Haris et al., 2022 - Google Patents
A systematic review on load balancing tools and techniques in cloud computingHaris et al., 2022
View PDF- Document ID
- 15148284013618700049
- Author
- Haris M
- Khan R
- Publication year
- Publication venue
- Inventive Systems and Control: Proceedings of ICISC 2022
External Links
Snippet
Nowadays, cloud computing attracted wide attention as it can deliver IT services and resources on a demand basis over the Internet. Load balancing is a key challenge in cloud computing. Due to the complex structure of cloud computing, it is difficult and costly to …
- 238000000034 method 0 title abstract description 35
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5061—Partitioning or combining of resources
- G06F9/5072—Grid computing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
- G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
- G06F9/5055—Allocation 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 software capabilities, i.e. software resources associated or available to the machine
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5061—Partitioning or combining of resources
- G06F9/5066—Algorithms for mapping a plurality of inter-dependent sub-tasks onto a plurality of physical CPUs
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
- G06F9/48—Programme initiating; Programme switching, e.g. by interrupt
- G06F9/4806—Task transfer initiation or dispatching
- G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
- G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
- G06F9/54—Interprogramme communication; Intertask communication
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/44—Arrangements for executing specific programmes
- G06F9/455—Emulation; Software simulation, i.e. virtualisation or emulation of application or operating system execution engines
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2209/00—Indexing scheme relating to G06F9/00
- G06F2209/50—Indexing scheme relating to G06F9/50
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording 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
- G06F11/3457—Performance evaluation by simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F15/00—Digital computers in general; Data processing equipment in general
- G06F15/16—Combinations of two or more digital computers each having at least an arithmetic unit, a programme unit and a register, e.g. for a simultaneous processing of several programmes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Mansouri et al. | Cloud computing simulators: A comprehensive review | |
Ahn et al. | Flux: Overcoming scheduling challenges for exascale workflows | |
Abdelmaboud et al. | Quality of service approaches in cloud computing: A systematic mapping study | |
Fakhfakh et al. | Simulation tools for cloud computing: A survey and comparative study | |
Malhotra et al. | Study and comparison of CloudSim simulators in the cloud computing | |
Nesmachnow et al. | Heterogeneous computing scheduling with evolutionary algorithms | |
Shi et al. | Fast multi-resource allocation with patterns in large scale cloud data center | |
Del-Pozo-Puñal et al. | A scalable simulator for cloud, fog and edge computing platforms with mobility support | |
Haris et al. | A systematic review on load balancing tools and techniques in cloud computing | |
Choudhary et al. | Energy-aware scientific workflow scheduling in cloud environment | |
Turin et al. | A formal model of the kubernetes container framework | |
Barika et al. | IoTSim-Stream: Modelling stream graph application in cloud simulation | |
Saleh et al. | A dynamic simulation environment for container-based cloud data centers using containercloudsim | |
Tchernykh et al. | Mitigating uncertainty in developing and applying scientific applications in an integrated computing environment | |
Singh et al. | Performance evaluation of genetic algorithm and flower pollination algorithm for scheduling tasks in cloud computing | |
Tuli et al. | SimTune: Bridging the simulator reality gap for resource management in edge-cloud computing | |
Ahn et al. | Scalable composition and analysis techniques for massive scientific workflows | |
Naik et al. | The changing landscape of machine learning: A comparative analysis of centralized machine learning, distributed machine learning and federated machine learning | |
Carothers et al. | Computational challenges in modeling and simulation | |
Jalali Khalil Abadi et al. | Deep reinforcement learning-based scheduling in distributed systems: a critical review | |
Asir Antony Gnana Singh et al. | Analysis of cloud environment using cloudsim | |
da Rosa Righi et al. | MigPF: Towards on self-organizing process rescheduling of bulk-synchronous parallel applications | |
Patel et al. | A comprehensive assessment and comparative analysis of simulations tools for cloud computing | |
Serrano-Iglesias et al. | A self-scalable distributed network simulation environment based on cloud computing | |
Lebre et al. | Vmplaces: A generic tool to investigate and compare vm placement algorithms |