LEADER 04078nam 22005895 450 001 9910865237603321 005 20240601125437.0 010 $a9789819726448$b(electronic bk.) 010 $z9789819726431 024 7 $a10.1007/978-981-97-2644-8 035 $a(MiAaPQ)EBC31360220 035 $a(Au-PeEL)EBL31360220 035 $a(CKB)32213009700041 035 $a(DE-He213)978-981-97-2644-8 035 $a(EXLCZ)9932213009700041 100 $a20240601d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aResource Management in Distributed Systems /$fedited by Anwesha Mukherjee, Debashis De, Rajkumar Buyya 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (319 pages) 225 1 $aStudies in Big Data,$x2197-6511 ;$v151 311 08$aPrint version: Mukherjee, Anwesha Resource Management in Distributed Systems Singapore : Springer Singapore Pte. Limited,c2024 9789819726431 327 $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. 330 $aThis book focuses on resource management in distributed computing systems. The book presents a collection of original, unpublished, and high-quality research works, which report the latest research advances on resource discovery, allocation, scheduling, etc., in cloud, fog, and edge computing. The topics covered in the book are resource management in cloud computing/edge computing/fog computing/dew computing, resource management in Internet of things, resource allocation, scheduling, monitoring, and orchestration in distributed computing systems, resource management in 5G network and beyond, latency-aware resource management, energy-efficient resource management, interoperability and portability, security and privacy in resource management, reliable resource management, trustworthiness in resource management, fault tolerance in resource management, and simulation related to resource management. 410 0$aStudies in Big Data,$x2197-6511 ;$v151 606 $aComputational intelligence 606 $aCloud computing 606 $aInternet of things 606 $aComputational Intelligence 606 $aCloud Computing 606 $aInternet of Things 615 0$aComputational intelligence. 615 0$aCloud computing. 615 0$aInternet of things. 615 14$aComputational Intelligence. 615 24$aCloud Computing. 615 24$aInternet of Things. 676 $a006.3 700 $aMukherjee$b Anwesha$01742670 701 $aDe$b Debashis$01346723 701 $aBuyya$b Rajkumar$0722089 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910865237603321 996 $aResource Management in Distributed Systems$94169382 997 $aUNINA