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Author: Sai Saketh Nandan Perala
Publisher:
ISBN:
Category : Image processing
Languages : en
Pages : 106
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Book Description
The Internet-of-Things (IoT) is a network of interconnected devices with sensing, monitoring and processing functionalities that work in a cooperative way to offer services. Smart buildings, self-driving cars, house monitoring and management, city electricity and pollution monitoring are some examples where IoT systems have been already deployed. Amongst different kinds of devices in IoT, cameras play a vital role, since they can capture rich and resourceful content. However, since multiple IoT devices share the same gateway, the data that is produced from high definition cameras congest the network and deplete the available computational resources resulting in Quality-of-Service degradation corresponding to the visual content. In this thesis, we present an edge-based resource management framework for serving video processing applications in an Internet-of-Things (IoT) environment. In order to support the computational demands of latency-sensitive video applications and utilize effectively the available network resources, we employ edge-based resource management policy. We evaluate our proposed framework with a face recognition use case.
Author: Sai Saketh Nandan Perala
Publisher:
ISBN:
Category : Image processing
Languages : en
Pages : 106
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Book Description
The Internet-of-Things (IoT) is a network of interconnected devices with sensing, monitoring and processing functionalities that work in a cooperative way to offer services. Smart buildings, self-driving cars, house monitoring and management, city electricity and pollution monitoring are some examples where IoT systems have been already deployed. Amongst different kinds of devices in IoT, cameras play a vital role, since they can capture rich and resourceful content. However, since multiple IoT devices share the same gateway, the data that is produced from high definition cameras congest the network and deplete the available computational resources resulting in Quality-of-Service degradation corresponding to the visual content. In this thesis, we present an edge-based resource management framework for serving video processing applications in an Internet-of-Things (IoT) environment. In order to support the computational demands of latency-sensitive video applications and utilize effectively the available network resources, we employ edge-based resource management policy. We evaluate our proposed framework with a face recognition use case.
Author: Turuk, Ashok Kumar
Publisher: IGI Global
ISBN: 1522517227
Category : Computers
Languages : en
Pages : 369
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Book Description
Today’s advancements in technology have brought about a new era of speed and simplicity for consumers and businesses. Due to these new benefits, the possibilities of universal connectivity, storage and computation are made tangible, thus leading the way to new Internet-of Things solutions. Resource Management and Efficiency in Cloud Computing Environments is an authoritative reference source for the latest scholarly research on the emerging trends of cloud computing and reveals the benefits cloud paths provide to consumers. Featuring coverage across a range of relevant perspectives and topics, such as big data, cloud security, and utility computing, this publication is an essential source for researchers, students and professionals seeking current research on the organization and productivity of cloud computing environments.
Author: Ioannis Galanis
Publisher:
ISBN:
Category : Edge computing
Languages : en
Pages : 372
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Book Description
The Internet of Things (IoT) computing paradigm has connected smart objects "things" and has brought new services at the proximity of the user. Edge Computing, a natural evolution of the traditional IoT, has been proposed to deal with the ever-increasing (i) number of IoT devices and (ii) the amount of data traffic that is produced by the IoT endpoints. EC promises to significantly reduce the unwanted latency that is imposed by the multi-hop communication delays and suggests that instead of uploading all the data to the remote cloud for further processing, it is beneficial to perform computation at the "edge" of the network, close to where the data is produced. However, bringing computation at the edge level has created numerous challenges as edge devices struggle to keep up with the growing application requirements (e.g. Neural Networks, or video-based analytics). In this thesis, we adopt the EC paradigm and we aim at addressing the open challenges. Our goal is to bridge the performance gap that is caused by the increased requirements of the IoT applications with respect to the IoT platform capabilities and provide latency- and energy-efficient computation at the edge level. Our first step is to study the performance of IoT applications that are based on Deep Neural Networks (DNNs). The exploding need to deploy DNN-based applications on resource-constrained edge devices has created several challenges, mainly due to the complex nature of DNNs. DNNs are becoming deeper and wider in order to fulfill users expectations for high accuracy, while they also become power hungry. For instance, executing a DNN on an edge device can drain the battery within minutes. Our solution to make DNNs more energy and inference friendly is to propose hardware-aware method that re-designs a given DNN architecture. Instead of proxy metrics, we measure the DNN performance on real edge devices and we capture their energy and inference time. Our method manages to find alternative DNN architectures that consume up to 78.82% less energy and are up to 35.71% faster than the reference networks. In order to achieve end-to-end optimal performance, we also need to manage the edge device resources that will execute a DNN-based application. Due to their unique characteristics, we distinguish the edge devices into two categories: (i) a neuromorphic platform that is designed to execute Spiking Neural Networks (SNNs), and (ii) a general-purpose edge device that is suitable to host a DNN. For the first category, we train a traditional DNN and then we convert it to a spiking representation. We target the SpiNNaker neuromorphic platform and we develop a novel technique that efficiently configures the platform-dependent parameters, in order to achieve the highest possible SNN accuracy. Experimental results show that our technique is 2.5× faster than an exhaustive approach and can reach up to 0.8% higher accuracy compared to a CPU-based simulation method. Regarding the general-purpose edge devices, we show that a DNN-unaware platform can result in sub-optimal DNN performance in terms of power and inference time. Our approach configures the frequency of the device components (GPU, CPU, Memory) and manages to achieve average of 33.4% and up to 66.3% inference time improvements and an average of 42.8% and up to 61.5% power savings compared to the predefined configuration of an edge device. The last part of this thesis is the offloading optimization between the edge devices and the gateway. The offloaded tasks create contention effects on gateway, which can lead to application slowdown. Our proposed solution configures (i) the number of application stages that are executed on each edge device, and (ii) the achieved utility in terms of Quality of Service (QoS) on each edge device. Our technique manages to (i) maximize the overall QoS, and (ii) simultaneously satisfy network constraints (bandwidth) and user expectations (execution time). In case of multi-gateway deployments, we tackled the problem of unequal workload distribution. In particular, we propose a workload-aware management scheme that performs intra- and inter-gateway optimizations. The intra-gateway mechanism provides a balanced execution environment for the applications, and it achieves up to 95% performance deviation improvement, compared to un-optimized systems. The presented inter-gateway method manages to balance the workload among multiple gateways and is able to achieve a global performance threshold.
Author: Aboul Ella Hassanien
Publisher: Academic Press
ISBN: 0128182881
Category : Science
Languages : en
Pages : 192
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Book Description
Internet of Things (IoT) is a new platform of various physical objects or “things equipped with sensors, electronics, smart devices, software, and network connections. IoT represents a new revolution of the Internet network which is driven by the recent advances of technologies such as sensor networks (wearable and implantable), mobile devices, networking, and cloud computing technologies. IoT permits these the smart devices to collect, store and analyze the collected data with limited storage and processing capacities. Swarm Intelligence for Resource Management in the Internet of Things presents a new approach in Artificial Intelligence that can be used for resources management in IoT, which is considered a critical issue for this network. The authors demonstrate these resource management applications using swarm intelligence techniques. Currently, IoT can be used in many important applications which include healthcare, smart cities, smart homes, smart hospitals, environment monitoring, and video surveillance. IoT devices cannot perform complex on-site data processing due to their limited battery and processing. However, the major processing unit of an application can be transmitted to other nodes, which are more powerful in terms of storage and processing. By applying swarm intelligence algorithms for IoT devices, we can provide major advantages for energy saving in IoT devices. Swarm Intelligence for Resource Management in the Internet of Things shows the reader how to overcome the problems and challenges of creating and implementing swarm intelligence algorithms for each application Examines the development and application of swarm intelligence systems in artificial intelligence as applied to the Internet of Things Discusses intelligent techniques for the implementation of swarm intelligence in IoT Prepared for researchers and specialists who are interested in the use and integration of IoT and cloud computing technologies
Author: Monika Mangla
Publisher: CRC Press
ISBN: 1000565033
Category : Computers
Languages : en
Pages : 536
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Book Description
This new volume provides an overview of the Internet of Things along with its architectures, its vital technologies, and their uses in our daily life. The book explores the integration of IoT with other emerging technologies, such as blockchain and cloud. Topics in the volume cover the many powerful features and applications of IoT, such as for weather forecasting, in agriculture, in medical science, in surveillance systems, and much more. The first section of the book covers many of the issues and challenges that arise from the Internet of Things (IoT), exploring security challenges, such as attack detection and prevention systems, as well as energy efficiency and resource management in IoT. The volume also introduces the use of IoT and smart technology in agricultural management, in healthcare diagnosis and monitoring, and in the financial industry. Chapters also focus on surveillance network technology, the technology shift from television to video streaming apps, using IoT–fog computing for smart healthcare, detection of anomalies in climate conditions, and even detection of illegal wood logging activity.
Author: Santosh Ganesh, Kapila Mehta
Publisher: Notion Press
ISBN:
Category : Business & Economics
Languages : en
Pages : 494
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Book Description
In an era where sustainability and responsible business practices are paramount, "The Circular Economy: A Blueprint for the Future of Business" offers a comprehensive guide to understanding and embracing this transformative concept. The objective of this book is to enlighten readers about the Circular Economy, its principles, and how it is reshaping the landscape of modern business. The book serves as a roadmap for businesses, entrepreneurs, policymakers, and individuals who aspire to thrive in a world where environmental stewardship and economic growth go hand in hand. It begins by defining the Circular Economy and unraveling its core principles, emphasizing resource efficiency, waste reduction, and the creation of regenerative systems.
Author: Kostas Siozios
Publisher: Springer
ISBN: 3030036405
Category : Technology & Engineering
Languages : en
Pages : 289
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Book Description
This book explains the fundamentals of control theory for Internet of Things (IoT) systems and smart grids and its applications. It discusses the challenges imposed by large-scale systems, and describes the current and future trends and challenges in decision-making for IoT in detail, showing the ongoing industrial and academic research in the field of smart grid domain applications. It presents step-by-step design guidelines for the modeling, design, customisation and calibration of IoT systems applied to smart grids, in which the challenges increase with each system’s increasing complexity. It also provides solutions and detailed examples to demonstrate how to use the techniques to overcome these challenges, as well as other problems related to decision-making for successful implementation. Further, it anaylses the features of decision-making, such as low-complexity and fault-tolerance, and uses open-source and publicly available software tools to show readers how they can design, implement and customise their own system control instantiations. This book is a valuable resource for power engineers and researchers, as it addresses the analysis and design of flexible decision-making mechanisms for smart grids. It is also of interest to students on courses related to control of large-scale systems, since it covers the use of state-of-the-art technology with examples and solutions in every chapter. And last but not least, it offers practical advice for professionals working with smart grids.
Author: Rodrigues, Joel J. P. C.
Publisher: IGI Global
ISBN: 1522578129
Category : Computers
Languages : en
Pages : 317
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Book Description
Advances in computing, communications, and control have bridged the physical components of reality and cyberspace leading to the smart internet of things (IoT). The notion of IoT has extraordinary significance for the future of several industrial domains. Hence, it is expected that the complexity in the design of IoT applications will continue to increase due to the integration of several cyber components with physical and industrial systems. As a result, several smart protocols and algorithms are needed to communicate and exchange data between IoT devices. Smart Devices, Applications, and Protocols for the IoT is a collection of innovative research that explores new methods and techniques for achieving reliable and efficient communication in recent applications including machine learning, network optimization, adaptive methods, and smart algorithms and protocols. While highlighting topics including artificial intelligence, sensor networks, and mobile network architectures, this book is ideally designed for IT specialists and consultants, software engineers, technology developers, academicians, researchers, and students seeking current research on up-to-date technologies in smart communications, protocols, and algorithms in IoT.
Author: Khang, Alex
Publisher: IGI Global
ISBN:
Category : Medical
Languages : en
Pages : 585
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Book Description
In the post-COVID-19 healthcare landscape, the demand for smart healthcare solutions and precision medicine systems has grown significantly. To address these challenges, the book AI and IoT-Based Technologies for Precision Medicine provides a comprehensive resource for doctors, researchers, engineers, and students. By leveraging AI and IoT technologies, the book equips healthcare professionals with advanced tools and methodologies for predictive disease analysis, informed decision-making, and other aspects of precision medicine. This resource bridges the gap between theory and practice, exploring concepts like machine learning, deep learning, computer vision, AI-integrated applications, IoT-based technologies, healthcare data analytics, and biotechnology applications. Through this, the book empowers healthcare practitioners to pioneer innovative solutions that enhance efficiency, accuracy, and security in medical practices. AI and IoT-Based Technologies for Precision Medicine not only offer insights into the potential of AI-powered applications and IoT-equipped techniques in smart healthcare but also foster collaboration among healthcare scholars and professionals. This authoritative guide encourages knowledge sharing and collaboration to harness the transformative potential of AI and IoT, leading to revolutionary advancements in medical practices and healthcare services. With this book as a guide, readers can navigate the evolving landscape of high-tech medicine, taking confident steps toward a cutting-edge and precise medical ecosystem.
Author: T.P. Jimmy To
Publisher: Springer Science & Business Media
ISBN: 9780792383208
Category : Computers
Languages : en
Pages : 154
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Book Description
Interactive Video-on-Demand Systems: Resource Management and Scheduling Strategies addresses issues in scheduling and management of resources in an interactive continuous-media (e.g., audio and video) server. The book emphasizes dynamic and run-time strategies for resource scheduling and management. Such strategies provide effective tools for supporting interactivity with on-line users who require the system to be responsive in serving their requests, and whose needs and actions vary frequently over time. With an emphasis on responsiveness and transient performance, this book elaborates on dynamic strategies for managing and scheduling resources in Video-on-Demand/Multimedia systems. Unlike previous books, this volume presents an unprecedented detailed analysis of the start-up and departure of streams. It gives a comprehensive evaluation of various techniques as workloads are varied in multiple dimensions (including arrival rate, data rate and length of play). Interactive Video-on-Demand Systems: Resource Management and Scheduling Strategies collectively addresses multiple issues including QoS, throughput, responsiveness and efficiency. The solutions discussed in this volume are particularly valuable to practitioners who are building digital library, interactive multimedia and hypermedia servers. Interactive Video-on-Demand Systems: Resource Management and Scheduling Strategies is an excellent reference for researchers, practitioners and educators in the field of multimedia systems, and may be used for advanced courses on multimedia systems and Video-on-Demand servers.
