In this work we present a calibration-free system for locating wireless local area network devices, based on the radio frequency characteristics of such networks. Calibration procedures are applied in a great number of proposed location techniques and are considered to be not practical or a considerable barrier to wider adoption of such methods. Thus, we addressed issues related to some aspects of location systems through, an architecture based on wireless sniffers and by constructing a location model based on signal propagation models, in which its parameters are calculated in real time. This guarantee good self-sufficiency and adaptation capacity to the proposed system, once it does not need human intervention to work, neither from the network administrator or the wireless user being located. Moreover, a probabilistic method was used for estimating wireless devices positions, based on the previous constructed model. We later demonstrate the feasibility of our approach by reporting results of field tests in which the proposed technique was implemented and validated in a real-world indoor environment.

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Internet of Things (IoT) has gained increasing visibility among emerging technologies and undoubtedly changing our daily life. Its adoption is strengthened by the growth of connected devices (things) as shown in recent statistics. However, as the number of connected things grows, responsibility related to security aspects also needs to increase. For instance, cyberattacks might happen if simple authentication mechanisms are not implemented on IoT applications, or if access control mechanisms are weakly defined. Considering the relevance of the subject, we performed a systematic literature review (SLR) to identify and synthesize security issues in IoT discussed in scientific papers published within a period of 8 years. Our literature review focused on four main security aspects, namely authentication, access control, data protection, and trust. We believe that a study considering these topics has the potential to reveal important opportunities and trends related to IoT security. In particular, we aim to identify open issues and technological trends that might guide future studies in this field, thus providing useful material both to researchers and to managers and developers of IoT systems. In this paper, we describe the protocol adopted to perform the SLR and present the state-of-the-art on the field by describing the main techniques reported in the retrieved studies. To the best of our knowledge, ours is the first study to compile information on a comprehensive set of security aspects in IoT. Moreover, we discuss the placement, in terms of architectural tiers, for deploying security techniques, in an attempt to provide guidelines to help design decisions of security solution developers. We summarize our results showing security trends and research gaps that can be explored in future studies.

Abstract-Mobility Models try to represent the movement behavior of devices in Mobile Ad hoc Networks. These models are used in performance evaluation of applications and communication systems, allowing the analysis of the mobility's impact. In this context, two individual mobility models for Mobile Ad hoc Networks are proposed in this paper. These models were based in [1] and intend to represent a wider movement capability. Using the proposed models it is possible to move in the same direction, in adjacent directions, to accelerate and to stop, avoiding sharp turns and sudden stops. This way, it is tried a closer representation to the real movement of the users in urban enviroments and roads. In this paper, the models are described analytically by Markov Chains. Besides that, some comparisions between the proposed models, the Waypoint model and the Random Walk model are presented through the use of simulations. *