On the Data Freshness for IoT Traffic Modelling in Real-Time Emergency Observation Systems

Internet of things (IoT) and fog computing based observation systems are gaining more importance as Internet becomes the main infrastructure to augment the pervasiveness in remote monitoring of the physical world. Considering the explosion in the number of connected ”things”, the increase of data traffic density on interconnection devices (i.e., IoT gateways) becomes an important problem for scalable real-time emergency detection and monitoring. Thus, data traffic analysis and modeling of fog services become an important research area to get more insights into real-time behavior of such systems. The outcomes of such analysis are important for prediction of IoT system behavior in a given network topology. In this paper, we elaborate on an architectural solution for periodic data acquisition from a wireless sensor network(WSN). To this end, we propose a publish/subscribe (P/S) based observation scheme which simultaneously interconnects clients to different kind of sensor devices over a fog layer service. Then, we examine the data freshness which is a critical traffic modeling parameter for real-time emergency observation. With using such scheme, we devise an analysis for understanding the behavior of the overall system in the context of data freshness. The results obtained from our experimental setup illustrate the appropriateness of freshness time calculation methods for obtaining the required service quality

Real-time localisation system for GPS denied open areas using smart street furniture

Real-time measurement of crowd dynamics has been attracting significant interest, as it has many applications including real-time monitoring of emergencies and evacuation plans. To effectively measure crowd behaviour, an accurate estimate for pedestrians’ locations is required. However, estimating pedestrians’ locations is a great challenge especially for open areas with poor Global Positioning System (GPS) signal reception and/or lack of infrastructure to install expensive solutions such as video-based systems. Street furniture assets such as rubbish bins have become smart, as they have been equipped with low-power sensors. Currently, their role is limited to certain applications such as waste management. We believe that the role of street furniture can be extended to include building real-time localisation systems as street furniture provides excellent coverage across different areas such as parks, streets, homes, universities. In this thesis, we propose a novel wireless sensor network architecture designed for smart street furniture. We extend the functionality of sensor nodes to act as soft Access Point (AP), sensing Wifi signals received from surrounding Wifi-enabled devices. Our proposed architecture includes a real-time and low-power design for sensor nodes. We attached sensor nodes to rubbish bins located in a busy GPS denied open area at Murdoch University (Perth, Western Australia), known as Bush Court. This enabled us to introduce two unique Wifi-based localisation datasets: the first is the Fingerprint dataset called MurdochBushCourtLoC-FP (MBCLFP) in which four users generated Wifi fingerprints for all available cells in the gridded Bush Court, called Reference Points (RPs), using their smartphones, and the second is the APs dataset called MurdochBushCourtLoC-AP (MBCLAP) that includes auto-generated records received from over 1000 users’ devices. Finally, we developed a real-time localisation approach based on the two datasets using a four-layer deep learning classifier. The approach includes a light-weight algorithm to label the MBCLAP dataset using the MBCLFP dataset and convert the MBCLAP dataset to be synchronous. With the use of our proposed approach, up to 19% improvement in location prediction is achieved

Value of Information Analysis in the Smart Agriculture Scenario using Wireless Internet of Things

openThe trend of Internet of Things development in the agriculture sector has led a high demand towards advanced technological settings with high efficiency and effectiveness. Often, the constructed sensor network suffers from excessive energy consumption due to the existence of collisions, and/or redundant data transmissions (time and space redundancy). In recent years, researchers have been trying to resolve this phenomenon by introducing a new quantitative metric, named Value of Information, which determines how valuable a generated information is. We want to make sure that the cost we spend for transmitting a packet corresponds to the value of the information that a packet submitted. In this thesis, we analyze such a metric from the agriculture point of view. Practical applications of this rationale include the reduction of update frequency by sensor considering the cost and network models that consider the transmissions of valuable packet only. These problems are evaluated through numerical simulation, in practical implementation contexts of a Lora network in real plantation and from a general perspective of future implementation.The trend of Internet of Things development in the agriculture sector has led a high demand towards advanced technological settings with high efficiency and effectiveness. Often, the constructed sensor network suffers from excessive energy consumption due to the existence of collisions, and/or redundant data transmissions (time and space redundancy). In recent years, researchers have been trying to resolve this phenomenon by introducing a new quantitative metric, named Value of Information, which determines how valuable a generated information is. We want to make sure that the cost we spend for transmitting a packet corresponds to the value of the information that a packet submitted. In this thesis, we analyze such a metric from the agriculture point of view. Practical applications of this rationale include the reduction of update frequency by sensor considering the cost and network models that consider the transmissions of valuable packet only. These problems are evaluated through numerical simulation, in practical implementation contexts of a Lora network in real plantation and from a general perspective of future implementation

A Dynamic Game with Adaptive Strategies For IEEE 802.15.4 and IoT

© 2016 IEEE. This is the accepted manuscript version of a conference paper which has been published in final form at https://doi.org/10.1109/TrustCom.2016.0099The problem of selfishness and misbehaviour in wireless networks is well known, as are the associated solutions that have been proposed for it in IEEE 802.11 Wireless Local Area Network (WLAN) and Wireless Sensory Network (WSN). However, tackling such problem in relation to the Internet of Things (IoT) is relatively new since the IoT is still under development. The central communication infrastructure of IoT is the IEEE 802.15.4 standard which defines low-rate and low energy wireless personal area networks. In order to share the medium fairly and efficiently in a beacon-enabled mode, the standard uses Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) in the Contention Access Period (CAP), and Guarantee Time Slot (GTS) in the Contention Free Period (CFP) of a super-frame. These channel sharing mechanisms are known to be vulnerable to selfishness, misbehaviour and channel capture as a result of nodes disobeying the communication rules. Most of the existing game theoretic solutions were designed for IEEE 802.11 WLAN and WSN. In this work, we present a dynamic game in which nodes can select and adapt their strategies of play according to the 'state of the game' and their energy level in order to increase their utility whenever their utility declined. Our model enables resources constrained nodes to optimised their strategies individually based upon the current state of the game and their available resources. Our analysis and simulation results suggest an improvement in utility, and fairness in channel sharing, as well as efficiency in energy usage in our dynamic model and hence performance and security in our scheme over the default IEEE 802.15.4 access mechanism

Machine Learning-Aided Operations and Communications of Unmanned Aerial Vehicles: A Contemporary Survey

The ongoing amalgamation of UAV and ML techniques is creating a significant synergy and empowering UAVs with unprecedented intelligence and autonomy. This survey aims to provide a timely and comprehensive overview of ML techniques used in UAV operations and communications and identify the potential growth areas and research gaps. We emphasise the four key components of UAV operations and communications to which ML can significantly contribute, namely, perception and feature extraction, feature interpretation and regeneration, trajectory and mission planning, and aerodynamic control and operation. We classify the latest popular ML tools based on their applications to the four components and conduct gap analyses. This survey also takes a step forward by pointing out significant challenges in the upcoming realm of ML-aided automated UAV operations and communications. It is revealed that different ML techniques dominate the applications to the four key modules of UAV operations and communications. While there is an increasing trend of cross-module designs, little effort has been devoted to an end-to-end ML framework, from perception and feature extraction to aerodynamic control and operation. It is also unveiled that the reliability and trust of ML in UAV operations and applications require significant attention before full automation of UAVs and potential cooperation between UAVs and humans come to fruition.Comment: 36 pages, 304 references, 19 Figure

Network Optimisation for Robotic Aerial Base Stations

One attractive application of unmanned aerial vehicles (UAVs) is to provide wireless coverage when acting as aerial base stations (ABSs). Compared to terrestrial small cells, ABSs have the benefit of flexible deployment, controllable mobility, and dominant line-of-sight channels, so they are expected to play a significant role in next-generation cellular networks. However, introducing this novel non-terrestrial communication device would also bring new challenges, such as requiring different evaluation criteria and being restricted by unexpected resource constraints. With this in mind, this thesis mainly focuses on the network optimisation problems of ABS-assisted networks.Specifically, we first investigate two contradictory metrics, i.e., the information freshness and energy consumption, when an ABS is employed to collect data from ground terminals. A novel multi-return-allowed serving mode is proposed to explore the Pareto optimal trade-off between these two metrics. Secondly, to overcome the functional endurance issue of conventional ABSs, we propose a novel prototype named robotic aerial base stations (RABSs) with grasping capabilities, which can attach autonomously in lampposts or land on other tall urban landforms to serve as small cells with prolonged endurance. By employing this novel ABS prototype, we first study the optimal deployment and operation strategy for RABSs when the mobile traffic demand shows heterogeneity in both spatial and temporal domains. Afterwards, to further explore the use of RABSs in the upcoming 6G era, we investigate two novel application scenarios, that is, an RABS-assisted integrated sensing and communication (ISAC) system and an RABS-aided millimetre-wave (mmWave) backhaul network.The proposed scenarios are formulated as various non-convex problems. By analyzing their constructions, we propose a variety of algorithms to solve them in a reasonable time. A wide set of simulation results shows that the proposed novel prototypes and serving schemes have immense potential in future cellular networks.<br/

Multi-factor Physical Layer Security Authentication in Short Blocklength Communication

Lightweight and low latency security schemes at the physical layer that have recently attracted a lot of attention include: (i) physical unclonable functions (PUFs), (ii) localization based authentication, and, (iii) secret key generation (SKG) from wireless fading coefficients. In this paper, we focus on short blocklengths and propose a fast, privacy preserving, multi-factor authentication protocol that uniquely combines PUFs, proximity estimation and SKG. We focus on delay constrained applications and demonstrate the performance of the SKG scheme in the short blocklength by providing a numerical comparison of three families of channel codes, including half rate low density parity check codes (LDPC), Bose Chaudhuri Hocquenghem (BCH), and, Polar Slepian Wolf codes for n=512, 1024. The SKG keys are incorporated in a zero-round-trip-time resumption protocol for fast re-authentication. All schemes of the proposed mutual authentication protocol are shown to be secure through formal proofs using Burrows, Abadi and Needham (BAN) and Mao and Boyd (MB) logic as well as the Tamarin-prover

Safe Intelligent Driver Assistance System in V2X Communication Environments based on IoT

In the modern world, power and speed of cars have increased steadily, as traffic continued to increase. At the same time highway-related fatalities and injuries due to road incidents are constantly growing and safety problems come first. Therefore, the development of Driver Assistance Systems (DAS) has become a major issue. Numerous innovations, systems and technologies have been developed in order to improve road transportation and safety. Modern computer vision algorithms enable cars to understand the road environment with low miss rates. A number of Intelligent Transportation Systems (ITSs), Vehicle Ad-Hoc Networks (VANETs) have been applied in the different cities over the world. Recently, a new global paradigm, known as the Internet of Things (IoT) brings new idea to update the existing solutions. Vehicle-to-Infrastructure communication based on IoT technologies would be a next step in intelligent transportation for the future Internet-of-Vehicles (IoV). The overall purpose of this research was to come up with a scalable IoT solution for driver assistance, which allows to combine safety relevant information for a driver from different types of in-vehicle sensors, in-vehicle DAS, vehicle networks and driver`s gadgets. This study brushed up on the evolution and state-of-the-art of Vehicle Systems. Existing ITSs, VANETs and DASs were evaluated in the research. The study proposed a design approach for the future development of transport systems applying IoT paradigm to the transport safety applications in order to enable driver assistance become part of Internet of Vehicles (IoV). The research proposed the architecture of the Safe Intelligent DAS (SiDAS) based on IoT V2X communications in order to combine different types of data from different available devices and vehicle systems. The research proposed IoT ARM structure for SiDAS, data flow diagrams, protocols. The study proposes several IoT system structures for the vehicle-pedestrian and vehicle-vehicle collision prediction as case studies for the flexible SiDAS framework architecture. The research has demonstrated the significant increase in driver situation awareness by using IoT SiDAS, especially in NLOS conditions. Moreover, the time analysis, taking into account IoT, Cloud, LTE and DSRS latency, has been provided for different collision scenarios, in order to evaluate the overall system latency and ensure applicability for real-time driver emergency notification. Experimental results demonstrate that the proposed SiDAS improves traffic safety