Energy-Efficient and Fresh Data Collection in IoT Networks by Machine Learning

The Internet-of-Things (IoT) is rapidly changing our lives in almost every field, such as smart agriculture, environmental monitoring, intelligent manufacturing system, etc. How to improve the efficiency of data collection in IoT networks has attracted increasing attention. Clustering-based algorithms are the most common methods used to improve the efficiency of data collection. They group devices into distinct clusters, where each device belongs to one cluster only. All member devices sense their surrounding environment and transmit the results to the cluster heads (CHs). The CHs then send the received data to a control center via single-hop or multi-hops transmission. Using unmanned aerial vehicles (UAVs) to collect data in IoT networks is another effective method for improving the efficiency of data collection. This is because UAVs can be flexibly deployed to communicate with ground devices via reliable air-to-ground communication links. Given that energy-efficient data collection and freshness of the collected data are two important factors in IoT networks, this thesis is concerned with designing algorithms to improve the energy efficiency of data collection and guarantee the freshness of the collected data. Our first contribution is an improved soft-k-means (IS-k-means) clustering algorithm that balances the energy consumption of nodes in wireless sensor networks (WSNs). The techniques of “clustering by fast search and find of density peaks” (CFSFDP) and kernel density estimation (KDE) are used to improve the selection of the initial cluster centers of the soft k-means clustering algorithm. Then, we utilize the flexibility of the soft-k-means and reassign member nodes by considering their membership probabilities at the boundary of clusters to balance the number of nodes per cluster. Furthermore, we use multi-CHs to balance the energy consumption within clusters. Extensive simulation results show that, on average, the proposed algorithm can postpone the first node death, the half of nodes death, and the last node death when compared to various clustering algorithms from the literature. The second contribution tackles the problem of minimizing the total energy consumption of the UAV-IoT network. Specifically, we formulate and solve the optimization problem that jointly finds the UAV’s trajectory and selects CHs in the IoT network. The formulated problem is a constrained combinatorial optimization and we develop a novel deep reinforcement learning (DRL) with a sequential model strategy to solve it. The proposed method can effectively learn the policy represented by a sequence-to-sequence neural network for designing the UAV’s trajectory in an unsupervised manner. Extensive simulation results show that the proposed DRL method can find the UAV’s trajectory with much less energy consumption when compared to other baseline algorithms and achieves close-to-optimal performance. In addition, simulation results show that the model trained by our proposed DRL algorithm has an excellent generalization ability, i.e., it can be used for larger-size problems without the need to retrain the model. The third contribution is also concerned with minimizing the total energy consumption of the UAV-aided IoT networks. A novel DRL technique, namely the pointer network-A* (Ptr-A*), is proposed, which can efficiently learn the UAV trajectory policy for minimizing the energy consumption. The UAV’s start point and the ground network with a set of pre-determined clusters are fed to the Ptr-A*, and the Ptr-A* outputs a group of CHs and the visiting order of CHs, i.e., the UAV’s trajectory. The parameters of the Ptr-A* are trained on problem instances having small-scale clusters by using the actor-critic algorithm in an unsupervised manner. Simulation results show that the models trained based on 20- clusters and 40-clusters have a good generalization ability to solve the UAV’s trajectory planning problem with different numbers of clusters, without the need to retrain the models. Furthermore, the results show that our proposed DRL algorithm outperforms two baseline techniques. In the last contribution, the new concept, age-of-information (AoI), is used to quantify the freshness of collected data in IoT networks. An optimization problem is formulated to minimize the total AoI of the collected data by the UAV from the ground IoT network. Since the total AoI of the IoT network depends on the flight time of the UAV and the data collection time at hovering points, we jointly optimize the selection of the hovering points and the visiting order to these points. We exploit the state-of-the-art transformer and the weighted A* to design a machine learning algorithm to solve the formulated problem. The whole UAV-IoT system, including all ground clusters and potential hovering points of the UAV, is fed to the encoder network of the proposed algorithm, and the algorithm’s decoder network outputs the visiting order to ground clusters. Then, the weighted A* is used to find the hovering point for each cluster in the ground IoT network. Simulation results show that the model trained by the proposed algorithm has a good generalization ability to generate solutions for IoT networks with different numbers of ground clusters, without the need to retrain the model. Furthermore, results show that our proposed algorithm can find better UAV trajectories with the minimum total AoI when compared to other algorithms

Portfolio peak algorithms achieving superior performance for maximizing throughput in WiMAX networks

The Mobile WiMAX IEEE 802.16 standards ensure provision of last mile wireless access, variable and high data rate, point to multi-point communication, large frequency range and QoS (Quality of Service) for various types of applications. The WiMAX standards are published by the Institute of Electric and Electronic Engineers (IEEE) and specify the standards of services and transmissions. However, the way how to run these services and when the transmission should be started are not specified in the IEEE standards and it is up to computer scientists to design scheduling algorithms that can best meet the standards. Finding the best way to implement the WiMAX standards through designing efficient scheduler algorithms is a very important component in wireless systems and the scheduling period presents the most common challenging issue in terms of throughput and time delay. The aim of the research presented in this thesis was to design and develop an efficient scheduling algorithm to provide the QoS support for real-time and non-real-time services with the WiMAX Network. This was achieved by combining a portfolio of algorithms, which will control and update transmission with the required algorithm by the various portfolios for supporting QoS such as; the guarantee of a maximum throughput for real-time and non-real-time traffic. Two algorithms were designed in this process and will be discussed in this thesis: Fixed Portfolio Algorithms and Portfolio Peak Algorithm. In order to evaluate the proposed algorithms and test their efficiency for IEEE 802.16 networks, the authors simulated the algorithms in the NS2 simulator. Evaluation of the proposed Portfolio algorithms was carried out through comparing its performance with those of the conventional algorithms. On the other hand, the proposed Portfolio scheduling algorithm was evaluated by comparing its performance in terms of throughput, delay, and jitter. The simulation results suggest that the Fixed Portfolio Algorithms and the Portfolio Peak Algorithm achieve higher performance in terms of throughput than all other algorithms. Keywords: WiMAX, IEEE802.16, QoS, Scheduling Algorithms, Fixed Portfolio Algorithms, and Portfolio Peak Algorithms.The Mobile WiMAX IEEE 802.16 standards ensure provision of last mile wireless access, variable and high data rate, point to multi-point communication, large frequency range and QoS (Quality of Service) for various types of applications. The WiMAX standards are published by the Institute of Electric and Electronic Engineers (IEEE) and specify the standards of services and transmissions. However, the way how to run these services and when the transmission should be started are not specified in the IEEE standards and it is up to computer scientists to design scheduling algorithms that can best meet the standards. Finding the best way to implement the WiMAX standards through designing efficient scheduler algorithms is a very important component in wireless systems and the scheduling period presents the most common challenging issue in terms of throughput and time delay. The aim of the research presented in this thesis was to design and develop an efficient scheduling algorithm to provide the QoS support for real-time and non-real-time services with the WiMAX Network. This was achieved by combining a portfolio of algorithms, which will control and update transmission with the required algorithm by the various portfolios for supporting QoS such as; the guarantee of a maximum throughput for real-time and non-real-time traffic. Two algorithms were designed in this process and will be discussed in this thesis: Fixed Portfolio Algorithms and Portfolio Peak Algorithm. In order to evaluate the proposed algorithms and test their efficiency for IEEE 802.16 networks, the authors simulated the algorithms in the NS2 simulator. Evaluation of the proposed Portfolio algorithms was carried out through comparing its performance with those of the conventional algorithms. On the other hand, the proposed Portfolio scheduling algorithm was evaluated by comparing its performance in terms of throughput, delay, and jitter. The simulation results suggest that the Fixed Portfolio Algorithms and the Portfolio Peak Algorithm achieve higher performance in terms of throughput than all other algorithms. Keywords: WiMAX, IEEE802.16, QoS, Scheduling Algorithms, Fixed Portfolio Algorithms, and Portfolio Peak Algorithms

Unified Framework for Multicarrier and Multiple Access based on Generalized Frequency Division Multiplexing

The advancements in wireless communications are the key-enablers of new applications with stringent requirements in low-latency, ultra-reliability, high data rate, high mobility, and massive connectivity. Diverse types of devices, ranging from tiny sensors to vehicles, with different capabilities need to be connected under various channel conditions. Thus, modern connectivity and network techniques at all layers are essential to overcome these challenges. In particular, the physical layer (PHY) transmission is required to achieve certain link reliability, data rate, and latency. In modern digital communications systems, the transmission is performed by means of a digital signal processing module that derives analog hardware. The performance of the analog part is influenced by the quality of the hardware and the baseband signal denoted as waveform. In most of the modern systems such as fifth generation (5G) and WiFi, orthogonal frequency division multiplexing (OFDM) is adopted as a favorite waveform due to its low-complexity advantages in terms of signal processing. However, OFDM requires strict requirements on hardware quality. Many devices are equipped with simplified analog hardware to reduce the cost. In this case, OFDM does not work properly as a result of its high peak-to-average power ratio (PAPR) and sensitivity to synchronization errors. To tackle these problems, many waveforms design have been recently proposed in the literature. Some of these designs are modified versions of OFDM or based on conventional single subcarrier. Moreover, multicarrier frameworks, such as generalized frequency division multiplexing (GFDM), have been proposed to realize varieties of conventional waveforms. Furthermore, recent studies show the potential of using non-conventional waveforms for increasing the link reliability with affordable complexity. Based on that, flexible waveforms and transmission techniques are necessary to adapt the system for different hardware and channel constraints in order to fulfill the applications requirements while optimizing the resources. The objective of this thesis is to provide a holistic view of waveforms and the related multiple access (MA) techniques to enable efficient study and evaluation of different approaches. First, the wireless communications system is reviewed with specific focus on the impact of hardware impairments and the wireless channel on the waveform design. Then, generalized model of waveforms and MA are presented highlighting various special cases. Finally, this work introduces low-complexity architectures for hardware implementation of flexible waveforms. Integrating such designs with software-defined radio (SDR) contributes to the development of practical real-time flexible PHY.:1 Introduction 1.1 Baseband transmission model 1.2 History of multicarrier systems 1.3 The state-of-the-art waveforms 1.4 Prior works related to GFDM 1.5 Objective and contributions 2 Fundamentals of Wireless Communications 2.1 Wireless communications system 2.2 RF transceiver 2.2.1 Digital-analogue conversion 2.2.2 QAM modulation 2.2.3 Effective channel 2.2.4 Hardware impairments 2.3 Waveform aspects 2.3.1 Single-carrier waveform 2.3.2 Multicarrier waveform 2.3.3 MIMO-Waveforms 2.3.4 Waveform performance metrics 2.4 Wireless Channel 2.4.1 Line-of-sight propagation 2.4.2 Multi path and fading process 2.4.3 General baseband statistical channel model 2.4.4 MIMO channel 2.5 Summary 3 Generic Block-based Waveforms 3.1 Block-based waveform formulation 3.1.1 Variable-rate multicarrier 3.1.2 General block-based multicarrier model 3.2 Waveform processing techniques 3.2.1 Linear and circular filtering 3.2.2 Windowing 3.3 Structured representation 3.3.1 Modulator 3.3.2 Demodulator 3.3.3 MIMO Waveform processing 3.4 Detection 3.4.1 Maximum-likelihood detection 3.4.2 Linear detection 3.4.3 Iterative Detection 3.4.4 Numerical example and insights 3.5 Summary 4 Generic Multiple Access Schemes 57 4.1 Basic multiple access and multiplexing schemes 4.1.1 Infrastructure network system model 4.1.2 Duplex schemes 4.1.3 Common multiplexing and multiple access schemes 4.2 General multicarrier-based multiple access 4.2.1 Design with fixed set of pulses 4.2.2 Computational model 4.2.3 Asynchronous multiple access 4.3 Summary 5 Time-Frequency Analyses of Multicarrier 5.1 General time-frequency representation 5.1.1 Block representation 5.1.2 Relation to Zak transform 5.2 Time-frequency spreading 5.3 Time-frequency block in LTV channel 5.3.1 Subcarrier and subsymbol numerology 5.3.2 Processing based on the time-domain signal 5.3.3 Processing based on the frequency-domain signal 5.3.4 Unified signal model 5.4 summary 6 Generalized waveforms based on time-frequency shifts 6.1 General time-frequency shift 6.1.1 Time-frequency shift design 6.1.2 Relation between the shifted pulses 6.2 Time-frequency shift in Gabor frame 6.2.1 Conventional GFDM 6.3 GFDM modulation 6.3.1 Filter bank representation 6.3.2 Block representation 6.3.3 GFDM matrix structure 6.3.4 GFDM demodulator 6.3.5 Alternative interpretation of GFDM 6.3.6 Orthogonal modulation and GFDM spreading 6.4 Summary 7 Modulation Framework: Architectures and Applications 7.1 Modem architectures 7.1.1 General modulation matrix structure 7.1.2 Run-time flexibility 7.1.3 Generic GFDM-based architecture 7.1.4 Flexible parallel multiplications architecture 7.1.5 MIMO waveform architecture 7.2 Extended GFDM framework 7.2.1 Architectures complexity and flexibility analysis 7.2.2 Number of multiplications 7.2.3 Hardware analysis 7.3 Applications of the extended GFDM framework 7.3.1 Generalized FDMA 7.3.2 Enchantment of OFDM system 7.4 Summary 7 Conclusions and Future work

Cognitive radio adaptive rendezvous protocols to establish network services for a disaster response

Disasters are catastrophic events that cause great damage or loss of life. In disasters, communication services might be disrupted due to damage to the existing network infrastructure. Temporary systems are required for victims and first responders, but installing them requires information about the radio environment and available spectrum. A cognitive radio (CR) can be used to provide a flexible and rapidly deployable temporary system due to its sensing, learning and decision-making capabilities. This thesis initially examines the potential of CR technology for disaster response networks (DRN) and shows that they are ideally suited to fulfill the requirements of a DRN. A software defined radio based prototype for multiple base transceiver stations based cellular network is proposed and developed. It is demonstrated that system can support a large number of simultaneous calls with sufficient call quality, but only when the background interference is low. It is concluded that to provide call quality with acceptable latency and packet losses, the spectrum should be used dynamically for backhaul connectivity. The deployment challenges for such a system in a disaster include the discovery of the available spectrum, existing networks, and neighbours. Furthermore, to set up a network and to establish network services, initially CR nodes are required to establish a rendezvous. However, this can be challenging due to unknown spectrum information, primary radio (PR) activity, nodes, and topology. The existing rendezvous strategies do not fulfill the DRN requirements and their time to rendezvous (TTR) is long. Therefore, we propose an extended modular clock algorithm (EMCA) which is a multiuser blind rendezvous protocol, considers the DRN requirements and has short TTR. For unknown nodes and topologies, a general framework for self-organizing multihop cooperative fully blind rendezvous protocol is also proposed, which works in different phases, can terminate when sufficient nodes are discovered, and is capable of disseminating the information of nodes which enter or leave a network. A synchronization mechanism is presented for periodic update of rendezvous information. An information exchange mechanism is also proposed which expedites the rendezvous process. In both single and multihop networks, EMCA provides up to 80% improvement in terms of TTR over the existing blind rendezvous strategies while considering the PR activity. A simple Random strategy, while being poorer than EMCA, is also shown to outperform existing strategies on average. To achieve adaptability in the presence of unknown PR activity, different CR operating policies are proposed which avoid the channels detected with PR activity to reduce the harmful interference, provide free channels to reduce the TTR, and can work with any rendezvous strategy. These policies are evaluated over different PR activities and shown to reduce the TTR and harmful interference significantly over the basic Listen before Talk approach. A proactive policy, which prefers to return to channels with recent lower PR activity, is shown to be best, and to improve the performance of all studied rendezvous strategies

Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey

The existence of representative datasets is a prerequisite of many successful artificial intelligence and machine learning models. However, the subsequent application of these models often involves scenarios that are inadequately represented in the data used for training. The reasons for this are manifold and range from time and cost constraints to ethical considerations. As a consequence, the reliable use of these models, especially in safety-critical applications, is a huge challenge. Leveraging additional, already existing sources of knowledge is key to overcome the limitations of purely data-driven approaches, and eventually to increase the generalization capability of these models. Furthermore, predictions that conform with knowledge are crucial for making trustworthy and safe decisions even in underrepresented scenarios. This work provides an overview of existing techniques and methods in the literature that combine data-based models with existing knowledge. The identified approaches are structured according to the categories integration, extraction and conformity. Special attention is given to applications in the field of autonomous driving

Third international conference on irrigation and drainage

Presented during the Third international conference on irrigation and drainage held March 30 - April 2, 2005 in San Diego, California. The theme of the conference was Water district management and governance.Includes bibliographical references.Sponsored by USCID; co-sponsored by Association of California Water Agencies and International Network for Participatory Irrigation Management.The changing face of western irrigated agriculture: structure, water management, and policy implications -- Proven institutional, financing and pricing principles for rural water services -- Involving stakeholders in irrigation and drainage district decisions: who, what, when, where, why, how -- Implementing district level irrigation water management with stakeholder participation -- WUA development and strengthening in the Kyrgyz Republic -- Variations in irrigation district voting and election procedures -- Water Users Association governance in developing countries: fragility and function -- Viet Nam: creating conditions for improved irrigation service delivery -- the case of the Phuoc Hoa Water Resources Project -- Technical and institutional support for water management in Albanian irrigation -- Reconciling traditional irrigation management with development of modern irrigation systems: the challenge for Afghanistan -- Field testing of SacMan Automated Canal Control System -- An infrastructure management system for enhanced irrigation district planning -- NCWCD efforts toward improving on-farm water management -- A web-based irrigation water use tracking system -- Using GIS to monitor water use compliance -- Development of a water management system to improve management and scheduling of water orders in Imperial Irrigation District -- Radar water-level measurement for open channels -- Non-standard structure flow measurement evaluation using the flow rate indexing procedure - QIP -- A GIS-based irrigation evaluation strategy for a rice production region -- Total Channel Control™ - an important role in identifying losses -- Commencing the modernization project of the Gila Gravity Main Canal -- Obtaining gains in efficiency when water is free -- A qualitative approach to study water markets in Pakistan -- Local groundwater management districts and Kansas state agencies share authority and responsibility for transition to long term management of the High Plains Aquifer -- Water user management and financing of irrigation facilities through use of improvement districts -- Irrigation management transfer to water user organizations in Turkey -- Farm size, irrigation practices, and on-farm irrigation efficiency in New Mexico's Elephant Butte Irrigation District -- The ITRC Rapid Appraisal Process (RAP) for irrigation districts -- Relationships between seepage loss rates and canal condition parameters for the Rapid Assessment Tool (RAT) -- Zarafshan Water District Improvement Project in Uzbekistan -- Technological modernization in irrigated agriculture: factors for sustainability in developing countries -- Reliability criteria for re-engineering of large-scale pressurized irrigation systems -- Upgrading existing databases: recommendations for irrigation districts -- Groundwater use in irrigated agriculture in Amudarya River basin in socio-economic dimensions -- Regional ET estimation from satellites

Proceedings of the inaugural construction management and economics ‘Past, Present and Future’ conference CME25, 16-18 July 2007, University of Reading, UK

This conference was an unusual and interesting event. Celebrating 25 years of Construction Management and Economics provides us with an opportunity to reflect on the research that has been reported over the years, to consider where we are now, and to think about the future of academic research in this area. Hence the sub-title of this conference: “past, present and future”. Looking through these papers, some things are clear. First, the range of topics considered interesting has expanded hugely since the journal was first published. Second, the research methods are also more diverse. Third, the involvement of wider groups of stakeholder is evident. There is a danger that this might lead to dilution of the field. But my instinct has always been to argue against the notion that Construction Management and Economics represents a discipline, as such. Granted, there are plenty of university departments around the world that would justify the idea of a discipline. But the vast majority of academic departments who contribute to the life of this journal carry different names to this. Indeed, the range and breadth of methodological approaches to the research reported in Construction Management and Economics indicates that there are several different academic disciplines being brought to bear on the construction sector. Some papers are based on economics, some on psychology and others on operational research, sociology, law, statistics, information technology, and so on. This is why I maintain that construction management is not an academic discipline, but a field of study to which a range of academic disciplines are applied. This may be why it is so interesting to be involved in this journal. The problems to which the papers are applied develop and grow. But the broad topics of the earliest papers in the journal are still relevant today. What has changed a lot is our interpretation of the problems that confront the construction sector all over the world, and the methodological approaches to resolving them. There is a constant difficulty in dealing with topics as inherently practical as these. While the demands of the academic world are driven by the need for the rigorous application of sound methods, the demands of the practical world are quite different. It can be difficult to meet the needs of both sets of stakeholders at the same time. However, increasing numbers of postgraduate courses in our area result in larger numbers of practitioners with a deeper appreciation of what research is all about, and how to interpret and apply the lessons from research. It also seems that there are contributions coming not just from construction-related university departments, but also from departments with identifiable methodological traditions of their own. I like to think that our authors can publish in journals beyond the construction-related areas, to disseminate their theoretical insights into other disciplines, and to contribute to the strength of this journal by citing our articles in more mono-disciplinary journals. This would contribute to the future of the journal in a very strong and developmental way. The greatest danger we face is in excessive self-citation, i.e. referring only to sources within the CM&E literature or, worse, referring only to other articles in the same journal. The only way to ensure a strong and influential position for journals and university departments like ours is to be sure that our work is informing other academic disciplines. This is what I would see as the future, our logical next step. If, as a community of researchers, we are not producing papers that challenge and inform the fundamentals of research methods and analytical processes, then no matter how practically relevant our output is to the industry, it will remain derivative and secondary, based on the methodological insights of others. The balancing act between methodological rigour and practical relevance is a difficult one, but not, of course, a balance that has to be struck in every single paper