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020 _a9789819726448
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024 7 _a10.1007/978-981-97-2644-8
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
245 1 0 _aResource Management in Distributed Systems
_h[electronic resource] /
_cedited by Anwesha Mukherjee, Debashis De, Rajkumar Buyya.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXII, 314 p. 88 illus., 75 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Big Data,
_x2197-6511 ;
_v151
505 0 _aResource Management in Distributed Computing -- Cloud Computing Resource Management -- Resource Allocation and Placement in Multi-access Edge Computing -- Resource Scheduling in Integrated IoT and Fog Computing Environments: A Taxonomy, Survey and Future Directions -- Trusted task offloading and resource allocation strategy in MEC environment -- Resource Management in Edge Clouds: Latency-aware Approaches for Big Data Analysis -- FSRmSTS – An Optimized Task Scheduling with a Hybrid Approach: Integrating FCFS, SJF, and RR with Median Standard Time Slice -- Container Orchestration in Heterogeneous Edge Computing Environments -- Resource targeted cybersecurity attacks in cloud computing environments -- Load balancing using Swarm intelligence in cloud Environment -- Interoperability and Portability in Big Data Analysis based Cloud-Fog-Edge-Dew Computing -- Cyber attack victim separation: new dimensions to minimize attack effects by resource management -- eBPF and XDP Technologies as Enablers for Ultra-Fast and Programmable Next-Gen Network Infrastructures -- Deep Reinforcement Learning (DRL)-based Methods for Serverless Stream Processing Engines: A Vision, Architectural Elements, and Future Directions.
520 _aThis book focuses on resource management in distributed computing systems. The book presents a collection of original, unpublished, and high-quality research works, which report the latest research advances on resource discovery, allocation, scheduling, etc., in cloud, fog, and edge computing. The topics covered in the book are resource management in cloud computing/edge computing/fog computing/dew computing, resource management in Internet of things, resource allocation, scheduling, monitoring, and orchestration in distributed computing systems, resource management in 5G network and beyond, latency-aware resource management, energy-efficient resource management, interoperability and portability, security and privacy in resource management, reliable resource management, trustworthiness in resource management, fault tolerance in resource management, and simulation related to resource management.
650 0 _aComputational intelligence.
_964052
650 0 _aCloud Computing.
_958386
650 0 _aInternet of things.
_958845
650 1 4 _aComputational Intelligence.
_964052
650 2 4 _aCloud Computing.
_958386
650 2 4 _aInternet of Things.
_958845
700 1 _aMukherjee, Anwesha.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_978127
700 1 _aDe, Debashis.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_965907
700 1 _aBuyya, Rajkumar.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819726431
776 0 8 _iPrinted edition:
_z9789819726455
776 0 8 _iPrinted edition:
_z9789819726462
830 0 _aStudies in Big Data,
_x2197-6511 ;
_v151
_968724
856 4 0 _uhttps://doi.org/10.1007/978-981-97-2644-8
912 _aZDB-2-INR
912 _aZDB-2-SXIT
999 _c60459
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