Multimedia and video streaming are applications driving the full exploitation of the modern technologies of 5G networks, through which mobile users can attain a new peak of quality experience. Nevertheless, technological advancements need careful planning of how many and where the base station antennas should be placed to guarantee good coverage and fair quality over the entire area where users move. The WinProp software suite is adopted to reproduce communications scenarios in an urban environment and estimate network performance. The results show that once the number and location of the base stations are given, there is a tradeoff between connectivity and throughput.

The OPTIMIST project is positioned into one of the most challenging and societal impactful innovation paths, by contributing to the design and implementation of a Multi-access Edge Computing-empowered service platform enabling the optimized delivery of the most popular type of traffic in the forthcoming 5G networks: mobile video. Advanced prediction tools (e.g. data analytics), MEC-enabled service provisioning, 5G networking, QoE-driven and model-based service optimization using stochastic modeling and algorithmic optimization, are major components toward a holistic system that combines analytical tools and close-to-market technologies. In addition, despite the considerable amount of valuable academic research conducted in the area of MEC- enabled service provisioning, the vast majority of obtained results remains hardly compatible (in terms of system models and implementation platforms) and are often limited to the scope of academic research with no envisaged market transfer plans. OPTIMIST fosters fruitful collaboration of academia and industry targeting at developing an innovative platform for fully personalized delivery of 5G mobile video content.

This paper presents an overview of the project CASPER, a Marie Curie Research and Innovation Staff Exchange (RISE) project running from 2016 until 2020. The main objective of CASPER is to combine academic and industrial forces towards leveraging the expected benefits of Quality of Experience (QoE) exploitation in future digital networks. In particular, CASPER exploits the most recent advances in communication networks, such as the Software Defined Networking (SDN) and the Network Functions Virtualisation (NFV) in order to design and implement a middleware architecture for QoE-driven service provisioning. CASPER, therefore, addresses the challenges that mobile network operators and service providers face in the current fully digitalized era of communications, concerning the need to provide customer-oriented, reliable, efficient, flexible and dynamic service management.

The CASPER project envisions the user-centric network and service management in future mobile networks. In this frame, this paper aims at studying the impact of packet loss rate (PLR) and end-to-end delay (E2E delay) induced by quality of experience (QoE)-aware management policies in real LTE networking conditions with Voice over IP and video streaming traffic patterns. This objective is achieved by implementing a simulation framework built upon SimuLTE/OMNeT++ to reproduce the CASPER reference scenarios. The results demonstrate that there is a clear trade-off between the PLR and E2E delay that needs to be taken into account to keep acceptable OoE levels.

Contemporary technologies as implemented in the field of healthcare have provided the everyday clinical practice with a plethora of tools to be used in various settings. In this field, distributed and networked embedded systems, such as Wireless Sensor Networks (WSNs), are the most promising technology to achieve continuous monitoring of aged people for their own safety, without affecting their daily activities. WSN4QoL is a Marie Curie project involving academic and industrial partners from three EU countries, which aims to show how new WSNs-based technologies suit the specific requirements of pervasive healthcare applications. In particular, in this paper, the WSN4QoL's system architecture is presented as designed to exploit the Network Coding (NC) mechanisms to achieve energy efficiency in the wireless communications and distributed positioning solutions to locate patients in indoor home environments. The system has been validated through experimental activities using commercial off the shelf (COTS) WSN testbeds and medical devices prototypes offered by a commercial partner. Results demonstrate that NC helps in achieving substantial gains in terms of energy efficiency as compared to traditional relay mechanisms, while the proposed positioning solution is able to locate people in indoor environments at a sub-room accuracy level, without requiring any extra dedicated hardware.

Timely delivery of critical traffic is a major challenge in industrial applications. The Wireless Dominance (WiDOM) medium access control protocol offers a very large number of priority levels to suit time sensitive application requirements. In particular, assuming that its overhead is properly modeled, WiDOM enables an accurate evaluation of the network response time in the wireless domain, through the power of the schedulability analysis, based on non-preemptive and static-priority scheduling. Recent research proposed a new version of WiDOM (dubbed Slotted WiDOM), which offers a lower overhead as compared to the original version. In this paper, we propose a new schedulability analysis for Slotted WiDOM and extend it to handle message streams with release jitter. In order to provide a more accurate timing analysis, the effect of transmission faults must be taken into account. Therefore, in our novel analysis we consider the case where messages are transmitted in a realistic wireless channel, affected by noise and interference. Evaluation is performed on a real test-bed and the results from experiments provide a firm validation of our findings.

Wireless body area networks (WBANs) are composed of sensors that either monitor and transmit vital signals or act as relays that forward the received data to a body node coordinator (BNC). In this paper, we introduce an energy efficient vital signal telemonitoring scheme, which exploits compressed sensing (CS) for low-complexity signal compression/reconstruction and distributed cooperation for reliable data transmission to the BNC. More specifically, we introduce a cooperative compressed sensing (CCS) approach, which increases the energy efficiency of WBANs by exploiting the benefits of random linear network coding (RLNC). We study the energy efficiency of RLNC and compare it with the store-and-forward (FW) protocol. Our mathematical analysis shows that the gain introduced by RLNC increases as the link failure rate increases, especially in practical scenarios with a limited number of relays. Furthermore, we propose a reconstruction algorithm that further enhances the benefits of RLNC by exploiting key characteristics of vital signals. With the aid of electrocardiographic (ECG) and electroencephalographic (EEG) data available in medical databases, extensive simulation results are illustrated, which validate our theoretical findings and show that the proposed recovery algorithm increases the energy efficiency of the body sensor nodes by 40% compared to conventional CS-based reconstruction methods.

Life expectancy is projected to increase significantly in the coming years. This fact has pushed the need for designing new and more pervasive healthcare systems. In this field, distributed and networked embedded systems, such as Wireless Sensor Networks (WSNs), are the most suitable technology to achieve continuous monitoring of aged people for their own safety, without affecting their daily activities. This paper proposes recent advancements in this field by introducing WSN4QoL, a Marie Curie project which involves academic and industrial partners from three EU countries. The project aims to propose new WSN-based technologies to meet the specific requirements of pervasive healthcare applications. In particular, in this paper, a Network Coding (NC) mechanism and a distributed localization solution are presented. They have been implemented on WSN testbeds to achieve efficiency in the communications and to enable indoor people tracking. Preliminary results in a real environment show good system performance that meet our expectations.

Wireless Sensor Networks (WSNs) are fostering pervasive healthcare applications, where people are remotely monitored, without the full time assistance of professional care-givers. A key enabling element is the possibility to locate people in indoor environments, especially in emergency situations. Framed within the WSN4QoL project, this paper proposes the use of a ray tracing model for network planning, to support efficient people localization and performance analysis. Preliminary results show accurate radio coverage estimations, with a minimal calibration effort.

We consider reliable communications in Body Area Networks (BAN), where a set of nodes placed on human body are connected using wireless links. In order to keep the Specific Absorption Rate (SAR) as low as possible for health safety reasons, these networks operate in low transmit power regime, which however, is known to be error prone. It has been observed that the fluctuations of the Received Signal Strength (RSS) at the nodes of a BAN on a moving person show certain regularities and that the magnitude of these fluctuations are significant (5 - 20 dB). In this paper, we present BANMAC, a MAC protocol that monitors and predicts the channel fluctuations and schedules transmissions opportunistically when the RSS is likely to be higher. The MAC protocol is capable of providing differentiated service and resolves co-channel interference in the event of multiple co-located BANs in a vicinity. We report the design and implementation details of BANMAC integrated with the IEEE 802.15.4 protocol stack. We present experimental data which show that the packet loss rate (PLR) of BANMAC is significantly lower as compared to that of the IEEE 802.15.4 MAC. For comparable PLR, the power consumption of BANMAC is also significantly lower than that of the IEEE~802.15.4. For co-located networks, the convergence time to find a conflict-free channel allocation was approximately 1 s for the centralized coordination mechanism and was approximately 4 s for the distributed coordination mechanism.

Wireless sensor networks (WSNs) have attracted growing interest in the last decade as an infrastructure to support a diversity of ubiquitous computing and cyber-physical systems. However, most research work has focused on protocols or on specific applications. As a result, there remains a clear lack of effective, feasible and usable system architectures that address both functional and non-functional requirements in an integrated fashion. In this paper, we outline the EMMON system architecture for large-scale, dense, real-time embedded monitoring. EMMON provides a hierarchical communication architecture together with integrated middleware and command and control software. It has been designed to use standard commercially-available technologies, while maintaining as much flexibility as possible to meet specific applications requirements. The EMMON architecture has been validated through extensive simulation and experimental evaluation, including a 300+ node test-bed, which is, to the best of our knowledge, the largest single-site WSN test-bed in Europe to date.

Knowing exactly where a mobile entity is and monitoring its trajectory in real-time has recently attracted a lot of interests from both academia and industrial communities, due to the large number of applications it enables, nevertheless, it is nowadays one of the most challenging problems from scientific and technological standpoints. In this work we propose a tracking system based on the fusion of position estimations provided by different sources, that are combined together to get a final estimation that aims at providing improved accuracy with respect to those generated by each system individually. In particular, exploiting the availability of a Wireless Sensor Network as an infrastructure, a mobile entity equipped with an inertial system first gets the position estimation using both a Kalman Filter and a fully distributed positioning algorithm (the Enhanced Steepest Descent, we recently proposed), then combines the results using the Simple Convex Combination algorithm. Simulation results clearly show good performance in terms of the final accuracy achieved. Finally, the proposed technique is validated against real data taken from an inertial sensor provided by THALES ITALIA.

Most research work on WSNs has focused on protocols or on specific applications. There is a clear lack of easy/ready-to-use WSN technologies and tools for planning, implementing, testing and commissioning WSN systems in an integrated fashion. While there exists a plethora of papers about network planning and deployment methodologies, to the best of our knowledge none of them helps the designer to match coverage requirements with network performance evaluation. In this paper we aim at filling this gap by presenting an unified toolset, i.e., a framework able to provide a global picture of the system, from the network deployment planning to system test and validation. This toolset has been designed to back up the EMMON WSN system architecture for large-scale, dense, real-time embedded monitoring. It includes network deployment planning, worst-case analysis and dimensioning, protocol simulation and automatic remote programming and hardware testing tools. This toolset has been paramount to validate the system architecture through DEMMON1, the first EMMON demonstrator, i.e., a 300+ node test-bed, which is, to the best of our knowledge, the largest single-site WSN test-bed in Europe to date.

The demonstration proposal moves from the capabilities of a wireless biometric badge [4], which integrates a localization and tracking service along with an automatic personal identification mechanism, to show how a full system architecture is devised to enable the control of physical accesses to restricted areas. The system leverages on the availability of a novel IEEE 802.15.4/Zigbee Cluster Tree network model, on enhanced security levels and on the respect of all the users' privacy issues.

Wireless sensor networks (WSNs) have attracted growing interest in the last decade as an infrastructure to support a diversity of ubiquitous computing and cyber-physical systems. However, most research work has focused on protocols or on specific applications. As a result, there remains a clear lack of effective and usable WSN system architectures that address both functional and non-functional requirements in an integrated fashion. This poster outlines the EMMON system architecture for large-scale, dense, real-time embedded monitoring. It provides a hierarchical communication architecture together with integrated middleware and command and control software. It has been designed to maintain as much as flexibility as possible while meeting specific applications requirements. EMMON has been validated through extensive analytical, simulation and experimental evaluations, including through a 300+ nodes test-bed the largest single-site WSN test-bed in Europe.

We propose a comprehensive theoretical framework to evaluate reliability and energy consumption of distributed source coding (DSC) in wireless sensor networks (WSNs) applications. Energy efficiency and the amount of measurements that can be successfully decoded in tree-based WSNs employing DSC in the presence of different coding topologies and packet aggregation schemes (PA) are accurately characterized. The system model includes a realistic network architecture with multi-hop communication, automatic repeat request protocol (ARQ), packet losses due to channel impairments and collisions, and correlation properties of the sensed phenomena. Four DSC topologies and three alternatives of PA are considered. The analysis is carried out by evaluating the expressions of reliability of DSC in terms of probability of measurements that cannot be decoded (loss factor), and the efficiency in terms of average energy consumption of the network. Numerical results show that the best choice of DSC topology and packet aggregation depends highly on the network parameters and source characteristics. Therefore, the analysis developed in this paper can be used as an effective mean to optimize network operations.

The demonstration proposal focuses on presenting the capabilities of a wireless biometric badge, which integrates a localization and tracking service along with an automatic personal identification mechanism, to control the access to restricted areas with a high level of security. The wireless biometric badge is the result of R&D activities conducted by several professors, researchers, and students in the Center of Excellence in Research DEWS at the University of L' Aquila in Italy, as well as its R&D Spin-Off WEST Aquila S.r.l.

In two recent contributions, we have provided a comparative analysis of various optimization algorithms, which can be used for atomic location estimation, and suggested an enhanced version of the Steepest Descent (ESD) algorithm, which we have shown to be competitive with other distributed localization algorithms in terms of estimation accuracy and numerical complexity. Moreover, therein we have conducted a preliminary statistical characterization of the positioning error distribution, by showing that it can be well approximated by the family of Pearson distributions, as well as pointed out that its knowledge may be efficiently used to speed-up the analysis of iterative-based positioning algorithms by avoiding the need of simulating the whole location discovery algorithm, and allowing simulation at the atomic level only. In this contribution, based on the preliminary results shown in, we propose a comprehensive statistical analysis of the positioning error distribution for the ESD algorithm, by providing the parameters of the Pearson fitting distribution with respect to two important design factors for wireless sensor networks (WSNs): i) the ranging error standard deviation, which represents the input parameter for every localization algorithm, and ii) the geometric dilution of precision factor, which provides a simple parameter to account for different network topologies. In particular, we report an extensive number of simulation results that may provide important insights to the system designer: i) allow a parametric analysis to figure out the joint effect of ranging errors and network topology on the performance of the localization algorithms, and ii) give a general framework for modeling the statistics of the positioning error, which may be used for network planning, as well as for the analysis and design of the upper layers of the protocol stack.

In recent contributions [Tennina, S., et al., 2008], [Tennina, S., 2008], we have provided a comparative analysis of various optimization algorithms, which can be used for atomic location estimation, and suggested an enhanced version of the steepest descent (ESD) algorithm, which we have shown to be competitive with well-known distributed localization algorithms in terms of estimation accuracy and numerical complexity. Moreover, in [Tennina, S., 2008] we have conducted a statistical characterization of the positioning error distribution of the ESD algorithm, and shown that the latter error can be well approximated by the family of Pearson distributions. However, the analysis in [Tennina, S., et al., 2008; Tennina, S., 2008; Tennina, S., 2008] is mainly based on numerical (i.e., computer-based) simulations, which only in part allows to predict the system performance in a realistic environment where sensor nodes are expected to operate. As a consequence, the aim of this contribution is twofold: i) to analyze the error performance of the ESD algorithm in a real testbed platform working in a typical indoor environment, and ii) to compare experimental and simulated results to substantiate via real measurements our previous findings useful for network setup and analysis. In particular, we will first report on the implementation issues related on mapping the ESD algorithm on the CrossBow's MICAz sensor node platform [http://www.xbow.com/Products/wproductsoverview.aspx.], and, then, we will investigate, via real experiments, on the effect of network topology and ranging errors in estimating the final position of an unknown sensor node.

Recent advances in the technology of wireless electronic devices have made possible to build ad-hoc wireless sensor networks (WSNs) using inexpensive nodes consisting of low power processors, a modest amount of memory, and simple wireless transceivers. Over the last years, many novel applications have been envisaged for distributed WSNs in the area of monitoring, communication, and control. One of the key enabling and indispensable services in WSNs is localization (i.e., positioning), given that the availability of nodes' location may represent the fundamental support for various protocols (e.g., routing) and applications (e.g., habitat monitoring). In the depicted context, the present contribution reports our recent research advances along two main directions: i) first of all, we provide a comparative analysis of various optimization algorithms that can be used for atomic location estimation, which include: triangulation, steepest descent, non-linear least squares, conjugate gradient, and an enhanced version of the Steepest Descent (ESD) that is introduced in this paper, and ii) then, we provide a statistical characterization of location errors, by showing that the distribution of error positions can be well approximated by the family of Pearson distributions. In particular, we will show that i) the ESD algorithm may be competitive with the other algorithms in terms of estimation accuracy and numerical complexity, and ii) the knowledge of location error distribution may be efficiently used to speed-up the analysis of iterative-based positioning algorithms by avoiding the need of simulating the whole location discovery algorithm and allowing simulation at the atomic level only.

In this paper, we propose a theoretical setup for evaluation of energy efficiency of wireless sensor networks (WSNs) with distributed source coding (DSC) algorithms and packet aggregation (PA). We consider four topologies for DSC and three alternatives for PA, and the system model includes a realistic network architecture with multi-hop communication, automatic repeat request protocol (ARQ), and packet losses. The analysis is carried out in two steps. Firstly we derive the packet loss probability, and then evaluate the average number of packets transmitted throughout the network. This second performance index can then be mapped onto an energy efficiency indicator. The proposed model is specifically adopted for performance comparison of the different coding strategies and aggregation schemes in terms of energy efficiency. Numerical results show that packet overheads have a relevant influence on performance, while the ARQ protocol introduces negligible effects on the energy consumption. Furthermore, DSC topologies with master- slave approach and fragmentation of packets exhibit better performance.