[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Ilager et al., 2020 - Google Patents

Artificial intelligence (ai)-centric management of resources in modern distributed computing systems

Ilager et al., 2020

View PDF
Document ID
7480633054341135566
Author
Ilager S
Muralidhar R
Buyya R
Publication year
Publication venue
2020 IEEE Cloud Summit

External Links

Snippet

Contemporary Distributed Computing Systems (DCS) such as Cloud Data Centers are large scale, complex, heterogeneous, and distributed across multiple networks and geographical boundaries. On the other hand, the Internet of Things (IoT)-driven applications are producing …
Continue reading at arxiv.org (PDF) (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]
    • G06F9/5061Partitioning or combining of resources
    • 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
    • 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
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • 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
    • G06F15/00Digital computers in general; Data processing equipment in general
    • G06F15/16Combinations 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/04Inference methods or devices
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/02Knowledge representation
    • G06N5/022Knowledge engineering, knowledge acquisition
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computer systems based on specific mathematical models
    • G06N7/005Probabilistic networks

Similar Documents

Publication Publication Date Title
Ilager et al. Artificial intelligence (ai)-centric management of resources in modern distributed computing systems
US11048498B2 (en) Edge computing platform
Xu et al. CoScal: Multifaceted scaling of microservices with reinforcement learning
US11283863B1 (en) Data center management using digital twins
Mirmohseni et al. Using Markov learning utilization model for resource allocation in cloud of thing network
US10007513B2 (en) Edge intelligence platform, and internet of things sensor streams system
Alsadie A comprehensive review of AI techniques for resource management in fog computing: Trends, challenges and future directions
Bendriss et al. AI for SLA management in programmable networks
US12067417B2 (en) Automatic container migration system
Becker et al. Towards aiops in edge computing environments
Bendriss et al. Forecasting and anticipating SLO breaches in programmable networks
Meng et al. Deepscaler: Holistic autoscaling for microservices based on spatiotemporal gnn with adaptive graph learning
Kumar et al. Association learning based hybrid model for cloud workload prediction
US11829799B2 (en) Distributed resource-aware training of machine learning pipelines
Velu et al. CloudAIBus: a testbed for AI based cloud computing environments
Aslani et al. Machine learning inference serving models in serverless computing: a survey
Morichetta et al. Demystifying deep learning in predictive monitoring for cloud-native SLOs
Pasricha et al. Data analytics enables energy-efficiency and robustness: from mobile to manycores, datacenters, and networks (special session paper)
Selvarajan AI-Driven Cloud Resource Management and Orchestration
Zámečníková et al. Comparison of platforms for high frequency data processing
Angelis et al. A Survey on the Landscape of Self-adaptive Cloud Design and Operations Patterns: Goals, Strategies, Tooling, Evaluation and Dataset Perspectives
Khan et al. EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments
Iftikhar Artificial Intelligence based Resource Management in Fog Computing
Liu Robust resource management in distributed stream processing systems
Kallimani et al. Stochastic Model of a Sensor Node