Consensus-based Time Synchronization Algorithms for Wireless Sensor Networks with Topological Optimization Strategies for Performance Improvement

Wireless Sensor Networks(WSNs)have received considerable attention in recent years because of its broad area of applications.In the same breadth,it also faces many challenges.Time synchronization is one of those fundamental challenges faced by WSN being a distributed system.It is a service by which all nodes in the network will share a common notion of time.It is a prerequisite for correctness of other protocols and services like security,localization and tracking protocols.Several approaches have been proposed in the last decade for time synchronization in WSNs.The well-known methods are based on synchronizing to a reference(root)node's time by considering a hierarchical backbone for the network.However,this approach seems to be not purely distributed,higher accumulated synchronization error for the farthest node from the root and subjected to the root node failure problem.Recently,consensus based approaches are gaining popularity due its computational lightness,robustness, and distributed nature.In this thesis,average consensus-based time synchronization algorithms are proposed,aiming to improve the performance metrics like number of iterations for convergence,total synchronization error,local synchronization error,message complexity,and scalability.Further,to cope up with energy constraint environment, Genetic algorithm based topological optimization strategies are proposed to minimize energy consumption and to accelerate the consensus convergence of the existing consensus-based time synchronization algorithms.All algorithms are analyzed mathematically and validated through simulation in MATLAB based PROWLER simulator.Firstly,a distributed Selective Average Time Synchronization (SATS) algorithm is proposed based on average consensus theory.The algorithm is purely distributed(runs at each node),and each node exploits a selective averaging with the neighboring node having maximum clock difference. To identify the neighboring node with maximum clock difference,every node broadcasts a synchronization initiation message to the neighboring nodes at its local oscillation period and waits for a random interval to get the synchronization acknowledgment messages.After receiving acknowledgment messages,a node estimates relative clock value and sends an averaging message to the selected node.The iteration continues until all nodes reach an acceptable synchronization error bound. The optimal convergence of the proposed SATS algorithm is analyzed and validated through simulation and compared with some state-of-the-art,average consensus based time synchronization algorithms. Furthermore, it is observed that most of the consensus-based time synchronization algorithms are one-hop in nature, i.e., the algorithms iterate by averaging with one-hop neighbors' clock value. In a sparse network with a lower average degree of connectivity, these algorithms show poor performance. In order to have better convergence on the sparse network, a multi-hop SATS algorithm is proposed. The basic principle of multi-hop SATS algorithm remains same as that of SATS algorithm, i.e., performing selective averaging with the neighboring node, having maximum clock difference. But, in this case, the search for neighboring node goes beyond one hop. The major challenge lies in multi-hop search is the end-to-end delay which increases with the increase in hop count. So, to search a multi-hop neighboring node with maximum clock difference and with minimum and bounded end-to-end delay, a distributed, constraint-based dynamic programming approach is proposed for multi-hop SATS algorithm. The performance of the proposed multi-hop SATS algorithm is compared with some one-hop consensus time synchronization algorithms. Simulation results show notable improvement in terms of convergence speed, total synchronization error within a restricted hop count. The trade-off with the increase in number of hops is also studied. The well-known consensus-based time synchronization algorithms are ``all node based'', i.e., every node iterates the algorithm to reach the synchronized state. This increases the overall message complexity and consumption of energy. Further, congestion in the network increases due to extensive synchronization message exchanges and induces the delay in the network. The delay induced in the message exchange is the main source of synchronization error and slows down the convergence speed to the synchronized (consensus) state. Hence, it is desirable that a subset of sensors along with a reasonable number of neighboring sensors should be selected in such a way that the resultant logical topology will accelerate the consensus algorithm with optimal message complexity and minimizes energy consumption. This problem is formulated as topological optimization problem which is claimed to be NP-complete in nature. Therefore, Genetic Algorithm (GA) based approaches are used to tackle this problem. Considering dense network topology, a single objective GA-based approach is proposed and considering sparse topology, a multi-objective Random Weighted GA based approach is proposed. Using the proposed topological optimization strategy, significant improvements are observed for consensus-based time synchronization algorithms in terms of average number of messages exchanged, energy consumption, and average mean square synchronization error

Bio-Inspired Tools for a Distributed Wireless Sensor Network Operating System

The problem which I address in this thesis is to find a way to organise and manage a network of wireless sensor nodes using a minimal amount of communication. To find a solution I explore the use of Bio-inspired protocols to enable WSN management while maintaining a low communication overhead. Wireless Sensor Networks (WSNs) are loosely coupled distributed systems comprised of low-resource, battery powered sensor nodes. The largest problem with WSN management is that communication is the largest consumer of a sensor node’s energy. WSN management systems need to use as little communication as possible to prolong their operational lifetimes. This is the Wireless Sensor Network Management Problem. This problem is compounded because current WSN management systems glue together unrelated protocols to provide system services causing inter-protocol interference. Bio-inspired protocols provide a good solution because they enable the nodes to self-organise, use local area communication, and can combine their communication in an intelligent way with minimal increase in communication. I present a combined protocol and MAC scheduler to enable multiple service protocols to function in a WSN at the same time without causing inter-protocol interference. The scheduler is throughput optimal as long as the communication requirements of all of the protocols remain within the communication capacity of the network. I show that the scheduler improves a dissemination protocol’s performance by 35%. A bio-inspired synchronisation service is presented which enables wireless sensor nodes to self organise and provide a time service. Evaluation of the protocol shows an 80% saving in communication over similar bio-inspired synchronisation approaches. I then add an information dissemination protocol, without significantly increasing communication. This is achieved through the ability of our bio-inspired algorithms to combine their communication in an intelligent way so that they are able to offer multiple services without requiring a great deal of inter-node communication.Open Acces

RF signal sensing and source localisation systems using Software Defined Radios

Radio frequency (RF) source localisation is a critical technology in numerous location-based military and civilian applications. In this thesis, the problem of RF source localisation has been studied from the perspective of the system implementation for real-world applications. Commercial off-the-shelf Software Defined Radio (SDR) devices are used to demonstrate the practical RF source localisation systems. Compared to the conventional localisation systems, which rely on dedicated hardware, the SDR-based system is developed using general-purpose hardware and software-defined components, offering great flexibility and cost efficiency in system design and implementation. In this thesis, the theoretical results of source localisation are evaluated and put into practice. To be specific, the practical localisation systems using different measurement techniques, including received-signal-strength-indication (RSSI) measurements, time-difference-of-arrival (TDOA) measurements and joint TDOA and frequency-difference-of-arrival (FDOA) measurements, are demonstrated to localise the stationary RF signal sources using the SDRs. The RSSI-based localisation system is demonstrated in small indoor and outdoor areas with a range of several metres using the SDR-based transceivers. Furthermore, interests from the defence area motivated us to implement the time-based localisation systems. The TDOA-based source localisation system is implemented using multiple spatially distributed SDRs in a large outdoor area with the sensor-target range of several kilometres. Moreover, they are implemented in a fully passive way without prior knowledge of the signal emitter, so the solutions can be applied in the localisation of non-cooperative signal sources provided that emitters are distant. To further reduce the system cost, and more importantly, to deal with the situation when the deployment of multiple SDRs, due to geographical restrictions, is not feasible, a joint TDOA and FDOA-based localisation system is also demonstrated using only one stationary SDR and one mobile SDR. To improve the localisation accuracy, the methods that can reduce measurement error and obtain accurate location estimates are studied. Firstly, to obtain a better understanding of the measurement error, the error sources that affect the measurement accuracy are systematically analysed from three aspects: the hardware precision, the accuracy of signal processing methods, and the environmental impact. Furthermore, the approaches to reduce the measurement error are proposed and verified in the experiments. Secondly, during the process of the location estimation, the theoretical results on the pre-existing localisation algorithms which can achieve a good trade-off between the accuracy of location estimation and the computational cost are evaluated, including the weight least-squares (WLS)-based solution and the Extended Kalman Filter (EKF)-based solution. In order to use the pre-existing algorithms in the practical source localisation, the proper adjustments are implemented. Overall, the SDR-based platforms are able to achieve low-cost and universal localisation solutions in the real-world environment. The RSSI-based localisation system shows tens of centimetres of accuracy in a range of several metres, which provides a useful tool for the verification of the range-based localisation algorithms. The localisation accuracy of the TDOA-based localisation system and the joint TDOA and FDOA-based localisation system is several tens of metres in a range of several kilometres, which offers potential in the low-cost localisation solutions in the defence area

Harnessing Knowledge, Innovation and Competence in Engineering of Mission Critical Systems

This book explores the critical role of acquisition, application, enhancement, and management of knowledge and human competence in the context of the largely digital and data/information dominated modern world. Whilst humanity owes much of its achievements to the distinct capability to learn from observation, analyse data, gain insights, and perceive beyond original realities, the systematic treatment of knowledge as a core capability and driver of success has largely remained the forte of pedagogy. In an increasingly intertwined global community faced with existential challenges and risks, the significance of knowledge creation, innovation, and systematic understanding and treatment of human competence is likely to be humanity's greatest weapon against adversity. This book was conceived to inform the decision makers and practitioners about the best practice pertinent to many disciplines and sectors. The chapters fall into three broad categories to guide the readers to gain insight from generic fundamentals to discipline-specific case studies and of the latest practice in knowledge and competence management

Wireless indoor localisation within the 5G internet of radio light

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonNumerous applications can be enhanced by accurate and efficient indoor localisation using wireless sensor networks, however trade-offs often exist between these two parameters. In this thesis, realworld and simulation data is used to examine the hybrid millimeter wave and Visible Light Communications (VLC) architecture of the 5G Internet of Radio Light (IoRL) Horizon 2020 project. Consequently, relevant localisation challenges within Visible Light Positioning (VLP) and asynchronous sampling networks are identified, and more accurate and efficient solutions are developed. Currently, VLP relies strongly on the assumed Lambertian properties of light sources. However, in practice, not all lights are Lambertian. To support the widespread deployment of VLC technology in numerous environments, measurements from non-Lambertian sources are analysed to provide new insights into the limitations of existing VLP techniques. Subsequently, a novel VLP calibration technique is proposed, and results indicate a 59% accuracy improvement against existing methods. This solution enables high accuracy centimetre level VLP to be achieved with non- Lambertian sources. Asynchronous sampling of range-based measurements is known to impact localisation performance negatively. Various Asynchronous Sampling Localisation Techniques (ASLT) exist to mitigate these effects. While effective at improving positioning performance, the exact suitability of such solutions is not evident due to their additional processes, subsequent complexity, and increased costs. As such, extensive simulations are conducted to study the effectiveness of ASLT under variable sampling latencies, sensor measurement noise, and target trajectories. Findings highlight the computational demand of existing ASLT and motivate the development of a novel solution. The proposed Kalman Extrapolated Least Squares (KELS) method achieves optimal localisation performance with a significant energy reduction of over 50% when compared to current leading ASLT. The work in this thesis demonstrates both the capability for high performance VLP from non- Lambertian sources as well as the potential for energy efficient localisation for sequentially sampled range measurements.Horizon 202

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks

Security and Privacy for Modern Wireless Communication Systems

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

Synchronization in complex networks

Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analytical approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.Comment: Final version published in Physics Reports. More information available at http://synchronets.googlepages.com

Architectures and synchronization techniques for distributed satellite systems: a survey

Cohesive Distributed Satellite Systems (CDSSs) is a key enabling technology for the future of remote sensing and communication missions. However, they have to meet strict synchronization requirements before their use is generalized. When clock or local oscillator signals are generated locally at each of the distributed nodes, achieving exact synchronization in absolute phase, frequency, and time is a complex problem. In addition, satellite systems have significant resource constraints, especially for small satellites, which are envisioned to be part of the future CDSSs. Thus, the development of precise, robust, and resource-efficient synchronization techniques is essential for the advancement of future CDSSs. In this context, this survey aims to summarize and categorize the most relevant results on synchronization techniques for Distributed Satellite Systems (DSSs). First, some important architecture and system concepts are defined. Then, the synchronization methods reported in the literature are reviewed and categorized. This article also provides an extensive list of applications and examples of synchronization techniques for DSSs in addition to the most significant advances in other operations closely related to synchronization, such as inter-satellite ranging and relative position. The survey also provides a discussion on emerging data-driven synchronization techniques based on Machine Learning (ML). Finally, a compilation of current research activities and potential research topics is proposed, identifying problems and open challenges that can be useful for researchers in the field.This work was supported by the Luxembourg National Research Fund (FNR), through the CORE Project COHEsive SATellite (COHESAT): Cognitive Cohesive Networks of Distributed Units for Active and Passive Space Applications, under Grant FNR11689919.Award-winningPostprint (published version