Energy Conservation Solutions for Fog-Edge Computing Paradigms

Energy Conservation Solutions for Fog-Edge Computing Paradigms [electronic resource] / edited by Rajeev Tiwari, Mamta Mittal, Lalit Mohan Goyal. - 1st ed. 2022. - 1 online resource - Lecture Notes on Data Engineering and Communications Technologies, 74 2367-4520 ; . - Lecture Notes on Data Engineering and Communications Technologies, 74 .

Energy-aware resource scheduling in FoG environment for IoT-based applications -- DoSP: A Deadline-Aware Dynamic Service Placement Algorithm for Workflow-oriented IoT Applications in Fog-Cloud Computing Environments -- Improvement of Task Offloading for Latency Sensitive Tasks in Fog Environment -- A Sustainable Energy Efficient IoT-Based Solution for Real Time Traffic Assistance using Fog Computing -- Analysis on Application of Fog Computing in Industry 4.0 and Smart Cities -- Fog-Computing: A Novel Approach For Cloud-based devices Using Perceptual Cloning Manifestation-PERCOLNIF Taxonomy by Energy Optimization -- Performance Evaluation and Energy Efficient VM Placement for Fog assisted IoT Environment -- Load Balancing in Fog Computing using QoS -- Fog Computing in Industry 4.0: Applications and Challenges – A Research Roadmap -- Fog Computing based Architecture for Smart City Projects and Applications -- Integration of Fog Computing and IoT Based Energy Harvesting (EHIoT) Model for Wireless Sensor Network -- Design and Development of Efficient Secure Routing Mechanism For Wireless Sensor Network -- Futuristic Communication Systems using Mobile Edge Computing -- Methodology to ensure the continuity of the information systems service, based on the monitoring of electrical energy, using IOT technology.

This book focuses on energy efficiency concerns in fog–edge computing and the requirements related to Industry 4.0 and next-generation networks like 5G and 6G. This book guides the research community about practical approaches, methodological, and moral questions in any nations’ journey to conserve energy in fog–edge computing environments. It discusses a detailed approach required to conserve energy and comparative case studies with respect to various performance evaluation metrics, such as energy conservation, resource allocation strategies, task allocation strategies, VM migration, and load-sharing strategies with state-of-the-art approaches, with fog and edge networks.

9789811634482

10.1007/978-981-16-3448-2 doi


Internet of things.
Computer Networks.
Cloud Computing.
Electric power distribution.
Internet of Things.
Computer Networks.
Cloud Computing.
Energy Grids and Networks.

Electronic data processing -- Distributed processing Internet of things

QA76.9.D5
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