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Full Description
Cloud computing has been a game changer for internet-based applications such as content delivery networks, social networking and multi-tier enterprise applications. However, the requirements for low-latency data access, security, bandwidth, mobility, and cost have challenged centralized data center-based cloud computing models, which is driving the need for the novel computing paradigms of edge and fog computing. The internet of things (IoT) focuses on discovery, aggregation, management, and acting on data originating from internet-connected devices via programmable sensors, actuators, mobile phones, surveillance cameras, routers, gateways and switches. But the aggregation of this data is expensive and can be time consuming.
Traditional cloud-centric resource management models need to move towards more distributed and decentralized models so that they can cope with the challenges posed by the evolution of IoT smart devices and network solutions. However, supporting IoT data processing across cloud and edge data centers is not a trivial challenge. IoT sensing devices must be configured as a collection of data-analytics driven workflows where each node in the process can essentially run on multiple heterogeneous cloud and edge data centers.
This book presents state-of-the-art interdisciplinary computing research in the application lifecycle management for internet of things in edge and cloud computing. The book addresses challenges from a distributed system perspective that includes both cyber and physical aspects. The authors aim to bring together the four paradigms of cloud and edge computing, cyber physical systems, internet of things and big data for future ICT systems.
Written and edited by an international team of experts in the field, this book offers key insights to researchers, engineers, IT professionals, advanced students, postgraduate students and lecturers working in the fields of parallel and distributed computing, data mining, information retrieval, cloud, edge and fog computing, and the IoT.
Contents
Chapter 1: Task offloading using fog analytics
Chapter 2: Resource management in edge and fog computing using FogBus2 framework
Chapter 3: Resource management and cloud-RAN implementation for narrowband-IoT systems
Chapter 4: Introduction to benchmarking IoT middleware platforms
Chapter 5: SLA conceptual model for IoT applications
Chapter 6: SLA representation and awareness within blockchain in the context of IoT
Chapter 7: IoT monitoring with blockchain: generating smart contracts from service level agreements
Chapter 8: Intrusion detection and prevention in software-defined networks
Chapter 9: Privacy challenges for Internet of Medical Things
Chapter 10: Quality-aware Internet of Things applications
Chapter 11: IoT deployment and management in the smart grid
Chapter 12: Consensus algorithm for energy applications: case study on P2P energy trading scenario
Chapter 13: Streamed gaming
