Weiting Zhang (25 results)

Condition: New. Zhang, Wendy (Weiting) (illustrator).

Taschenbuch. Condition: Neu. Zhang, Wendy (Weiting) (illustrator). Neuware.

Condition: New.

Hardcover. Condition: new. Hardcover. This book investigates technologies that enable more powerful resources and improve resource utilization for end-edge-cloud networks. The authors cover tools such as federated learning (FL) and real-time inference in industrial IoT and they present a novel communication and computation integration architecture for end-edge-cloud networks. Under the considered end-edge-cloud network architecture, the authors then propose different resource scheduling schemes based on centralized and distributed deep reinforcement learning methods to improve overall resource utilization for guaranteeing the diversified quality of service (QoS) requirements from different applications. The proposed architecture and schemes can not only be adopted in future end-edge-cloud networks to efficiently manage the multi-dimensional resources in real time, but also provide useful guidelines for multi-dimensional resource scheduling scheme designing and resource utilization enhancement in complex end-edge-cloud networks with diversified data services and applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New.

Condition: New.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book investigates technologies that enable more powerful resources and improve resource utilization for end-edge-cloud networks. The authors cover tools such as federated learning (FL) and real-time inference in industrial IoT and they present a novel communication and computation integration architecture for end-edge-cloud networks. Under the considered end-edge-cloud network architecture, the authors then propose different resource scheduling schemes based on centralized and distributed deep reinforcement learning methods to improve overall resource utilization for guaranteeing the diversified quality of service (QoS) requirements from different applications. The proposed architecture and schemes can not only be adopted in future end-edge-cloud networks to efficiently manage the multi-dimensional resources in real time, but also provide useful guidelines for multi-dimensional resource scheduling scheme designing and resource utilization enhancement in complex end-edge-cloud networks with diversified data services and applications.

Hardcover. Condition: Brand New. 180 pages. 9.25x6.10x9.21 inches. In Stock.

Paperback / softback. Condition: New. Zhang, Wendy (Weiting) (illustrator). This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

HRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condition: New. Print on Demand.

Condition: New. Print on Demand.

Condition: New. PRINT ON DEMAND.

Hardcover. Condition: Brand New. 180 pages. 9.25x6.10x9.21 inches. In Stock. This item is printed on demand.

Hardcover. Condition: new. Hardcover. Mobile crowdsensing (MCS) has emerged as a pivotal element in contemporary communication technology, witnessing substantial growth recently. The advent of 5G, the Internet of Things (IoT), and edge computing has propelled MCS researchers to achieve enhanced sensing efficiency and broaden its application spectrum across various domains such as environmental monitoring, traffic management, and healthcare. However, despite these advantages, MCS confronts significant security and privacy challenges due to its open and diverse nature. Critical concerns encompass data leakage, unauthorized access, data tampering, and cross-network attacks. These issues can severely compromise the stability, privacy, and security of MCS systems. Furthermore, the dynamic mobility of users and devices within MCS introduces additional complexity to conventional security measures, particularly concerning communication and cross-domain access control. To tackle these challenges, researchers have devised several strategies aimed at bolstering the security and privacy of MCS systems. These novel protection mechanisms offer distinct benefits over traditional approaches. They are capable of securing data even with constrained computational and communication resources, enhancing system flexibility, and effectively thwarting sophisticated cyberattacks. These strategies provide both theoretical and practical underpinnings for fortifying MCS security and lay a robust foundation for the field's future evolution. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Hardcover. Condition: new. Hardcover. This book investigates technologies that enable more powerful resources and improve resource utilization for end-edge-cloud networks. The authors cover tools such as federated learning (FL) and real-time inference in industrial IoT and they present a novel communication and computation integration architecture for end-edge-cloud networks. Under the considered end-edge-cloud network architecture, the authors then propose different resource scheduling schemes based on centralized and distributed deep reinforcement learning methods to improve overall resource utilization for guaranteeing the diversified quality of service (QoS) requirements from different applications. The proposed architecture and schemes can not only be adopted in future end-edge-cloud networks to efficiently manage the multi-dimensional resources in real time, but also provide useful guidelines for multi-dimensional resource scheduling scheme designing and resource utilization enhancement in complex end-edge-cloud networks with diversified data services and applications. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book investigates technologies that enable more powerful resources and improve resource utilization for end-edge-cloud networks. The authors cover tools such as federated learning (FL) and real-time inference in industrial IoT and they present a novel communication and computation integration architecture for end-edge-cloud networks. Under the considered end-edge-cloud network architecture, the authors then propose different resource scheduling schemes based on centralized and distributed deep reinforcement learning methods to improve overall resource utilization for guaranteeing the diversified quality of service (QoS) requirements from different applications. The proposed architecture and schemes can not only be adopted in future end-edge-cloud networks to efficiently manage the multi-dimensional resources in real time, but also provide useful guidelines for multi-dimensional resource scheduling scheme designing and resource utilization enhancement in complex end-edge-cloud networks with diversified data services and applications. 145 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.

Hardcover. Condition: new. Hardcover. This book investigates technologies that enable more powerful resources and improve resource utilization for end-edge-cloud networks. The authors cover tools such as federated learning (FL) and real-time inference in industrial IoT and they present a novel communication and computation integration architecture for end-edge-cloud networks. Under the considered end-edge-cloud network architecture, the authors then propose different resource scheduling schemes based on centralized and distributed deep reinforcement learning methods to improve overall resource utilization for guaranteeing the diversified quality of service (QoS) requirements from different applications. The proposed architecture and schemes can not only be adopted in future end-edge-cloud networks to efficiently manage the multi-dimensional resources in real time, but also provide useful guidelines for multi-dimensional resource scheduling scheme designing and resource utilization enhancement in complex end-edge-cloud networks with diversified data services and applications. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condition: New. Print on Demand.

Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book investigates technologies that enable more powerful resources and improve resource utilization for end-edge-cloud networks. The authors cover tools such as federated learning (FL) and real-time inference in industrial IoT and they present a novel communication and computation integration architecture for end-edge-cloud networks. Under the considered end-edge-cloud network architecture, the authors then propose different resource scheduling schemes based on centralized and distributed deep reinforcement learning methods to improve overall resource utilization for guaranteeing the diversified quality of service (QoS) requirements from different applications. The proposed architecture and schemes can not only be adopted in future end-edge-cloud networks to efficiently manage the multi-dimensional resources in real time, but also provide useful guidelines for multi-dimensional resource scheduling scheme designing and resource utilization enhancement in complex end-edge-cloud networks with diversified data services and applications.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 160 pp. Englisch.

Condition: New. PRINT ON DEMAND.

Buch. Condition: Neu. Data Privacy and Cybersecurity in Mobile Crowdsensing | Buch | Englisch | 2025 | MDPI AG | EAN 9783725845408 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.