[go: up one dir, main page]

Sharma et al., 2021 - Google Patents

An Empirical Study of Different Techniques for the Improvement of Quality of Service in Cloud Computing

Sharma et al., 2021

Document ID
448126530405931908
Author
Sharma C
Tiwari P
Agarwal G
Publication year
Publication venue
Data Engineering for Smart Systems: Proceedings of SSIC 2021

External Links

Snippet

In a large, heterogeneous, and distributed environment, the computing infrastructure expands, and resource management becomes a challenging task. In a cloud world, one experiences problems of resource distribution, triggered by items like heterogeneity …
Continue reading at link.springer.com (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46Multiprogramming arrangements
    • G06F9/50Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/505Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the load
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46Multiprogramming arrangements
    • G06F9/50Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5061Partitioning or combining of resources
    • G06F9/5072Grid computing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46Multiprogramming arrangements
    • G06F9/48Programme initiating; Programme switching, e.g. by interrupt
    • G06F9/4806Task transfer initiation or dispatching
    • G06F9/4843Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/4881Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46Multiprogramming arrangements
    • G06F9/50Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5083Techniques for rebalancing the load in a distributed system
    • G06F9/5088Techniques for rebalancing the load in a distributed system involving task migration
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46Multiprogramming arrangements
    • G06F9/50Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5011Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for programme control, e.g. control unit
    • G06F9/06Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46Multiprogramming arrangements
    • G06F9/50Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5094Allocation of resources, e.g. of the central processing unit [CPU] where the allocation takes into account power or heat criteria
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring
    • G06F11/30Monitoring
    • G06F11/34Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3409Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F1/00Details of data-processing equipment not covered by groups G06F3/00 - G06F13/00, e.g. cooling, packaging or power supply specially adapted for computer application
    • G06F1/26Power supply means, e.g. regulation thereof
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F2209/00Indexing scheme relating to G06F9/00
    • G06F2209/50Indexing scheme relating to G06F9/50
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F2201/00Indexing scheme relating to error detection, to error correction, and to monitoring

Similar Documents

Publication Publication Date Title
Katal et al. Energy efficiency in cloud computing data centers: a survey on software technologies
Patel et al. Energy efficient strategy for placement of virtual machines selected from underloaded servers in compute Cloud
Zakarya et al. An energy aware cost recovery approach for virtual machine migration
Zikos et al. Performance and energy aware cluster-level scheduling of compute-intensive jobs with unknown service times
Udayasankaran et al. Energy efficient resource utilization and load balancing in virtual machines using prediction algorithms
Singh et al. A comprehensive review of cloud computing virtual machine consolidation
Chaabouni et al. Energy management strategy in cloud computing: a perspective study
Hasan et al. Heuristic based energy-aware resource allocation by dynamic consolidation of virtual machines in cloud data center.
Kamran et al. QoS-aware VM placement and migration for hybrid cloud infrastructure
Chehelgerdi-Samani et al. PCVM. ARIMA: predictive consolidation of virtual machines applying ARIMA method
Kulshrestha et al. An efficient host overload detection algorithm for cloud data center based on exponential weighted moving average
Banerjee et al. Efficient resource utilization using multi-step-ahead workload prediction technique in cloud.
Altomare et al. Data analytics for energy-efficient clouds: design, implementation and evaluation
Han et al. Energy efficient VM scheduling for big data processing in cloud computing environments
Zhang et al. Dynamic energy-efficient virtual machine placement optimization for virtualized clouds
Xu et al. Energy-Efficient Dynamic Consolidation of Virtual Machines in Big Data Centers
Surya et al. Prediction of resource contention in cloud using second order Markov model
Rahmani et al. SPP: stochastic process-based placement for VM consolidation in cloud environments
CU et al. Fuzzy based energy efficient workload management system for flash crowd
Thiam et al. Cooperative scheduling anti-load balancing algorithm for cloud: Csaac
Kumar Mishra et al. Cs-based energy-efficient service allocation in cloud
Balusamy et al. Ant colony-based load balancing and fault recovery for cloud computing environment
Sharma et al. An Empirical Study of Different Techniques for the Improvement of Quality of Service in Cloud Computing
Gribaudo et al. Analysis of the influence of application deployment on energy consumption
Guo et al. SAVE: self-adaptive consolidation of virtual machines for energy efficiency of CPU-intensive applications in the cloud