Jaradat et al., 2020 - Google Patents
Multiple users replica selection in data grids for fair user satisfaction: A hybrid approachJaradat et al., 2020
View PDF- Document ID
- 5586068785141509390
- Author
- Jaradat A
- Alhussian H
- Patel A
- Fati S
- Publication year
- Publication venue
- Computer Standards & Interfaces
External Links
Snippet
Replica selection in data grids aims to select the best replica location based on the quality-of- service parameters preferred by the user. This choice is important because of the limited number of available data resources in comparison with the large number of users. Typically …
- 238000004422 calculation algorithm 0 abstract description 38
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
-
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network-specific arrangements or communication protocols supporting networked applications
- H04L67/10—Network-specific arrangements or communication protocols supporting networked applications in which an application is distributed across nodes in the network
- H04L67/1002—Network-specific arrangements or communication protocols supporting networked applications in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers, e.g. load balancing
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance or administration or management of packet switching networks
- H04L41/14—Arrangements for maintenance or administration or management of packet switching networks involving network analysis or design, e.g. simulation, network model or planning
- H04L41/145—Arrangements for maintenance or administration or management of packet switching networks involving network analysis or design, e.g. simulation, network model or planning involving simulating, designing, planning or modelling of a network
-
- 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
-
- 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
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/06—Investment, e.g. financial instruments, portfolio management or fund management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
-
- 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
- G06Q30/00—Commerce, e.g. shopping or e-commerce
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/12—Computer systems based on biological models using genetic models
- G06N3/126—Genetic algorithms, i.e. information processing using digital simulations of the genetic system
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
- G06F2217/78—Power analysis and optimization
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Seghir et al. | A hybrid approach using genetic and fruit fly optimization algorithms for QoS-aware cloud service composition | |
Zhou et al. | Minimizing cost and makespan for workflow scheduling in cloud using fuzzy dominance sort based HEFT | |
Iranmanesh et al. | DCHG-TS: a deadline-constrained and cost-effective hybrid genetic algorithm for scientific workflow scheduling in cloud computing | |
Ghobaei-Arani et al. | An efficient resource provisioning approach for analyzing cloud workloads: a metaheuristic-based clustering approach | |
Szabo et al. | Science in the cloud: Allocation and execution of data-intensive scientific workflows | |
Zhang et al. | Multi-objective scheduling of many tasks in cloud platforms | |
Lin et al. | Dynamic multiservice load balancing in cloud-based multimedia system | |
Gao et al. | A multi-objective ant colony system algorithm for virtual machine placement in cloud computing | |
WO2016165392A1 (en) | Genetic algorithm-based cloud computing resource scheduling method | |
Xu et al. | Blockchain-based cloudlet management for multimedia workflow in mobile cloud computing | |
Tripathi et al. | Modified dragonfly algorithm for optimal virtual machine placement in cloud computing | |
Shi et al. | A genetic-based approach to location-aware cloud service brokering in multi-cloud environment | |
Rawat et al. | Virtual machine allocation to the task using an optimization method in cloud computing environment | |
Li et al. | Energy cost minimization with job security guarantee in Internet data center | |
Chen et al. | Scheduling independent tasks in cloud environment based on modified differential evolution | |
Tripathi et al. | Energy efficient VM placement for effective resource utilization using modified binary PSO | |
Jaradat et al. | Multiple users replica selection in data grids for fair user satisfaction: A hybrid approach | |
Cai et al. | Multitasking bi-level evolutionary algorithm for data-intensive scientific workflows on clouds | |
Priya et al. | To optimize load of hybrid P2P cloud data-center using efficient load optimization and resource minimization algorithm | |
Ziafat et al. | A method for the optimum selection of datacenters in geographically distributed clouds | |
El Gaily et al. | Constrained quantum optimization for resource distribution management | |
Younis et al. | Genetic algorithm for independent job scheduling in grid computing | |
AbdulHamed et al. | A genetic algorithm for service flow management with budget constraint in heterogeneous computing | |
Ma et al. | Aiming at QoS: A modified DE algorithm for task allocation in cloud computing | |
Wei et al. | Burstable resource compatible general resource scheduling for stochastic demands in heterogeneous cloudsU+ 2605 |