9 research outputs found

    Joint Resources and Workflow Scheduling in UAV-Enabled Wirelessly-Powered MEC for IoT Systems

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    This paper considers a UAV-enabled mobile edge computing (MEC) system, where a UAV first powers the Internet of things device (IoTD) by utilizing Wireless Power Transfer (WPT) technology. Then each IoTD sends the collected data to the UAV for processing by using the energy harvested from the UAV. In order to improve the energy efficiency of the UAV, we propose a new time division multiple access (TDMA) based workflow model, which allows parallel transmissions and executions in the UAV-assisted system. We aim to minimize the total energy consumption of the UAV by jointly optimizing the IoTDs association, computing resources allocation, UAV hovering time, wireless powering duration and the services sequence of the IoTDs. The formulated problem is a mixed-integer non-convex problem, which is very difficult to solve in general. We transform and relax it into a convex problem and apply flow-shop scheduling techniques to address it. Furthermore, an alternative algorithm is developed to set the initial point closer to the optimal solution. Simulation results show that the total energy consumption of the UAV can be effectively reduced by the proposed scheme compared with the conventional systems

    Holistic resource management in UAV-assisted wireless networks

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    Unmanned aerial vehicles (UAVs) are considered as a promising solution to assist terrestrial networks in future wireless networks (i.e., beyond fifth-generation (B5G) and sixth-generation (6G)). The convergence of various technologies requires future wireless networks to provide multiple functionalities, including communication, computing, control, and caching (4C), necessary for applications such as connected robotics and autonomous systems. The majority of existing works consider the developments in 4C individually, which limits the cooperation among 4C for potential gains. UAVs have been recently introduced to supplement mobile edge computing (MEC) in terrestrial networks to reduce network latency by providing mobile resources at the network edge in future wireless networks. However, compared to ground base stations (BSs), the limited resources at the network edge call for holistic management of the resources, which requires joint optimization. We provide a comprehensive review of holistic resource management in UAV-assisted wireless networks. Integrated resource management considers the challenges associated with aerial networks (such as three-dimensional (3D) placement of UAVs, trajectory planning, channel modelling, and backhaul connectivity) and terrestrial networks (such as limited bandwidth, power, and interference). We present architectures (source-UAV-destination and UAV-destination architecture) and 4C in UAV-assisted wireless networks. We then provide a detailed discussion on resource management by categorizing the optimization problems into individual or combinations of two (communication and computation) or three (communication, computation and control). Moreover, solution approaches and performance metrics are discussed and analyzed for different objectives and problem types. We formulate a mathematical framework for holistic resource management to minimize the linear combination of network latency and cost for user association while guaranteeing the offloading, computing, and caching constraints. Binary decision variables are used to allocate offloading and computing resources. Since the decision variables are binary and constraints are linear, the formulated problem is a binary linear programming problem. We propose a heuristic algorithm based on the interior point method by exploiting the optimization structure of the problem to get a sub-optimal solution with less complexity. Simulation results show the effectiveness of the proposed work when compared to the optimal results obtained using branch and bound. Finally, we discuss insight into the potential future research areas to address the challenges of holistic resource management in UAV-assisted wireless networks

    Urban Informatics

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    This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

    Urban Informatics

    Get PDF
    This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

    Urban Informatics

    Get PDF
    This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity
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