A multi-layer parametric approach to maximize the access probability of mobile networks

Next-generation mobile networks (5G) are defined to provide access in the framework of heterogeneous systems where it is crucial to have “always on” and “everywhere connectivity” capabilities. This is of fundamental importance even in 4G mobile systems, down to 3G and also Wi-Fi and WiMAX. In order to guarantee access to users with handheld devices equipped with multiple radio interfaces, an automated and reconfigurable tool for selecting the best network to be connected with is needed. This should be achieved by avoiding service outages. Current vertical handovers, i.e., switching from a network to another, are essentially based on power received levels and often do not avoid temporary service outages. We propose in this paper a procedure to access mobile networks by sensing multiple performance parameters related to networks available in the considered area. We target at maximizing the probability of accessing the wireless medium despite the technology used. We develop an algorithm, based on dynamic programming, able to select the most suitable network. We present the performance of the proposed algorithm both on the basis of computer simulations and on tests performed in an Arduino-based hardware platform

CLEVER: a cooperative and cross-layer approach to video streaming in HetNets

We investigate the problem of providing a video streaming service to mobile users in an heterogeneous cellular network composed of micro e-NodeBs (eNBs) and macro e-NodeBs (MeNBs). More in detail, we target a cross-layer dynamic allocation of the bandwidth resources available over a set of eNBs and one MeNB, with the goal of reducing the delay per chunk experienced by users. After optimally formulating the problem of minimizing the chunk delay, we detail the Cross LayEr Video stReaming (CLEVER) algorithm, to practically tackle it. CLEVER makes allocation decisions on the basis of information retrieved from the application layer aswell as from lower layers. Results, obtained over two representative case studies, show that CLEVER is able to limit the chunk delay, while also reducing the amount of bandwidth reserved for offloaded users on the MeNB, as well as the number of offloaded users. In addition, we show that CLEVER performs clearly better than two selected reference algorithms, while being very close to a best bound. Finally, we show that our solution is able to achieve high fairness indexes and good levels of Quality of Experience (QoE)

Adaptive data synchronization algorithm for IoT-oriented low-power wide-area networks

The Internet of Things (IoT) is by now very close to be realized, leading the world towards a new technological era where people’s lives and habits will be definitively revolutionized. Furthermore, the incoming 5G technology promises significant enhancements concerning the Quality of Service (QoS) in mobile communications. Having billions of devices simultaneously connected has opened new challenges about network management and data exchange rules that need to be tailored to the characteristics of the considered scenario. A large part of the IoT market is pointing to Low-Power Wide-Area Networks (LPWANs) representing the infrastructure for several applications having energy saving as a mandatory goal besides other aspects of QoS. In this context, we propose a low-power IoT-oriented file synchronization protocol that, by dynamically optimizing the amount of data to be transferred, limits the device level of interaction within the network, therefore extending the battery life. This protocol can be adopted with different Layer 2 technologies and provides energy savings at the IoT device level that can be exploited by different applications

Corporate governance codes: a review and research agenda

Manuscript Type: Review Research Question/Issue: This study reviews previous country-level and firm-level studies on corporate governance codes up to 2014 in order to highlight recent trends and indicate future avenues of research. Research Findings/Results: Our data show that research on codes increases over time consistently with the diffusion and the relevance of the empirical phenomenon. Despite previous studies have substantially enriched our knowledge of the antecedents and the consequences of governance codes, our study shows there are still several opportunities for making significant contributions in this area. Theoretical Implications: Agency theory is the dominant theoretical framework, although other theoretical perspectives (especially the institutional one) are increasingly adopted. Future studies should be aimed at widening and combining various theoretical lenses so as to develop new interpretations and a better understanding of governance codes. Practical Implications: Legislators and policy makers should continue to develop and update the recommendations of national governance codes in order to address the potential failures of corporate governance mechanisms in place

Special issue on “Modeling and Performance Evaluation of Wireless Ad-Hoc Networks”

A primary aim of wireless ad-hoc networks is to deliver data in areas where there is no pre-defined infrastructure. In these networks, the users, but also the network entities can be potentially mobile. Wireless ad-hoc networks have recently witnessed their fastest growth period ever in history. Real wireless ad-hoc networks are now implemented, deployed and tested, and this trend is likely to increase in the future. However, as such networks are increasingly complex, performance modeling and evaluation play a crucial part in their design process to ensure their successful deployment and exploitation in practice. This special issue on Modeling and Performance Evaluation of Wireless Ad-Hoc Networks aims to open a new critical debate on the evaluation of wireless ad-hoc networks. It includes original theoretical and/or practical contributions, from researchers and practitioners that identify and address issues in evaluating wireless ad-hoc networks.Peer ReviewedPostprint (author's final draft

Improving Wireless Access Control Schemes via Adaptive Power Regulation

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What is the best spatial distribution to model base station density? A deep dive into two european mobile networks

This paper studies the base station (BS) spatial distributions across different scenarios in urban, rural, and coastal zones, based on real BS deployment data sets obtained from two European countries (i.e., Italy and Croatia). Basically, this paper takes into account different representative statistical distributions to characterize the probability density function of the BS spatial density, including Poisson, generalized Pareto, Weibull, lognormal, and \alpha -Stable. Based on a thorough comparison with real data sets, our results clearly assess that the \alpha -Stable distribution is the most accurate one among the other candidates in urban scenarios. This finding is confirmed across different sample area sizes, operators, and cellular technologies (GSM/UMTS/LTE). On the other hand, the lognormal and Weibull distributions tend to fit better the real ones in rural and coastal scenarios. We believe that the results of this paper can be exploited to derive fruitful guidelines for BS deployment in a cellular network design, providing various network performance metrics, such as coverage probability, transmission success probability, throughput, and delay

Exploratory approach for network behavior clustering in LoRaWAN

The interest in the Internet of Things (IoT) is increasing both as for research and market perspectives. Worldwide, we are witnessing the deployment of several IoT networks for different applications, spanning from home automation to smart cities. The majority of these IoT deployments were quickly set up with the aim of providing connectivity without deeply engineering the infrastructure to optimize the network efficiency and scalability. The interest is now moving towards the analysis of the behavior of such systems in order to characterize and improve their functionality. In these IoT systems, many data related to device and human interactions are stored in databases, as well as IoT information related to the network level (wireless or wired) is gathered by the network operators. In this paper, we provide a systematic approach to process network data gathered from a wide area IoT wireless platform based on LoRaWAN (Long Range Wide Area Network). Our study can be used for profiling IoT devices, in order to group them according to their characteristics, as well as detecting network anomalies. Specifically, we use the k-means algorithm to group LoRaWAN packets according to their radio and network behavior. We tested our approach on a real LoRaWAN network where the entire captured traffic is stored in a proprietary database. Quite important is the fact that LoRaWAN captures, via the wireless interface, packets of multiple operators. Indeed our analysis was performed on 997, 183 packets with 2169 devices involved and only a subset of them were known by the considered operator, meaning that an operator cannot control the whole behavior of the system but on the contrary has to observe it. We were able to analyze clusters’ contents, revealing results both in line with the current network behavior and alerts on malfunctioning devices, remarking the reliability of the proposed approach