Spatial networks with wireless applications

Many networks have nodes located in physical space, with links more common between closely spaced pairs of nodes. For example, the nodes could be wireless devices and links communication channels in a wireless mesh network. We describe recent work involving such networks, considering effects due to the geometry (convex,non-convex, and fractal), node distribution, distance-dependent link probability, mobility, directivity and interference.Comment: Review article- an amended version with a new title from the origina

Detecting Flow Anomalies in Distributed Systems

Deep within the networks of distributed systems, one often finds anomalies that affect their efficiency and performance. These anomalies are difficult to detect because the distributed systems may not have sufficient sensors to monitor the flow of traffic within the interconnected nodes of the networks. Without early detection and making corrections, these anomalies may aggravate over time and could possibly cause disastrous outcomes in the system in the unforeseeable future. Using only coarse-grained information from the two end points of network flows, we propose a network transmission model and a localization algorithm, to detect the location of anomalies and rank them using a proposed metric within distributed systems. We evaluate our approach on passengers' records of an urbanized city's public transportation system and correlate our findings with passengers' postings on social media microblogs. Our experiments show that the metric derived using our localization algorithm gives a better ranking of anomalies as compared to standard deviation measures from statistical models. Our case studies also demonstrate that transportation events reported in social media microblogs matches the locations of our detect anomalies, suggesting that our algorithm performs well in locating the anomalies within distributed systems

Resource-efficient strategies for mobile ad-hoc networking

The ubiquity and widespread availability of wireless mobile devices with ever increasing inter-connectivity (e. g. by means of Bluetooth, WiFi or UWB) have led to new and emerging next generation mobile communication paradigms, such as the Mobile Ad-hoc NETworks (MANETs). MANETs are differentiated from traditional mobile systems by their unique properties, e. g. unpredictable nodal location, unstable topology and multi-hop packet relay. The success of on-going research in communications involving MANETs has encouraged their applications in areas with stringent performance requirements such as the e-healthcare, e. g. to connect them with existing systems to deliver e-healthcare services anytime anywhere. However, given that the capacity of mobile devices is restricted by their resource constraints (e. g. computing power, energy supply and bandwidth), a fundamental challenge in MANETs is how to realize the crucial performance/Quality of Service (QoS) expectations of communications in a network of high dynamism without overusing the limited resources. A variety of networking technologies (e. g. routing, mobility estimation and connectivity prediction) have been developed to overcome the topological instability and unpredictability and to enable communications in MANETs with satisfactory performance or QoS. However, these technologies often feature a high consumption of power and/or bandwidth, which makes them unsuitable for resource constrained handheld or embedded mobile devices. In particular, existing strategies of routing and mobility characterization are shown to achieve fairly good performance but at the expense of excessive traffic overhead or energy consumption. For instance, existing hybrid routing protocols in dense MANETs are based in two-dimensional organizations that produce heavy proactive traffic. In sparse MANETs, existing packet delivery strategy often replicates too many copies of a packet for a QoS target. In addition, existing tools for measuring nodal mobility are based on either the GPS or GPS-free positioning systems, which incur intensive communications/computations that are costly for battery-powered terminals. There is a need to develop economical networking strategies (in terms of resource utilization) in delivering the desired performance/soft QoS targets. The main goal of this project is to develop new networking strategies (in particular, for routing and mobility characterization) that are efficient in terms of resource consumptions while being effective in realizing performance expectations for communication services (e. g. in the scenario of e-healthcare emergency) with critical QoS requirements in resource-constrained MANETs. The main contributions of the thesis are threefold: (1) In order to tackle the inefficient bandwidth utilization of hybrid service/routing discovery in dense MANETs, a novel "track-based" scheme is developed. The scheme deploys a one-dimensional track-like structure for hybrid routing and service discovery. In comparison with existing hybrid routing/service discovery protocols that are based on two-dimensional structures, the track-based scheme is more efficient in terms of traffic overhead (e. g. about 60% less in low mobility scenarios as shown in Fig. 3.4). Due to the way "provocative tracks" are established, the scheme has also the capability to adapt to the network traffic and mobility for a better performance. (2) To minimize the resource utilization of packet delivery in sparse MANETs where wireless links are intermittently connected, a store-and-forward based scheme, "adaptive multicopy routing", was developed for packet delivery in sparse mobile ad-hoc networks. Instead of relying on the source to control the delivery overhead as in the conventional multi-copy protocols, the scheme allows each intermediate node to independently decide whether to forward a packet according to the soft QoS target and local network conditions. Therefore, the scheme can adapt to varying networking situations that cannot be anticipated in conventional source-defined strategies and deliver packets for a specific QoS targets using minimum traffic overhead. ii (3) The important issue of mobility measurement that imposes heavy communication/computation burdens on a mobile is addressed with a set of resource-efficient "GPS-free" soluti ons, which provide mobility characterization with minimal resource utilization for ranging and signalling by making use of the information of the time-varying ranges between neighbouring mobile nodes (or groups of mobile nodes). The range-based solutions for mobility characterization consist of a new mobility metric for network-wide performance measurement, two velocity estimators for approximating the inter-node relative speeds, and a new scheme for characterizing the nodal mobility. The new metric and its variants are capable of capturing the mobility of a network as well as predicting the performance. The velocity estimators are used to measure the speed and orientation of a mobile relative to its neighbours, given the presence of a departing node. Based on the velocity estimators, the new scheme for mobility characterization is capable of characterizing the mobility of a node that are associated with topological stability, i. e. the node's speeds, orientations relative to its neighbouring nodes and its past epoch time. iiiBIOPATTERN EU Network of Excellence (EU Contract 508803

Direct communication radio Iinterface for new radio multicasting and cooperative positioning

Cotutela: Universidad de defensa UNIVERSITA’ MEDITERRANEA DI REGGIO CALABRIARecently, the popularity of Millimeter Wave (mmWave) wireless networks has increased due to their capability to cope with the escalation of mobile data demands caused by the unprecedented proliferation of smart devices in the fifth-generation (5G). Extremely high frequency or mmWave band is a fundamental pillar in the provision of the expected gigabit data rates. Hence, according to both academic and industrial communities, mmWave technology, e.g., 5G New Radio (NR) and WiGig (60 GHz), is considered as one of the main components of 5G and beyond networks. Particularly, the 3rd Generation Partnership Project (3GPP) provides for the use of licensed mmWave sub-bands for the 5G mmWave cellular networks, whereas IEEE actively explores the unlicensed band at 60 GHz for the next-generation wireless local area networks. In this regard, mmWave has been envisaged as a new technology layout for real-time heavy-traffic and wearable applications. This very work is devoted to solving the problem of mmWave band communication system while enhancing its advantages through utilizing the direct communication radio interface for NR multicasting, cooperative positioning, and mission-critical applications. The main contributions presented in this work include: (i) a set of mathematical frameworks and simulation tools to characterize multicast traffic delivery in mmWave directional systems; (ii) sidelink relaying concept exploitation to deal with the channel condition deterioration of dynamic multicast systems and to ensure mission-critical and ultra-reliable low-latency communications; (iii) cooperative positioning techniques analysis for enhancing cellular positioning accuracy for 5G+ emerging applications that require not only improved communication characteristics but also precise localization. Our study indicates the need for additional mechanisms/research that can be utilized: (i) to further improve multicasting performance in 5G/6G systems; (ii) to investigate sideline aspects, including, but not limited to, standardization perspective and the next relay selection strategies; and (iii) to design cooperative positioning systems based on Device-to-Device (D2D) technology

SLS: Smart localization service: human mobility models and machine learning enhancements for mobile phone’s localization

In recent years we are witnessing a noticeable increment in the usage of new generation smartphones, as well as the growth of mobile application development. Today, there is an app for almost everything we need. We are surrounded by a huge number of proactive applications, which automatically provide relevant information and services when and where we need them. This switch from the previous generation of passive applications to the new one of proactive applications has been enabled by the exploitation of context information. One of the most important and most widely used pieces of context information is location data. For this reason, new generation devices include a localization engine that exploits various embedded technologies (e.g., GPS, WiFi, GSM) to retrieve location information. Consequently, the key issue in localization is now the efficient use of the mobile localization engine, where efficient means lightweight on device resource consumption, responsive, accurate and safe in terms of privacy. In fact, since the device resources are limited, all the services running on it have to manage their trade-off between consumption and reliability to prevent a premature depletion of the phone’s battery. In turn, localization is one of the most demanding services in terms of resource consumption. In this dissertation I present an efficient localization solution that includes, in addition to the standard location tracking techniques, the support of other technologies already available on smartphones (e.g., embedded sensors), as well as the integration of both Human Mobility Modelling (HMM) and Machine Learning (ML) techniques. The main goal of the proposed solution is the provision of a continuous tracking service while achieving a sizeable reduction of the energy impact of the localization with respect to standard solutions, as well as the preservation of user privacy by avoiding the use of a back-end server. This results in a Smart Localization Service (SLS), which outperforms current solutions implemented on smartphones in terms of energy consumption (and, therefore, mobile device lifetime), availability of location information, and network traffic volume