Priscila Solís Barreto

IEEE802.11b/g Standard: Theoretical Maximum Throughput

Estimating the throughput of an WiFi connection can be quite complex, even when considering simplified scenarios. Indeed, the varying number of parameters specified in the standards makes it hard to understand their impact in terms of delay and throughput. The main contribution of this work is to present a simple scheme to compute the exact maximum throughput for an IEEE 802.11g network. The proposed scheme incorporates all the timings and settings which allows one to calculate the throughput for different channel spacing and modulation techniques specified in the standard. Numerical and experimental results showing the accuracy of the proposed scheme are also presented.

A traffic characterization procedure for multimedia applications in converged networks

This work presents a traffic characterization procedure for traffic engineering (TE) in converged networks. An analytical model, focused in a self-similar aggregated traffic characterization is proposed, which considers QoS restrictions for delay metrics. The model, together with evolutionary techniques, is used for the optimization of the link capacity assignment task in network planning with multi-service applications. The results show that the traffic characterization model is reliable as a part of the optimization of costs in converged networks.

Network Planning Optimization for Multimedia Networks

This work presents a planning methodology for multimedia networks based on a hybrid traffic model and an evolutionary optimization procedure. The methodology intends to optimize the sizing of network elements to comply with two QoS simultaneous network parameters as well as to promote network stability and cost efficiency. The hybrid traffic model deals with the multimedia network traffic as a combination of fBm (fractional Brownian motion) and Markovian process. Also, the model considers the links loads and variance coefficients to produce more accurate Qos metrics values for network delay and packet loss probability. The traffic model characterization accuracy was evaluated with an optimization procedure that sizes network elements to fulfill performance and cost requirements. The simulations results show that the methodology may have a practical use for sizing network elements and promoting stability.

Hybrid Traffic Model for Multimedia Network Performance Evaluation

This work proposes a hybrid traffic model for multimedia networks as a fundamental element in a network planning optimization procedure. The proposed model uses a combination of the fBm (fractional Brownian motion) and Markovian traffic characterization procedures combined with link parameters in order to produce more accurate values of QoS metrics. The hybrid traffic model was evaluated in a network scenario that aggregates different traffic types with different combinations of Hurst parameters and variance coefficients. The results show that the QoS metrics calculated with the hybrid traffic model appear to be more accurate than the ones obtained exclusively with the fBm or the Markovian models. With these results, the proposed model appears to be useful in network planning optimization methods. .

Evaluation of Distributed Denial of Service threat in the Internet of Things

There is a concern about possible threats deriving from the widespread adoption of IoT (Internet of Things). The number of devices connected to the Internet is going to increase dramatically, potentiating their security risks. A Distributed Denial of Service (DDoS) attack is a good candidate to explore IoT security vulnerabilities, because of the enormous number of new devices connected to the Internet there is also an increase in the number of possible compromised devices. This study aims to analyze the efficiency of a DDoS attack in a typical IoT environment, by using simulations that, in the best of our knowledge, have not been conducted yet.

IP and 3G Bandwidth Management Strategies Applied to Capacity Planning

This chapter discusses the application of methodologies to plan and design IP Backbones and 3G access networks for todays Internet world. The recent trend of the multi-frequency band operations for mobile communication systems requires increasingly bandwidth capacity in terms of core and access. The network planning task needs mathematical models to forecast network capacity that match the service demands. As the nature of network usage changed, to explain and forecast the network growth, new methods are needed. In this chapter, we will discuss some strategies to optimize the bandwidth management of a real service provider IP/MPLS backbone and later we will propose a method for traffic engineering in a national IP backbone.

A Planning and Adaptive Routing Methodology for Multimedia Networks

This work presents a traffic engineering proposal based on a network planning and adaptive routing strategy for multimedia networks. The proposal uses a hybrid traffic model based on fBm (fractional Brownian motion) and Markovian processes to characterize the multimedia traffic and calculate QoS metrics and effective bandwidth. The routing strategy was evaluated in a scenario with different Poisson and self-similar aggregated traffic series. The results show that the proposed methodoly achieves the established QoS requirements and promotes a better load balancing in the network.

Network Planning and Adaptive Routing for Multimedia Traffic

This work presents a methodology for network traffic engineering based on a hybrid traffic model and an adaptive routing algorithm. The hybrid traffic model pursuits the calculation of more accurate Qos metrics and effective bandwidth for multimedia traffic in order to optimize the sizing of network elements at a minimal cost. During network operation, the links weighted values are modified to compute shortest path routing algorithms in an adaptive manner to comply with the traffic effective bandwidth and QoS requirements. The network routing methodology was evaluated in a network topology that aggregates different traffic types, Poisson and self-similar. The results show that the proposed methodology achieves the QoS requirements and promotes a more efficient traffic balancing within the network.

Device-Based Security to Improve User Privacy in the Internet of Things †

The use of Internet of Things (IoT) is rapidly growing and a huge amount of data is being generated by IoT devices. Cloud computing is a natural candidate to handle this data since it has enough power and capacity to process, store and control data access. Moreover, this approach brings several benefits to the IoT, such as the aggregation of all IoT data in a common place and the use of cloud services to consume this data and provide useful applications. However, enforcing user privacy when sending sensitive information to the cloud is a challenge. This work presents and evaluates an architecture to provide privacy in the integration of IoT and cloud computing. The proposed architecture, called PROTeCt—Privacy aRquitecture for integratiOn of internet of Things and Cloud computing, improves user privacy by implementing privacy enforcement at the IoT devices instead of at the gateway, as is usually done. Consequently, the proposed approach improves both system security and fault tolerance, since it removes the single point of failure (gateway). The proposed architecture is evaluated through an analytical analysis and simulations with severely constrained devices, where delay and energy consumption are evaluated and compared to other architectures. The obtained results show the practical feasibility of the proposed solutions and demonstrate that the overheads introduced in the IoT devices are worthwhile considering the increased level of privacy and security.The use of Internet of Things (IoT) is rapidly growing and a huge amount of data is being generated by IoT devices. Cloud computing is a natural candidate to handle this data since it has enough power and capacity to process, store and control data access. Moreover, this approach brings several benefits to the IoT, such as the aggregation of all IoT data in a common place and the use of cloud services to consume this data and provide useful applications. However, enforcing user privacy when sending sensitive information to the cloud is a challenge. This work presents and evaluates an architecture to provide privacy in the integration of IoT and cloud computing. The proposed architecture, called PROTeCt—Privacy aRquitecture for integratiOn of internet of Things and Cloud computing, improves user privacy by implementing privacy enforcement at the IoT devices instead of at the gateway, as is usually done. Consequently, the proposed approach improves both system security and fault tolerance, since it removes the single point of failure (gateway). The proposed architecture is evaluated through an analytical analysis and simulations with severely constrained devices, where delay and energy consumption are evaluated and compared to other architectures. The obtained results show the practical feasibility of the proposed solutions and demonstrate that the overheads introduced in the IoT devices are worthwhile considering the increased level of privacy and security.

Evaluating the Impact of Management Traffic and Self-Similarity on Wireless Network Performance

This article makes a taxonomic study of wireless traffic using a model of self-similarity based on traffic components at the link, network and transport layer. We evaluate applications performance using two different simulation scenarios in which the traffic is defined according to the statistical parameters observed in real traffic. The simulations evaluate network performance using different compositions of wireless management traffic and several degrees of self-similarity. The results show a better performance for delay and loss when certain management traffic components are removed, even for the cases when the traffic is self-similar. The results may help to identify unwanted management traffic components for certain network scenarios.