNs. The main goal of the article is to provide the reader with the opportunity to understand what has been done and what remains as open issues in this field, as well as which are the pivotal factors of this evolutionary design and how this kind of design can be exploited by a wide range of WSN applications.

EPMOSt: An Energy-Efficient Passive Monitoring System for Wireless Sensor Networks

Monitoring systems are important for debugging and analyzing Wireless Sensor Networks (WSN). In passive monitoring, a monitoring network needs to be deployed in addition to the network to be monitored, named the target network. The monitoring network captures and analyzes packets transmitted by the target network. An energy-efficient passive monitoring system is necessary when we need to monitor a WSN in a real scenario because the lifetime of the monitoring network is extended and, consequently, the target network benefits from the monitoring for a longer time. In this work, we have identified, analyzed and compared the main passive monitoring systems proposed for WSN. During our research, we did not identify any passive monitoring system for WSN that aims to reduce the energy consumption of the monitoring network. Therefore, we propose an Energy-efficient Passive MOnitoring SysTem for WSN named EPMOSt that provides monitoring information using a Simple Network Management Protocol (SNMP) agent. Thus, any management tool that supports the SNMP protocol can be integrated with this monitoring system. Experiments with real sensors were performed in several scenarios. The results obtained show the energy efficiency of the proposed monitoring system and the viability of using it to monitor WSN in real scenarios.

Exploiting the power of OSI management for the control of SNMP-capable resources using generic application level gateways

A major aspect of Open Systems’ network management is the inter-working between distinct Management architectures. This paper details the development of a generic object oriented application level gateway that achieves seamless coexistence between OSI and SNMPv1 management systems. The work builds upon the Network Management Forum’s `ISO/CCITT and Internet Management Coexistence’ activities. The power of the OSI Systems Management Functions is made available for the management of SNMPvl based resources, bringing fully event driven management to the SNMP domain.