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One of the main characteristics of the DVB-S2/S2X standard is the capability of using the Adaptive Coding and Modulation (ACM) technique. Differently from Variable Coding and Modulation (VCM), ACM provides a feedback path in the return channel for dynamically varying protection error levels in accordance with different channel conditions. In this article, a double-layer packet scheduling mechanism able to support different QoS levels monitoring the propagation and channel conditions is proposed. It consists of a Two-Stage Scheduler (TSS) approach and proposes two novel schedulers to be used in the first and second stage: an Adaptive Priority-based Scheduling (APS) able to account QoS requirements is proposed for the first stage; an improved version of Proportional Fair queueing (PF) called PF with Padding and Packing (PF-PP), able to select and transmit in the forward link frames in accordance to an appropriate fair policy is designed for the second stage. Performed experiments show an improvement of the overall system performance in terms of packet drop rate, delay jitter, and packets delay.

The development of Directional Medium Access Control (DMAC) strategies that allow to enhance the limitations due to the use of omnidirectional antennas in Mobile ad Hoc Networks (MANET), introduces several issues that need to be properly addressed such as the Deafness problem. The use of Smart Antenna Systems (SAS) along with Directional Request To Send (DRTS) and Directional Clear To Send (DCTS) could be not sufficient to mitigate the Deafness. In this regard, a sectorized antenna approach together with a frame scheduling mechanism can improve the overall MAC performance while limiting the Deafness; however, the employment of scheduling algorithms without priority such as the Round Robin could limit the network performance especially in terms of Packet Delivery Ratio (PDR) and fairness. For this reason, we propose two approaches: the A-MSDU (Aggregation MAC Service Data Unit) MAC and a WRR (Weighted Round Robin) MAC that could allow to overcome the limitations of the Round Robin scheme applied at MAC layer in order to have an high efficiency in the overall resource allocation. More specifically, obtained results show that, through the use of frame aggregation, it is possible to considerably reduce issues implied by Round Robin such as time slice and network overhead; WRR approach, instead, is able to enhance the overall network fairness by reducing the number of collisions provided by a directional MAC based on Round Robin scheduling; this aspect translates into higher PDR performance compared to Round Robin approach.

In this paper, some collision avoidance systems based on MEC in a VANET environment are proposed and investigated. Micro services at edge are considered to support service continuity in vehicle communication and advertising. This considered system makes use of cloud and edge computing, allowing to switch communication from edge to cloud server and vice versa when possible, trying to guarantee the required constraints and balancing the communication among the servers. Simulation results were used to evaluate the performance of three considered mechanisms: the first one considering only edge with load balancing, the second one using edge/cloud switching and the third one using edge with load balancing and collision avoidance advertising.

Vehicle positioning is becoming an important issue related to Intelligent Transportation Systems (ITSs). Novel vehicles and autonomous vehicles need to be localized under different weather conditions and it is important to have a reliable positioning system to track vehicles. Satellite navigation systems can be a key technology in providing global coverage and providing localization services through many satellite constellations such as GPS, GLONASS, Galileo and so forth. However, the modeling of positioning and localization systems under different weather conditions is not a trivial objective especially considering different factors such as receiver sensitivity, dynamic weather conditions, propagation delay and so forth. This paper focuses on the use of simulators for performing different kinds of tests on Global Navigation Satellite System (GNSS) systems in order to reduce the cost of the positioning testing under different techniques or models. Simulation driven approach, combined with some specific hardware equipment such as receivers and transmitters can characterize a more realistic scenario and the simulation can consider other aspects that could be complex to really test. In this work, the main contribution is the introduction of the Troposphere Collins model in a GNSS simulator for VANET applications, the GPS-SDR-SIM software. The use of the Collins model in the simulator allows to improve the accuracy of the simulation experiments throughout the reduction of the receiver errors.

Many CSMA based MACs can abruptly degrade their performance when the optimized design parameters do not fit with the considered scenarios. The main issue is the lack of optimal adaptation of the MAC strategies to dynamic network conditions. Novel approaches based on learning, deep-learning, nature-inspired learning are gaining interest for their robustness to dynamic network conditions. In this paper, a simple adaptive MAC strategy based on the Q-learning has been proposed. Our proposal, called Q-CSMA, is able to dynamically tune the contention probability in a slotted CSMA to decrease the number of collisions, also reducing the packet latency. Q-CSMA has been compared with optimal $p$ -persistent CSMA (p-pers-CSMA/ $p$ *) and a sift-based CSMA (sift-CSMA).

Mobile Edge Computing (MEC) is a new network paradigm that allows resource management and IT services at the edge of a communication network and, so, closer to the devices guaranteeing low latency and high bandwidth requirements. This characteristic makes MEC paradigm suitable for critical communication services used in collaboration with container-based virtualization and with 5G networks. In this paper, an implementation of a collision avoidance system based on MEC in a VANET environment is proposed. This system makes use of cloud and edge computing and it is able to switch communication from edge to cloud server and vice versa when possible, trying to guarantee the required constraints and balancing the communication among the servers avoiding of overloading edge layer. The simulation results have proved how, in some cases, the MEC-5G combination is the best solution for avoiding collisions in a VANET environment.

This paper presents a novel data dissemination strategy called Geographic Energy-aware Epidemic Routing (GEER) in DTN network. This routing scheme tries to consider the residual node energy and degree centrality to dynamically select the number of nodes where forwarding data and it tries to preserve buffer space reducing the TTL of data sent on nodes with higher degree centrality. A novel estimation of node density differentiated for geographic area is proposed to improve the data forwarding and a buffer data discarding policy has been applied when network becomes congested. GEER has been compared with Energy Aware Epidemic Routing (EAER) and EpSoc routing scheme in terms of Data Packet delivery ratio, overhead and energy consumption.

This work addresses the coordination problem of multiple robots with the goal of finding specific hazardous targets in an unknown area and dealing with them cooperatively. The desired behaviour for the robotic system entails multiple requirements, which may also be conflicting. The paper presents the problem as a constrained bi-objective optimization problem in which mobile robots must perform two specific tasks of exploration and at same time cooperation and coordination for disarming the hazardous targets. These objectives are opposed goals, in which one may be favored, but only at the expense of the other. Therefore, a good trade-off must be found. For this purpose, a nature-inspired approach and an analytical mathematical model to solve this problem considering a single equivalent weighted objective function are presented. The results of proposed coordination model, simulated in a two dimensional terrain, are showed in order to assess the behaviour of the proposed solution to tackle this problem. We have analyzed the performance of the approach and the influence of the weights of the objective function under different conditions: static and dynamic. In this latter situation, the robots may fail under the stringent limited budget of energy or for hazardous events. The paper concludes with a critical discussion of the experimental results., Comment: 40 pages

Recently the topic of health monitoring is growing in interest and several applications and devices were designed and put on the markets. This interest is promoted by an increasing enthusiasm about physical activities to improve health and wellness. In this work, we present a wearable device able to collect data from different body sensors to send them towards a cloud platform. The Message Queuing Telemetry Transport MQTT communication protocol is used to send data by customizing the messages payload and building up a customized protocol between devices and cloud. These data, are used to recognize user activity and health status sending alerts when an anomaly is detected. These results can be used to monitor performances or to investigate anomalies discovered during activities. In addition, we propose a fuzzy-based Human Activity Recognition (HAR) classifier which continuously acquire data from body sensors exploiting an Internet of Things (IoT) architecture. In order to improve HAR, different classes of data filters have been analyzed to reduce the amount of data sent to the cloud. These filters introduce smart functionalities at the edge of the network reducing the data-flow without compromising the classifier goodness. A smart device based on embedded technologies is designed to realize the wearable device.

Smart Antenna Systems (SAS) are largely employed in wireless networks for their capabilities to provide very high performances with respect to omnidirectional antennas. The use of adaptive array Smart Antenna could bring to enhance aspects such as energy management, especially in Mobile Ad Hoc Network (MANET), when the network performance closely depends on the battery life of the mobile nodes as well as on the routing protocol features. In this paper, we propose a new adaptive array Smart Antenna System that improves some Ad Hoc Distance Vector (AODV) network protocol features through a mechanism of energy consumption optimization. The system implements the Least Mean Square (LMS) as adaptive algorithm; for this purpose, we perform a co-simulation between Matlab, that implements the LMS algorithm and Omnet++, that provides a complete simulation environment for MANET.

Numerous challenges prevent the securing of IoT devices and their end-to-end communication in an IoT environment. The IoT is currently widely used in many areas such as in smart cities, in advanced logistic systems, in smart home etc. The safety and security of such systems are key aspects to guarantee the quality of their services. The purpose of this work is to model and evaluate a new IoT security system in a fog/edge network where there are lightweight nodes exchanging messages through the Message Queue Telemetry Transport (MQTT) protocol. This work aims to increase the security of this protocol at the application level, particularly mitigating data tampering and eavesdropping by using Elliptic Curve Cryptography (ECC), and applying different security mechanisms to the data topics. This feature allows to apply a threshold-based packet discarding policy for preserving the Quality of Service (QoS) of MQTT topics.

In this paper, we focused our attention on the design of an Intelligent Transportation System (ITS) system which offers support to the platooning management to achieve a global optimisation of the groups. In this way, new formations help vehicles to reduce energy consumption exploiting platooning. A novel algorithm based on Grey Wolf Optimization (GWO) to perform the search of the best platoon is considered. We evaluated the system performances of the platoon formation by considering several constraints such as platoon size, platoon speed, average platoon energy consumption. For the analysis of the results, we use the Omnet++ framework for protocol issues and Matlab tools for carrying out algorithm performances.

Platooning in VANET context is gaining a lot of interest in the last years. In order to support properly the car platooning multiple simulation modules need to be integrated to consider a different car mobility model, a different sensor equipment management on board. In this paper, an overview of the main simulator modules to support platooning are presented and a simple platooning management protocol has been proposed in order to improve the performance of electrical vehicles from an energetic point of view.

A QoS routing to select the best paths among Drones supporting incoming calls and multimedia traffic in emergency or critical situations is proposed. In situations where drones' teams are requested to cover areas where mobile users can need to communicate under the absence of network infrastructure, a self-organized on-the fly network becomes an essential goal. Cooperating with a critical network infrastructure, deploying a QoS aware path selection strategy supporting QoS requests and multimedia traffic such as VoIP and Video traffic can become a key issue to face. In this paper, a bio-inspired strategy to maintain the drones' network topology in a ligthway manner is proposed. Two metrics considered in a joint unified metric are proposed in order to balance traffic load and, at the same time, select the shortest routes. A comparison with an enhanced Link-State (LS) routing has been performed where the minimum hop count metric has been considered together to a LS routing with maximum available bandwidth metric. Performance evaluation has been evaluated in terms of control overhead, number or admitted calls, average bandwidth utilization.

Internet of Things (IoT) is a platform where every day devices become smarter, every day processing becomes intelligent, and every day communication becomes informative. Numerous challenges prevent to secure IoT devices and their end-to-end communication in an IoT environment. In fact, the IoT security is still an open challenge. The purpose of this work is to examine a distributed strategy for mitigating Denial of Service (DoS) attacks against the fog node in an edge computing context in which the nodes exchange messages through Message Queue Telemetry Transport (MQTT) protocol. The proposed strategy is based on a dynamic message sending frequency of the lightweight nodes. It is also mitigated data tampering and eavesdropping by using Elliptic Curve Cryptography (ECC).

In recent years, technology use has assumed an important role in the support of human activities. Intellectual work has become the main preferred human activity, while structured activities are going to become ever more automatized for increasing their efficiency. For this reason, we assist to the diffusion of ever more innovative devices able to face new emergent problems. These devices can interact with the environment and each other autonomously, taking decisions even without human control. This is the Internet of Things (IoT) phenomenon, favored by low cost, high mobility, high interaction and low power devices. This spread of devices has become uncontrolled, but security in this context continues to increase slowly. The purpose of this work is to model and evaluate a new IoT security system. The context is based on a generic IoT system in the presence of lightweight actuator and sensor nodes exchanging messages through Message Queue Telemetry Transport (MQTT) protocol. This work aims to increase the security of this protocol at application level, particularly mitigating Denial of Service (DoS) attacks. The system is based on the use of a host Intrusion Detection System (IDS) which applies a threshold based packet discarding policy to the different topics defined through MQTT.

Massive MIMO Systems certainly represent one of the most significant technology with regard to 5G systems; they are able to ensure high capacity performance through a better exploitation of the total radiated power with respect, for example, to sectorized and omnidirectional antennas. Unfortunately, because of the important amount of resources involved for achieving high data rates, these types of systems, could be affected from significant waste of energy especially if an appropriate mechanism that handles the energy consumption of nodes is not designed. Therefore, limiting the energy consumption of nodes relating to systems using very high data rates, constitutes a critical task because energy waste occur at the transmitter as well as at the receiver due to different reasons. In view of these considerations, in the present paper, we propose a novel algorithm having variable data rate and a mechanism for optimizing the energy consumption of nodes that addresses the problem both for the transmitter and the receiver.

In the last few years, we witnessed numerous episodes of terrorist attacks and menaces in public crowded places. The necessity of better surveillance in these places pushed the development of new automated solutions to spot and notify possible menaces as fast as possible. In this work, we propose a novel approach to create a decentralized architecture to manage patrolling drones and cameras exploiting lightweight protocols used in the internet of things (IoT) domain. Through the adoption of the mist computing paradigm it is possible to give to all the object of the smart ecosystem a cognitive intelligence to speed up the recognition and analysis tasks. Distributing the intelligence among all the objects of the surveillance ecosystem allows a faster recognition and reaction to possible warning situations. The recognition of unusual objects in certain areas, e.g., airports, train stations and bus stations, has been made using computer vision algorithms. The adoption of the IoT protocols in a hierarchical architecture provides high scalability allowing an easy and painless join of other smart objects. Also a study on the soft real-time feasibility has been conducted and is herein presented.

In wireless networking, the main desire of end-users is to take advantage of satisfactory services, in terms of QoS, especially when they pay for a required need. Many efforts have been made to investigate how the continuity of services can be guaranteed in QoS networks, where users can move from one cell to another one. The introduction of a prediction scheme with passive reservations is the only way to face this issue; however, the deployment of in-advance bandwidth leads the system to waste resources. This work consists of two main integrated contributions: a new pattern prediction scheme based on a distributed set of Markov chains, in order to handle passive reservations, and a statistical bandwidth management algorithm for the reduction of bandwidth wastage. The result of the integration is the Distributed Prediction with Bandwidth Management Algorithm (DPBMA) that is independent from the considered technology and the vehicular environment. Several simulation campaigns were conducted in order to evaluate the effectiveness of the proposed idea. It was also compared with other prediction schemes, in terms of system utilization, accuracy, call dropping, and call blocking probabilities.

Biological communication is a core component of biological systems, mainly presented in the form of evolution, transmitting information from a generation to the next. Unfortunately, biological systems also include other components and functionalities that would cause unwanted information processing and/or communication problems that manifest as diseases. On the other hand, general communication systems, e.g. digital communications, have been well developed and analysed to yield accuracy, high performance, and efficiency. Therefore, we extend the theories of digital communication systems to analyse biological communications. However, in order to accurately model biological communication as digital ones, an analysis of the analogies between both systems is essential. In this work, we propose a novel stacked-layer network model that presents gene expression (i.e. the process by which the information carried by deoxyribonucleic acid or DNA is transformed into the appropriate proteins) and the role of the Golgi apparatus in transmitting these proteins to a target organ. This is analogous to the transmit process in digital communications where a transmitting device in some network would send digital information to a destination/receiver device in another network through a router. The proposed stacked-layer network model exploits key networks’ theories and applies them into the broad field genomic analysis, which in turn can impact our understanding and use of medical methods. For example, it would be useful in detecting a target site (e.g. tumour cells) for drug therapy, improving the targeting accuracy (addressing), and reducing side effects in patients from health and socio-economic perspectives. Besides improving our understanding of biological communication systems, the proposed model unleashes the true duality between digital and biological communication systems. Therefore, it could be deployed into leveraging the advantages and efficiencies of biological systems into digital communication systems as well and to further develop efficient models that would overcome the disadvantages of either system.

Vehicular ad hoc networks (VANETs) represent a particular mobile technology that permits communication between vehicles, offering security and comfort. Nowadays, distributed mobile wireless computing is becoming a very important communication paradigm, due to its flexibility to adapt to different mobile applications. In this work, an interference aware metric is proposed in order to reduce the level of interference between each pair of nodes at the MAC and routing layer. In particular, this metric with a prediction algorithm is proposed to work in a cross-layered MAC and an on-demand routing scheme in multi-radio vehicular networks, wherein each node is equipped with two multi-channel radio interfaces. The proposed metric is based on the maximization of the average signal-to-interference ratio (SIR) level of the connection between source and destination. In order to relieve the effects of the co-channel interference perceived by mobile nodes, transmission channels are switched on a basis of a periodical SIR evaluation. Our solution has been integrated with an on-demand routing scheme but it can be applied to other routing strategies. Three on-demand interference aware routing schemes integrating IEEE 802.11p Multi-channel MAC have been tested to assess the benefits of the novel metric applied to a vehicular context. NS-3 has been used for implementing and testing the proposed idea, and significant performance improvements were obtained: in particular, the proposed policy has resulted in an enhancement of network performance in terms of throughput and packet delivery ratio.

From many years, the methods to defend against Denial of Service attacks have been very attractive from different point of views, although network security is a large and very complex topic. Different techniques have been proposed and so-called packet marking and IP tracing procedures have especially demonstrated a good capacity to face different malicious attacks. While host-based DoS attacks are more easily traced and managed, network-based DoS attacks are a more challenging threat. In this paper, we discuss a powerful aspect of the IP traceback method, which allows a router to mark and add information to attack packets on the basis of a fixed probability value. We propose a potential method for modeling the classic probabilistic packet marking algorithm as Markov chains, allowing a closed form to be obtained for evaluating the correct number of received marked packets in order to build a meaningful attack graph and analyze how marking routers must behave to minimize the overall overhead.

The paper proposes a comparison between two different coordination protocols for UAVs management in the agriculture domain. In precision agriculture the presence of parasites or the sudden climatic changes represent an important issue for farmers because of the degradation of crops and cultivation quality. Then, the use of the new technologies such as UAVs devices, the new networks such as FANET and the utilization of new sensors and actuators inside UAVs can represent an important aid to the farmers and the agriculture. An important aspect is, surely, the adequate management and coordination of these new devices in order to plan specific strategies able to support adequately the agriculture humans operators.

Many applications, related to autonomous mobile robots, require to explore in an unknown environment searching for static targets, without any a priori information about the environment topology and target locations. Targets in such rescue missions can be fire, mines, human victims, or dangerous material that the robots have to handle. In these scenarios, some cooperation among the robots is required for accomplishing the mission. This paper focuses on the application of different bio-inspired metaheuristics for the coordination of a swarm of mobile robots that have to explore an unknown area in order to rescue and handle cooperatively some distributed targets. This problem is formulated by first defining an optimization model and then considering two sub-problems: exploration and recruiting. Firstly, the environment is incrementally explored by robots using a modified version of ant colony optimization. Then, when a robot detects a target, a recruiting mechanism is carried out to recruit a certain number of robots to deal with the found target together. For this latter purpose, we have proposed and compared three approaches based on three different bio-inspired algorithms (Firefly Algorithm, Particle Swarm Optimization, and Artificial Bee Algorithm). A computational study and extensive simulations have been carried out to assess the behavior of the proposed approaches and to analyze their performance in terms of total energy consumed by the robots to complete the mission. Simulation results indicate that the firefly-based strategy usually provides superior performance and can reduce the wastage of energy, especially in complex scenarios.

The advances accomplished in the modern wireless network are leading to the development of efficient antenna devices that are able to achieve high requirements especially as regards the 5G next generation systems. Although a significant number of theoretical recommendations already exist in this context, the most of the used network simulators do not offer the possibility to emulate the next generation systems. The present paper provides an overview about URPA (Uniform Rectangular Planar Array) massive MIMO (Multiple Input Multiple Output) with reference to PER (Packet Error Rate) and channel performance; in addition, a support for emulating such systems, extending Omnet++ network simulator features, is presented.

In the last decade, the attention on unmanned aerial vehicles has rapidly grown, due to their ability to help in many human activities. Among their widespread benefits, one of the most important uses regards the possibility of distributing wireless connectivity to many users in a specific coverage area. In this study, we focus our attention on these new kinds of networks, called flying ad-hoc networks. As stated in the literature, they are suitable for all emergency situations where the traditional networking paradigm may have many issues or difficulties to be implemented. The use of a software simulator can give important help to the scientific community in the choice of the right UAV/drone parameters in many different situations. In particular, in this work, we focus our main attention on the new ways of area covering and human mobility behaviors with the introduction of a UAV/drone behavior model to take into account also drones energetic issues. A deep campaign of simulations was carried out to evaluate the goodness of the proposed simulator illustrating how it works.

Nowadays, the research on vehicular computing enhanced a very huge amount of services and protocols, aimed to vehicles security and comfort. The investigation of the IEEE802.11p, Wireless Access in Vehicular Environments (WAVE) and Dedicated Short Range Communication (DSRC) standards gave to the scientific world the chance to integrate new services, protocols, algorithms and devices inside vehicles. This opportunity attracted the attention of private/public organizations, which spent lot of resources and money to promote vehicular technologies. In this paper, the attention is focused on the design of a new approach for vehicular environments able to gather information during mobile node trips, for advising dangerous or emergency situations by exploiting on-board sensors. It is assumed that each vehicle has an integrated on-board unit composed of several sensors and Global Position System (GPS) device, able to spread alerting messages around the network, regarding warning and dangerous situations/conditions. On-board units, based on the standard communication protocols, share the collected information with the surrounding road-side units, while the sensing platform is able to recognize the environment that vehicles are passing through (obstacles, accidents, emergencies, dangerous situations, etc.). Finally, through the use of the GPS receiver, the exact location of the caught event is determined and spread along the network. In this way, if an accident occurs, the arriving cars will, probably, avoid delay and danger situations.

This work focuses on the return channel resource allocation in the DVB-RCS/RCS2 system for mobile terminals. A continuous carrier (CC) operation mode based on DVB-S2/S2X is considered and investigated. The paper focuses on the possibility of transmitting simultaneously in multifrequency–time division multiple access (MF-TDMA) or single channel per carrier (SCPC) medium access techniques, as suggested by a previous DVB-RCS+M standard. The introduction of this capability has also been analyzed for a new DVB-RCS2 standard that gives the possibility of using both return link (RL) modalities. Moreover, we propose a detailed study of the RL channel in a satellite platform in order to understand the operative range of SCPC and MF-TDMA techniques. The contribution seeks to provide some threshold indications to network operators for dynamically managing satellite resources.We considered the railway market, which is characterized by an N-LOS condition due to blockage caused by tunnels, vegetation, and buildings, as the reference scenario. Furthermore, we introduced a transparent gap filler (GF) solution to overcome this issue. Simulation campaigns are shown, in order to give satellite operators some guidelines, when they want to make use of this hybrid channel modality.

In the design of a Directional Medium Access Control (MAC) protocol for pervasive environments such the Mobile Ad hoc Networks (MANET), one of the most known problems that needs to be properly addressed is the deafness problem. Deafness could produce a large amount of collisions in the network and consequently a not negligible waste of energy. In this paper. we propose to partially mitigate this issue through the implementation of a Round-Robin MAC (RR-MAC) approach that provides for a logical sectorization of the transmission plane, limiting the maximum beamforming time of nodes, in order to reduce the frame collisions in the channel and at the same time to ensure an acceptable overall throughput in the network.

The mine detection in an unexplored area is an optimization problem where multiple mines, randomly distributed throughout an area, need to be discovered and disarmed in a minimum amount of time. We propose a strategy to explore an unknown area, using a stigmergy approach based on ants behavior, and a novel swarm based protocol to recruit and coordinate robots for disarming the mines cooperatively. Simulation tests are presented to show the effectiveness of our proposed Ant-based Task Robot Coordination (ATRC) with only the exploration task and with both exploration and recruiting strategies. Multiple minimization objectives have been considered: the robots' recruiting time and the overall area exploration time. We discuss, through simulation, different cases under different network and field conditions, performed by the robots. The results have shown that the proposed decentralized approaches enable the swarm of robots to perform cooperative tasks intelligently without any central control., Comment: Soft Computing, 2017

Drones or Unmanned Aerial Vehicles (UAVs) receive a growing interest for agricultural purposes. The aim is to provide inspiring insights in this domain from a technological and computational point of view. In these last years, indeed, there is an enormous potential that UAV technologies presents to support the agricultural domain in monitoring the land for checking and countering the presence of parasites that can damage the crop. However, to properly manage a UAVs team, equipped with multiple sensors and actuators, it is necessary to test these technologies and design proper strategies and coordination techniques able to efficiently manage the team. At this purpose, the paper proposes a simulator suitable for the agriculture domain in order to design novel coordination and control techniques of a UAVs team. Moreover it is possible to define the main variables and parameters of this domain of interest. The work presented many coordination techniques both for monitoring the area and both for coordinating the actions of the drones in the presence of parasites in order to analyze how the performance can significantly change if more constraints, such as energy, communication range, resource capacities, are accounted.

Directional antennas are largely employed in wireless networks due to their capability of increasing spatial reuse of the wireless channel with respect to the classical omnidirectional systems. In this context. the use of Smart Antenna Systems (SAS) are providing a strong increasing impact in digital wireless communication systems. Because of their many benefits, this kind of systems are extremely used especially in pervasive network environments such as Mobile Ad hoc Networks (MANET). However, almost of the whole of existing network simulators use omnidirectional antennas on nodes, and in many cases, do not provide a support for asymmetrical and directional communications. In view of this, we intend to enhance Omnet++ network simulator features by designing a new switched beam smart antenna model for providing a support for directional communications. Our proposed model simulates the basic operation of a Phased Array System also exploiting a very simple algorithm for modeling power management in the channel in order to provide an asymmetrical communication behavior.

The use of adaptive antenna systems enables the improvement of the overall wireless network capacity, especially in Mobile Ad hoc Networks (MANET) environments in which the quality of the communication is closely related to the Signal-to-Noise-Ratio (SNR) measured in the channel. Unfortunately, most of used adaptive algorithms such as Least Mean Square (LMS) and Constant Modulus Algorithm (CMA), because are strongly related to the step size value and to the error metric estimation, usually present a speed convergence problem. In this paper, a new Variable Error Metric (VMA) adaptive Algorithm is proposed in order to limit the level of dependency between the algorithms and step size also reducing the slowing effect introduced by Mean Square Error (MSE) criterion used for example by LMS algorithm.

Dishonesty detection in mobile and wireless networks is a task that typically relies on watchdog techniques. However, these medium overhearing-based techniques are prone to cause a high energy consumption. In an attempt to address this problem, several proposals adopted trust management as an alternative solution that is able to overcome the shortcomings of cryptography-based solutions when facing inside attacks. Unfortunately, these trust-based solutions remain mostly unable to reduce energy consumption. In this paper we propose a distributed time division-based monitoring strategy to achieve the required security levels while optimizing the energy consumption. Our proposal accounts for both trust and link duration among honest peers to fairly divide the monitoring period, and takes advantage of the periodically exchanged hello messages to make this solution fully distributed. Simulations results evidence the energy efficiency achieved by our proposal, especially for high density scenarios (>120 nodes) where the consumption becomes stable and does not increase with the number of nodes, while ensuring high detection ratios of malicious nodes (>85%).

Security in the context of Internet of Things (IoT) is a critical challenge. The purpose of this work is to model and evaluate a dynamic IoT security system based on a generic IoT edge network in which nodes exchange messages through the Message Queue Telemetry Transport (MQTT) protocol. This work aims to increase MQTT security by mitigating data tampering, eavesdropping and Replay attacks by using the Elliptic Curve Cryptography (ECC), timestamps and wake up patterns, with the purpose of preserving node energy. The evaluated results will show that it is possible to increase the system lifetime by linking security levels and energy.

Given the recent computation technologies and dedicated systems able to analyze huge amounts of “real-world” data and to extract information from it, the application possibilities reached in wireless mobile systems have significantly increased. The availability of mobile information, directly extracted from mobility traces, can be used to enhance the quality of the services offered, especially in a vehicular environment, where mobility is one of the main challenges. We present an in-depth study of mobility information management in infrastructure networks, where the covering devices can have a complete local visibility of what happens in terms of covered nodes. We focus our attention on the ways the gathered information can be used to set the coverage radius, to enhance a call admission control algorithm and to predict future movements. The paper introduces also a detailed description of how the obtained data can be statistically processed, and the obtained results confirm the benefits of the proposed scheme, especially in terms of call dropping probability (a minimum gain of 0.35 is obtained), which is a dominant parameter in infrastructure networks.

Nowadays, interest in mobile communications is growing rapidly due to the high level of device development, which permits the achievement of good objectives in terms of quality of service (QoS) for user satisfaction during active data flows. The increasing mobile client populations use different mobile devices to access the wireless medium and many applications are being developed to satisfy eager client requirements. Independently on the considered architecture (WLAN, UMTS, LTE, etc.), mobility represents a great advantage for user comfort, but it needs to be managed in an adequate manner in order to avoid service disruptions or unacceptable degradation of the perceived quality. In this paper, the concept of cell-mobility prediction is considered and we show how the analysis of user behavior, in terms of mobility, can be exploited to enhance QoS levels in current communications among mobile hosts and base stations (coverage cells, in general). This paper surveys different unconventional approaches and protocols, showing how it is possible to consider in-advance bandwidth reservations to achieve service continuity, avoiding call droppings during active sessions. First, we present the importance of in-advance reserving in wireless cellular networks, then we discuss the existing protocols and approaches for determining the most suitable future cells.

In the last few years the process of monitoring people health status has grown in interest in the researcher community and led to the develop of new devices able to detect and analyse information gathered from many kind of sensors. These devices are commonly designed to monitor or diagnose disease in the medical field. Moreover, a remarkable interest is growing in the field of sports. In amateur activities such as jogging, running, climbing a set of smart devices are used to improve and monitor performances. Another field of interest is represented by those people that wants to monitor their health status by using low cost devices. In this work we propose a two stage fuzzy logic approach in which the device tries to learn and fit customer habits in order to discover outlier warning signals. The two stages approach proposed consists of monitoring the normal activities of the user in order to build a reference of its condition; Then a real-time monitoring and analysis of gathered data from body sensors is accomplished. User status is carried out using a Fuzzy Logic based network. First stage will give us the current activity of the user while second stage will provide information about health status in terms of heart rate.

In situations where Internet connectivity is not available, opportunistic networks exploit the encounters between mobile human-carried devices for exchanging information. When people encounter each other, their handheld devices can communicate wirelessly and in a cooperative way using the encounter opportunities for forwarding their messages. However, in the real world, most of the nodes exhibit selfish behaviors mostly to conserve the limited buffer and power resources. As such, for ensuring a fair delivery, node selfishness should be taken into account. In this paper, we study the impact of node selfishness on the system throughput and delay of opportunistic communications. Through extensive simulations, we evaluate the system performances by utilizing experimental human mobility traces with different communication patterns. Our results show that the message delivery ratio decreases and the end-to-end average latency increases as the percentage of selfish nodes increases for all the routing protocols considered. However, the social-based forwarding rules are able to better manage node selfishness.

One of the most important issue that must be addressed in designing communication protocols for wireless sensor networks (WSN) is how to save sensor node energy while meeting the needs of applications. Recent researches have led to new protocols specifically designed for sensor networks where energy awareness is an essential consideration. Internet of Things (IoT) is an innovative ICT paradigm where a number of intelligent devices connected to Internet are involved in sharing information and making collaborative decision. Integration of sensing and actuation systems, connected to the Internet, means integration of all forms of energy consuming devices such as power outlets, bulbs, air conditioner, etc. Sometimes the system can communicate with the utility supply company and this led to achieve a balance between power generation and energy usage or in general is likely to optimize energy consumption as a whole. In this paper some emerging trends and challenges are identified to enable energy-efficient communications in Internet of Things architectures and between smart devices. The way devices communicate is analyzed in order to reduce energy consumption and prolong system lifetime. Devices equipped with WiFi and RF interfaces are analyzed under different scenarios by setting different communication parameters, such as data size, in order to evaluate the best device configuration and the longest lifetime of devices.

Coordination among multiple robots has been extensively studied, since a number of practical real problem s can be performed using an effective approach. In this paper is investigated a collective task that requires a multi-robot system to search for randomly distributed mines in an unknown environment and disarm them cooperatively. The communication among the swarm of robots influences the overall performance in terms of time to execute the task or consumed energy. To address this problem, a new distributed recruiting protocol to coordinate a swarm of robots in demining mission, is described. This problem is a multi-objective problem and two bio inspired strategies are used. The novelty of this approach lies in the combination of direct and indirect communication: on one hand an indirect communication among robots is used for the exploration of the environment, on the other hand a novel protocol is used to accomplish the recruiting and coordination of the robots for demining task. This protocol attempts to tackle the question of how autonomous robot can coordinate themselves into an unknown environment relying on simple low-level capabilities. The strategy is able to adapt the current system dynamics if the number of robots or the environment structure or both change. The proposed approach has been implemented and has been evaluated in several simulated environments. We analyzed the impact of our approach in the overall performance of a robot team. Experimental results indicated the effectiveness and efficiency of the proposed protocol to spread the robots in the environment.

In this paper some of the motivations for energy-efficient communications in wireless systems are described by highlighting emerging trends and identifying some challenges that need to be addressed to enable novel, scalable and energy-efficient communications. So an architecture for Internet of Things systems is presented, the purpose of which is to minimize energy consumption by communication devices, protocols, networks, end-user systems and data centers. Some electrical devices have been designed with multiple communication interfaces, such as RF or WiFi, using open source technology; they have been analyzed under different working conditions. Some devices are programmed to communicate directly with a web server, others to communicate only with a special device that acts as a bridge between some devices and the web server. Communication parameters and device status have been changed dynamically according to different scenarios in order to have the most benefits in terms of energy cost and battery lifetime. So the way devices communicate with the web server or between each other and the way they try to obtain the information they need to be always up to date change dynamically in order to guarantee always the lowest energy consumption, a long lasting battery lifetime, the fastest responses and feedbacks and the best quality of service and communication for end users and inner devices of the system.

MANETs are networks composed of mobile nodes connected using the wireless medium to communicate each other. The MANET nature makes it subject to various types of security leaks. External nodes could interfere with the communication, fair nodes could be compromised at any time by malicious agents. Another issue regards the limited amount of energy available to nodes, so their behavior could become selfish under some conditions. Many proposals detect these behaviors using a trust management system, but the activity of packet monitoring is energy-consuming. The main aim of this proposal is the reduction of the energy required by the monitoring system without lowering detection performance. Various simulations show that the achievement of this result is obtained through the application of a probabilistic approach, having also better performance in terms of time needed to detect misbehaviors.

The security is a key aspect in Mobile Ad-hoc Networks (MANETs), because the communication between the nodes is obtained using the wireless transmission, and the network setup is done without an infrastructure. In this scenario it is possible to perform internal and external attacks compromising the network functions. Moreover, the adoption of Intrusion Detection System (IDS) to discover internal attacks is often energy consuming highly reducing the network lifetime. At this purpose, our proposal is the design and adoption of an energy-aware probabilistic monitoring module useful to IDS, to better perform in a MANET scenario where not only security but also energy constraints need to be accounted. The proposed scheme has been analyzed by an energy point of view and considering also its efficacy to discover malicious nodes under different network conditions.

The use of smart antenna systems (SASs) in mobile ad hoc networks (MANETs) has been promoted as the best choice to improve spatial division multiple access (SDMA) and throughput. Although directional communications are expected to provide great advantages in terms of network performance, directional MAC (medium access control) protocols introduce several issues. One of the most known problems in this context is represented by the fact that, when attempting to solve or at least mitigate the problems introduced by these kinds of antennas especially at MAC layer, a large amount of energy consumption is achieved, for example, due to excessive retransmissions introduced by very frequently issue such as deafness and handoff. The expedients proposed in order to reduce these drawbacks attempting to limit beamforming time of nodes in cooperation with a round-robin scheduling can grant high performance in terms of fairness and throughput. However, the overall energy distribution in the network is not efficient due to static approach. In view of this, we propose adaptive beamforming time with round-robin MAC providing a dynamic assignment of the beamforming time with the aim to limit the waste of energy of nodes. The proposed approach provides benefits in terms of energy consumption distribution among nodes in sectorized antennas environments and, simultaneously, improves MAC packet performance.

In opportunistic networks, the nodes usually exploit a contact opportunity to perform hop-by-hop routing, since an end-to-end path between the source node and destination node may not exist. Most social-based routing protocols use social information extracted from real-world encounter networks to select an appropriate message relay. A protocol based on encounter history, however, takes time to build up a knowledge database from which to take routing decisions. An opportunistic routing protocol which extracts social information from multiple social networks, can be an alternative approach to avoid suboptimal paths due to partial information on encounters. While contact information changes constantly and it takes time to identify strong social ties, online social network ties remain rather stable and can be used to augment available partial contact information. In this paper, we propose a novel opportunistic routing approach, called ML-SOR (Multi-layer Social Network based Routing), which extracts social network information from multiple social contexts. To select an effective forwarding node, ML-SOR measures the forwarding capability of a node when compared to an encountered node in terms of node centrality, tie strength and link prediction. These metrics are computed by ML-SOR on different social network layers. Trace driven simulations show that ML-SOR, when compared to other schemes, is able to deliver messages with high probability while keeping overhead ratio very small.

Map matching is the process of positioning each point of a mobility trajectory on a digital map. A mobility trajectory is nothing more than a sequence of points characterized by latitude, longitude and timestamp information. The difficulty of map-matching depends on various factors such as the accuracy of maps, or the sampling rate of the points of the trajectory. In this paper, we explore the different tradeoffs involved in map-matching, and analyze how these vary under different location sampling conditions. We propose an algorithm to efficiently adapt the sampling method of the user location in order to reduce the energy consumption over the mobile device, while ensuring a sufficient reliability of the reconstructed path. Finally, we validate the proposed approach over real-world data, showing a 23% energy reduction in various mobility conditions, while maintaining a high accuracy of the reconstructed path.

In the last years the physical security in transportation systems is becoming a critical issue due to the high number of accidents and emergency situations. With the increasing availability of technological applications in vehicular environments researchers aimed at minimizing the probability of road accidents. In this paper, we propose a new platform able to discover dangerous driving behaviors. We based our application on the on-board diagnosis standard, able to provide all the needed information directly from the electronic vehicle control unit . We integrated the received data with a fuzzy logic approach, obtaining a description of the driver behavior. The overall system can take several initiatives (alarms, rpm corrections, etc.), in order to notify the driver bad behavior. The performance of the proposed scheme has been validated through a deep campaign of driving simulations.