04135nam 2200973z- 450 991055771420332120231214133030.0(CKB)5400000000046183(oapen)https://directory.doabooks.org/handle/20.500.12854/76847(EXLCZ)99540000000004618320202201d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierEdge/Fog Computing Technologies for IoT InfrastructureBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 electronic resource (231 p.)3-0365-1456-2 3-0365-1455-4 The prevalence of smart devices and cloud computing has led to an explosion in the amount of data generated by IoT devices. Moreover, emerging IoT applications, such as augmented and virtual reality (AR/VR), intelligent transportation systems, and smart factories require ultra-low latency for data communication and processing. Fog/edge computing is a new computing paradigm where fully distributed fog/edge nodes located nearby end devices provide computing resources. By analyzing, filtering, and processing at local fog/edge resources instead of transferring tremendous data to the centralized cloud servers, fog/edge computing can reduce the processing delay and network traffic significantly. With these advantages, fog/edge computing is expected to be one of the key enabling technologies for building the IoT infrastructure. Aiming to explore the recent research and development on fog/edge computing technologies for building an IoT infrastructure, this book collected 10 articles. The selected articles cover diverse topics such as resource management, service provisioning, task offloading and scheduling, container orchestration, and security on edge/fog computing infrastructure, which can help to grasp recent trends, as well as state-of-the-art algorithms of fog/edge computing technologies.Information technology industriesbicssccloud computingcontainer orchestrationcustom metricsDockeredge computingHorizontal Pod Autoscaling (HPA)KubernetesPrometheusresource metricsfog computingtask allocationmulti-objective optimizationevolutionary geneticshyper-anglecrowding distancecontainersleader electionload balancingstatefulmulti-access edge computingorchestratortask offloadingfuzzy logic5Gfog/edge computingservice provisioningservice placementservice offloadingInternet of Things (IoT)task schedulingmarkov decision process (MDP)deep reinforcement learning (DRL)resource managementalgorithm classificationevaluation frameworkwebWeb AssemblyOpenCLLWCfast implementationInternet of thingsIoT actordata managerGDPRcomputingcomputational offloadingdynamic offloading thresholdminimizing delayminimizing energy consumptionmaximizing throughputsInformation technology industriesYoo Seong-eunedt1328750Kim TaehongedtKim YoungsooedtYoo Seong-eunothKim TaehongothKim YoungsooothBOOK9910557714203321Edge3039491UNINA